diff --git a/README.md b/README.md --- a/README.md +++ b/README.md @@ -1,20 +1,31 @@ # Amazon Machine Learning SDK -> _Warning:_ This is an experimental preview release which is still under heavy development and not intended for public consumption, _caveat emptor_! - +* [Version](#version) * [Description](#description) * [Contribute](#contribute) * [Licence](#licence) + +## Version + +`1.0.0` + + ## Description -Amazon Machine Learning (Amazon ML) is a robust machine learning platform -that allows software developers to build and train predictive applications -and host those applications in a scalable AWS cloud solution. +Definition of the public APIs exposed by Amazon Machine Learning Documentation is available via [Hackage](http://hackage.haskell.org/package/amazonka-ml) and the [AWS API Reference](http://docs.aws.amazon.com/machine-learning/latest/APIReference/Welcome.html). +The types from this library are intended to be used with [amazonka](http://hackage.haskell.org/package/amazonka), +which provides mechanisms for specifying AuthN/AuthZ information and sending requests. + +Use of lenses is required for constructing and manipulating types. +This is due to the amount of nesting of AWS types and transparency regarding +de/serialisation into more palatable Haskell values. +The provided lenses should be compatible with any of the major lens libraries +[lens](http://hackage.haskell.org/package/lens) or [lens-family-core](http://hackage.haskell.org/package/lens-family-core). ## Contribute diff --git a/amazonka-ml.cabal b/amazonka-ml.cabal --- a/amazonka-ml.cabal +++ b/amazonka-ml.cabal @@ -1,27 +1,33 @@ name: amazonka-ml -version: 0.3.6 +version: 1.0.0 synopsis: Amazon Machine Learning SDK. homepage: https://github.com/brendanhay/amazonka license: OtherLicense license-file: LICENSE author: Brendan Hay maintainer: Brendan Hay -copyright: Copyright (c) 2013-2014 Brendan Hay +copyright: Copyright (c) 2013-2015 Brendan Hay category: Network, AWS, Cloud, Distributed Computing build-type: Simple extra-source-files: README.md cabal-version: >= 1.10 description: - Amazon Machine Learning (Amazon ML) is a robust machine learning platform - that allows software developers to build and train predictive applications - and host those applications in a scalable AWS cloud solution. - + Definition of the public APIs exposed by Amazon Machine Learning . - /See:/ + The types from this library are intended to be used with + , which provides + mechanisms for specifying AuthN/AuthZ information and sending requests. . - /Warning:/ This is an experimental preview release which is still under - heavy development and not intended for public consumption, caveat emptor! + Use of lenses is required for constructing and manipulating types. + This is due to the amount of nesting of AWS types and transparency regarding + de/serialisation into more palatable Haskell values. + The provided lenses should be compatible with any of the major lens libraries + such as or + . + . + See "Network.AWS.MachineLearning" and the + to get started. source-repository head type: git @@ -61,9 +67,40 @@ , Network.AWS.MachineLearning.UpdateDataSource , Network.AWS.MachineLearning.UpdateEvaluation , Network.AWS.MachineLearning.UpdateMLModel + , Network.AWS.MachineLearning.Waiters other-modules: + Network.AWS.MachineLearning.Types.Product + , Network.AWS.MachineLearning.Types.Sum build-depends: - amazonka-core == 0.3.6.* + amazonka-core == 1.0.0.* , base >= 4.7 && < 5 + +test-suite amazonka-ml-test + type: exitcode-stdio-1.0 + default-language: Haskell2010 + hs-source-dirs: test + main-is: Main.hs + + ghc-options: -Wall -threaded + + -- This is not comprehensive if modules have manually been added. + -- It exists to ensure cabal 'somewhat' detects test module changes. + other-modules: + Test.AWS.MachineLearning + , Test.AWS.Gen.MachineLearning + , Test.AWS.MachineLearning.Internal + + build-depends: + amazonka-core == 1.0.0 + , amazonka-test == 1.0.0 + , amazonka-ml == 1.0.0 + , base + , bytestring + , lens + , tasty + , tasty-hunit + , text + , time + , unordered-containers diff --git a/gen/Network/AWS/MachineLearning.hs b/gen/Network/AWS/MachineLearning.hs --- a/gen/Network/AWS/MachineLearning.hs +++ b/gen/Network/AWS/MachineLearning.hs @@ -1,70 +1,390 @@ +{-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-duplicate-exports #-} + +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Amazon Machine Learning (Amazon ML) is a robust machine learning platform --- that allows software developers to build and train predictive applications --- and host those applications in a scalable AWS cloud solution. +-- Definition of the public APIs exposed by Amazon Machine Learning +-- +-- /See:/ module Network.AWS.MachineLearning - ( module Network.AWS.MachineLearning.CreateBatchPrediction - , module Network.AWS.MachineLearning.CreateDataSourceFromRDS + ( + -- * Service + MachineLearning + + -- * Errors + -- $errors + + -- ** InternalServerException + , _InternalServerException + + -- ** InvalidInputException + , _InvalidInputException + + -- ** IdempotentParameterMismatchException + , _IdempotentParameterMismatchException + + -- ** PredictorNotMountedException + , _PredictorNotMountedException + + -- ** ResourceNotFoundException + , _ResourceNotFoundException + + -- ** LimitExceededException + , _LimitExceededException + + -- * Waiters + -- $waiters + + -- ** MLModelAvailable + , mLModelAvailable + + -- ** BatchPredictionAvailable + , batchPredictionAvailable + + -- ** DataSourceAvailable + , dataSourceAvailable + + -- ** EvaluationAvailable + , evaluationAvailable + + -- * Operations + -- $operations + + -- ** DeleteDataSource + , module Network.AWS.MachineLearning.DeleteDataSource + + -- ** UpdateDataSource + , module Network.AWS.MachineLearning.UpdateDataSource + + -- ** CreateDataSourceFromRedshift , module Network.AWS.MachineLearning.CreateDataSourceFromRedshift + + -- ** CreateDataSourceFromS , module Network.AWS.MachineLearning.CreateDataSourceFromS - , module Network.AWS.MachineLearning.CreateEvaluation + + -- ** CreateMLModel , module Network.AWS.MachineLearning.CreateMLModel - , module Network.AWS.MachineLearning.CreateRealtimeEndpoint + + -- ** DeleteBatchPrediction , module Network.AWS.MachineLearning.DeleteBatchPrediction - , module Network.AWS.MachineLearning.DeleteDataSource - , module Network.AWS.MachineLearning.DeleteEvaluation + + -- ** UpdateBatchPrediction + , module Network.AWS.MachineLearning.UpdateBatchPrediction + + -- ** GetMLModel + , module Network.AWS.MachineLearning.GetMLModel + + -- ** GetDataSource + , module Network.AWS.MachineLearning.GetDataSource + + -- ** DeleteMLModel , module Network.AWS.MachineLearning.DeleteMLModel - , module Network.AWS.MachineLearning.DeleteRealtimeEndpoint + + -- ** UpdateMLModel + , module Network.AWS.MachineLearning.UpdateMLModel + + -- ** DescribeBatchPredictions (Paginated) , module Network.AWS.MachineLearning.DescribeBatchPredictions - , module Network.AWS.MachineLearning.DescribeDataSources - , module Network.AWS.MachineLearning.DescribeEvaluations - , module Network.AWS.MachineLearning.DescribeMLModels + + -- ** UpdateEvaluation + , module Network.AWS.MachineLearning.UpdateEvaluation + + -- ** DeleteEvaluation + , module Network.AWS.MachineLearning.DeleteEvaluation + + -- ** GetBatchPrediction , module Network.AWS.MachineLearning.GetBatchPrediction - , module Network.AWS.MachineLearning.GetDataSource - , module Network.AWS.MachineLearning.GetEvaluation - , module Network.AWS.MachineLearning.GetMLModel + + -- ** CreateEvaluation + , module Network.AWS.MachineLearning.CreateEvaluation + + -- ** CreateDataSourceFromRDS + , module Network.AWS.MachineLearning.CreateDataSourceFromRDS + + -- ** CreateBatchPrediction + , module Network.AWS.MachineLearning.CreateBatchPrediction + + -- ** Predict , module Network.AWS.MachineLearning.Predict - , module Network.AWS.MachineLearning.Types - , module Network.AWS.MachineLearning.UpdateBatchPrediction - , module Network.AWS.MachineLearning.UpdateDataSource - , module Network.AWS.MachineLearning.UpdateEvaluation - , module Network.AWS.MachineLearning.UpdateMLModel + + -- ** DeleteRealtimeEndpoint + , module Network.AWS.MachineLearning.DeleteRealtimeEndpoint + + -- ** DescribeEvaluations (Paginated) + , module Network.AWS.MachineLearning.DescribeEvaluations + + -- ** GetEvaluation + , module Network.AWS.MachineLearning.GetEvaluation + + -- ** CreateRealtimeEndpoint + , module Network.AWS.MachineLearning.CreateRealtimeEndpoint + + -- ** DescribeMLModels (Paginated) + , module Network.AWS.MachineLearning.DescribeMLModels + + -- ** DescribeDataSources (Paginated) + , module Network.AWS.MachineLearning.DescribeDataSources + + -- * Types + + -- ** Algorithm + , Algorithm (..) + + -- ** BatchPredictionFilterVariable + , BatchPredictionFilterVariable (..) + + -- ** DataSourceFilterVariable + , DataSourceFilterVariable (..) + + -- ** DetailsAttributes + , DetailsAttributes (..) + + -- ** EntityStatus + , EntityStatus (..) + + -- ** EvaluationFilterVariable + , EvaluationFilterVariable (..) + + -- ** MLModelFilterVariable + , MLModelFilterVariable (..) + + -- ** MLModelType + , MLModelType (..) + + -- ** RealtimeEndpointStatus + , RealtimeEndpointStatus (..) + + -- ** SortOrder + , SortOrder (..) + + -- ** BatchPrediction + , BatchPrediction + , batchPrediction + , bpStatus + , bpLastUpdatedAt + , bpCreatedAt + , bpInputDataLocationS3 + , bpMLModelId + , bpBatchPredictionDataSourceId + , bpBatchPredictionId + , bpName + , bpCreatedByIAMUser + , bpMessage + , bpOutputURI + + -- ** DataSource + , DataSource + , dataSource + , dsStatus + , dsNumberOfFiles + , dsLastUpdatedAt + , dsCreatedAt + , dsRDSMetadata + , dsDataSourceId + , dsDataSizeInBytes + , dsName + , dsCreatedByIAMUser + , dsDataLocationS3 + , dsComputeStatistics + , dsMessage + , dsRedshiftMetadata + , dsRoleARN + , dsDataRearrangement + + -- ** Evaluation + , Evaluation + , evaluation + , eStatus + , ePerformanceMetrics + , eLastUpdatedAt + , eCreatedAt + , eInputDataLocationS3 + , eMLModelId + , eName + , eCreatedByIAMUser + , eMessage + , eEvaluationId + , eEvaluationDataSourceId + + -- ** MLModel + , MLModel + , mLModel + , mlmStatus + , mlmTrainingParameters + , mlmLastUpdatedAt + , mlmCreatedAt + , mlmScoreThresholdLastUpdatedAt + , mlmInputDataLocationS3 + , mlmSizeInBytes + , mlmMLModelId + , mlmScoreThreshold + , mlmName + , mlmAlgorithm + , mlmCreatedByIAMUser + , mlmEndpointInfo + , mlmTrainingDataSourceId + , mlmMessage + , mlmMLModelType + + -- ** PerformanceMetrics + , PerformanceMetrics + , performanceMetrics + , pmProperties + + -- ** Prediction + , Prediction + , prediction + , pPredictedValue + , pPredictedLabel + , pPredictedScores + , pDetails + + -- ** RDSDataSpec + , RDSDataSpec + , rdsDataSpec + , rdsdsDataSchemaURI + , rdsdsDataSchema + , rdsdsDataRearrangement + , rdsdsDatabaseInformation + , rdsdsSelectSqlQuery + , rdsdsDatabaseCredentials + , rdsdsS3StagingLocation + , rdsdsResourceRole + , rdsdsServiceRole + , rdsdsSubnetId + , rdsdsSecurityGroupIds + + -- ** RDSDatabase + , RDSDatabase + , rdsDatabase + , rdsdInstanceIdentifier + , rdsdDatabaseName + + -- ** RDSDatabaseCredentials + , RDSDatabaseCredentials + , rdsDatabaseCredentials + , rdsdcUsername + , rdsdcPassword + + -- ** RDSMetadata + , RDSMetadata + , rdsMetadata + , rmSelectSqlQuery + , rmDataPipelineId + , rmDatabase + , rmDatabaseUserName + , rmResourceRole + , rmServiceRole + + -- ** RealtimeEndpointInfo + , RealtimeEndpointInfo + , realtimeEndpointInfo + , reiCreatedAt + , reiEndpointURL + , reiEndpointStatus + , reiPeakRequestsPerSecond + + -- ** RedshiftDataSpec + , RedshiftDataSpec + , redshiftDataSpec + , rDataSchemaURI + , rDataSchema + , rDataRearrangement + , rDatabaseInformation + , rSelectSqlQuery + , rDatabaseCredentials + , rS3StagingLocation + + -- ** RedshiftDatabase + , RedshiftDatabase + , redshiftDatabase + , rdDatabaseName + , rdClusterIdentifier + + -- ** RedshiftDatabaseCredentials + , RedshiftDatabaseCredentials + , redshiftDatabaseCredentials + , rdcUsername + , rdcPassword + + -- ** RedshiftMetadata + , RedshiftMetadata + , redshiftMetadata + , redSelectSqlQuery + , redRedshiftDatabase + , redDatabaseUserName + + -- ** S3DataSpec + , S3DataSpec + , s3DataSpec + , sdsDataSchema + , sdsDataSchemaLocationS3 + , sdsDataRearrangement + , sdsDataLocationS3 ) where -import Network.AWS.MachineLearning.CreateBatchPrediction -import Network.AWS.MachineLearning.CreateDataSourceFromRDS -import Network.AWS.MachineLearning.CreateDataSourceFromRedshift -import Network.AWS.MachineLearning.CreateDataSourceFromS -import Network.AWS.MachineLearning.CreateEvaluation -import Network.AWS.MachineLearning.CreateMLModel -import Network.AWS.MachineLearning.CreateRealtimeEndpoint -import Network.AWS.MachineLearning.DeleteBatchPrediction -import Network.AWS.MachineLearning.DeleteDataSource -import Network.AWS.MachineLearning.DeleteEvaluation -import Network.AWS.MachineLearning.DeleteMLModel -import Network.AWS.MachineLearning.DeleteRealtimeEndpoint -import Network.AWS.MachineLearning.DescribeBatchPredictions -import Network.AWS.MachineLearning.DescribeDataSources -import Network.AWS.MachineLearning.DescribeEvaluations -import Network.AWS.MachineLearning.DescribeMLModels -import Network.AWS.MachineLearning.GetBatchPrediction -import Network.AWS.MachineLearning.GetDataSource -import Network.AWS.MachineLearning.GetEvaluation -import Network.AWS.MachineLearning.GetMLModel -import Network.AWS.MachineLearning.Predict -import Network.AWS.MachineLearning.Types -import Network.AWS.MachineLearning.UpdateBatchPrediction -import Network.AWS.MachineLearning.UpdateDataSource -import Network.AWS.MachineLearning.UpdateEvaluation -import Network.AWS.MachineLearning.UpdateMLModel +import Network.AWS.MachineLearning.CreateBatchPrediction +import Network.AWS.MachineLearning.CreateDataSourceFromRDS +import Network.AWS.MachineLearning.CreateDataSourceFromRedshift +import Network.AWS.MachineLearning.CreateDataSourceFromS +import Network.AWS.MachineLearning.CreateEvaluation +import Network.AWS.MachineLearning.CreateMLModel +import Network.AWS.MachineLearning.CreateRealtimeEndpoint +import Network.AWS.MachineLearning.DeleteBatchPrediction +import Network.AWS.MachineLearning.DeleteDataSource +import Network.AWS.MachineLearning.DeleteEvaluation +import Network.AWS.MachineLearning.DeleteMLModel +import Network.AWS.MachineLearning.DeleteRealtimeEndpoint +import Network.AWS.MachineLearning.DescribeBatchPredictions +import Network.AWS.MachineLearning.DescribeDataSources +import Network.AWS.MachineLearning.DescribeEvaluations +import Network.AWS.MachineLearning.DescribeMLModels +import Network.AWS.MachineLearning.GetBatchPrediction +import Network.AWS.MachineLearning.GetDataSource +import Network.AWS.MachineLearning.GetEvaluation +import Network.AWS.MachineLearning.GetMLModel +import Network.AWS.MachineLearning.Predict +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.UpdateBatchPrediction +import Network.AWS.MachineLearning.UpdateDataSource +import Network.AWS.MachineLearning.UpdateEvaluation +import Network.AWS.MachineLearning.UpdateMLModel +import Network.AWS.MachineLearning.Waiters + +{- $errors +Error matchers are designed for use with the functions provided by +. +This allows catching (and rethrowing) service specific errors returned +by 'MachineLearning'. +-} + +{- $operations +Some AWS operations return results that are incomplete and require subsequent +requests in order to obtain the entire result set. The process of sending +subsequent requests to continue where a previous request left off is called +pagination. For example, the 'ListObjects' operation of Amazon S3 returns up to +1000 objects at a time, and you must send subsequent requests with the +appropriate Marker in order to retrieve the next page of results. + +Operations that have an 'AWSPager' instance can transparently perform subsequent +requests, correctly setting Markers and other request facets to iterate through +the entire result set of a truncated API operation. Operations which support +this have an additional note in the documentation. + +Many operations have the ability to filter results on the server side. See the +individual operation parameters for details. +-} + +{- $waiters +Waiters poll by repeatedly sending a request until some remote success condition +configured by the 'Wait' specification is fulfilled. The 'Wait' specification +determines how many attempts should be made, in addition to delay and retry strategies. +-} diff --git a/gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs b/gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs --- a/gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs +++ b/gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs @@ -1,179 +1,205 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.CreateBatchPrediction --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Generates predictions for a group of observations. The observations to --- process exist in one or more data files referenced by a 'DataSource'. This --- operation creates a new 'BatchPrediction', and uses an 'MLModel' and the data --- files referenced by the 'DataSource' as information sources. +-- Generates predictions for a group of observations. The observations to +-- process exist in one or more data files referenced by a 'DataSource'. +-- This operation creates a new 'BatchPrediction', and uses an 'MLModel' +-- and the data files referenced by the 'DataSource' as information +-- sources. -- --- 'CreateBatchPrediction' is an asynchronous operation. In response to 'CreateBatchPrediction', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'BatchPrediction' status to 'PENDING'. After the 'BatchPrediction' completes, Amazon ML sets the --- status to 'COMPLETED'. +-- 'CreateBatchPrediction' is an asynchronous operation. In response to +-- 'CreateBatchPrediction', Amazon Machine Learning (Amazon ML) immediately +-- returns and sets the 'BatchPrediction' status to 'PENDING'. After the +-- 'BatchPrediction' completes, Amazon ML sets the status to 'COMPLETED'. -- --- You can poll for status updates by using the 'GetBatchPrediction' operation --- and checking the 'Status' parameter of the result. After the 'COMPLETED' status --- appears, the results are available in the location specified by the 'OutputUri' --- parameter. +-- You can poll for status updates by using the GetBatchPrediction +-- operation and checking the 'Status' parameter of the result. After the +-- 'COMPLETED' status appears, the results are available in the location +-- specified by the 'OutputUri' parameter. -- --- +-- /See:/ for CreateBatchPrediction. module Network.AWS.MachineLearning.CreateBatchPrediction ( - -- * Request - CreateBatchPrediction - -- ** Request constructor - , createBatchPrediction - -- ** Request lenses - , cbpBatchPredictionDataSourceId - , cbpBatchPredictionId + -- * Creating a Request + createBatchPrediction + , CreateBatchPrediction + -- * Request Lenses , cbpBatchPredictionName + , cbpBatchPredictionId , cbpMLModelId - , cbpOutputUri + , cbpBatchPredictionDataSourceId + , cbpOutputURI - -- * Response - , CreateBatchPredictionResponse - -- ** Response constructor + -- * Destructuring the Response , createBatchPredictionResponse - -- ** Response lenses - , cbprBatchPredictionId + , CreateBatchPredictionResponse + -- * Response Lenses + , cbprsBatchPredictionId + , cbprsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data CreateBatchPrediction = CreateBatchPrediction - { _cbpBatchPredictionDataSourceId :: Text - , _cbpBatchPredictionId :: Text - , _cbpBatchPredictionName :: Maybe Text - , _cbpMLModelId :: Text - , _cbpOutputUri :: Text - } deriving (Eq, Ord, Read, Show) +-- | /See:/ 'createBatchPrediction' smart constructor. +data CreateBatchPrediction = CreateBatchPrediction' + { _cbpBatchPredictionName :: !(Maybe Text) + , _cbpBatchPredictionId :: !Text + , _cbpMLModelId :: !Text + , _cbpBatchPredictionDataSourceId :: !Text + , _cbpOutputURI :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'CreateBatchPrediction' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'CreateBatchPrediction' with the minimum fields required to make a request. -- --- * 'cbpBatchPredictionDataSourceId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'cbpBatchPredictionId' @::@ 'Text' +-- * 'cbpBatchPredictionName' -- --- * 'cbpBatchPredictionName' @::@ 'Maybe' 'Text' +-- * 'cbpBatchPredictionId' -- --- * 'cbpMLModelId' @::@ 'Text' +-- * 'cbpMLModelId' -- --- * 'cbpOutputUri' @::@ 'Text' +-- * 'cbpBatchPredictionDataSourceId' -- -createBatchPrediction :: Text -- ^ 'cbpBatchPredictionId' - -> Text -- ^ 'cbpMLModelId' - -> Text -- ^ 'cbpBatchPredictionDataSourceId' - -> Text -- ^ 'cbpOutputUri' - -> CreateBatchPrediction -createBatchPrediction p1 p2 p3 p4 = CreateBatchPrediction - { _cbpBatchPredictionId = p1 - , _cbpMLModelId = p2 - , _cbpBatchPredictionDataSourceId = p3 - , _cbpOutputUri = p4 - , _cbpBatchPredictionName = Nothing +-- * 'cbpOutputURI' +createBatchPrediction + :: Text -- ^ 'cbpBatchPredictionId' + -> Text -- ^ 'cbpMLModelId' + -> Text -- ^ 'cbpBatchPredictionDataSourceId' + -> Text -- ^ 'cbpOutputURI' + -> CreateBatchPrediction +createBatchPrediction pBatchPredictionId_ pMLModelId_ pBatchPredictionDataSourceId_ pOutputURI_ = + CreateBatchPrediction' + { _cbpBatchPredictionName = Nothing + , _cbpBatchPredictionId = pBatchPredictionId_ + , _cbpMLModelId = pMLModelId_ + , _cbpBatchPredictionDataSourceId = pBatchPredictionDataSourceId_ + , _cbpOutputURI = pOutputURI_ } --- | The ID of the 'DataSource' that points to the group of observations to predict. -cbpBatchPredictionDataSourceId :: Lens' CreateBatchPrediction Text -cbpBatchPredictionDataSourceId = - lens _cbpBatchPredictionDataSourceId - (\s a -> s { _cbpBatchPredictionDataSourceId = a }) +-- | A user-supplied name or description of the 'BatchPrediction'. +-- 'BatchPredictionName' can only use the UTF-8 character set. +cbpBatchPredictionName :: Lens' CreateBatchPrediction (Maybe Text) +cbpBatchPredictionName = lens _cbpBatchPredictionName (\ s a -> s{_cbpBatchPredictionName = a}); -- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. cbpBatchPredictionId :: Lens' CreateBatchPrediction Text -cbpBatchPredictionId = - lens _cbpBatchPredictionId (\s a -> s { _cbpBatchPredictionId = a }) - --- | A user-supplied name or description of the 'BatchPrediction'. 'BatchPredictionName' can only use the UTF-8 character set. -cbpBatchPredictionName :: Lens' CreateBatchPrediction (Maybe Text) -cbpBatchPredictionName = - lens _cbpBatchPredictionName (\s a -> s { _cbpBatchPredictionName = a }) +cbpBatchPredictionId = lens _cbpBatchPredictionId (\ s a -> s{_cbpBatchPredictionId = a}); -- | The ID of the 'MLModel' that will generate predictions for the group of -- observations. cbpMLModelId :: Lens' CreateBatchPrediction Text -cbpMLModelId = lens _cbpMLModelId (\s a -> s { _cbpMLModelId = a }) +cbpMLModelId = lens _cbpMLModelId (\ s a -> s{_cbpMLModelId = a}); +-- | The ID of the 'DataSource' that points to the group of observations to +-- predict. +cbpBatchPredictionDataSourceId :: Lens' CreateBatchPrediction Text +cbpBatchPredictionDataSourceId = lens _cbpBatchPredictionDataSourceId (\ s a -> s{_cbpBatchPredictionDataSourceId = a}); + -- | The location of an Amazon Simple Storage Service (Amazon S3) bucket or --- directory to store the batch prediction results. The following substrings are --- not allowed in the s3 key portion of the "outputURI" field: ':', '//', '/./', --- '/../'. +-- directory to store the batch prediction results. The following +-- substrings are not allowed in the s3 key portion of the \"outputURI\" +-- field: \':\', \'\/\/\', \'\/.\/\', \'\/..\/\'. -- --- Amazon ML needs permissions to store and retrieve the logs on your behalf. --- For information about how to set permissions, see the . -cbpOutputUri :: Lens' CreateBatchPrediction Text -cbpOutputUri = lens _cbpOutputUri (\s a -> s { _cbpOutputUri = a }) +-- Amazon ML needs permissions to store and retrieve the logs on your +-- behalf. For information about how to set permissions, see the +-- . +cbpOutputURI :: Lens' CreateBatchPrediction Text +cbpOutputURI = lens _cbpOutputURI (\ s a -> s{_cbpOutputURI = a}); -newtype CreateBatchPredictionResponse = CreateBatchPredictionResponse - { _cbprBatchPredictionId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest CreateBatchPrediction where + type Sv CreateBatchPrediction = MachineLearning + type Rs CreateBatchPrediction = + CreateBatchPredictionResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + CreateBatchPredictionResponse' <$> + (x .?> "BatchPredictionId") <*> (pure (fromEnum s))) --- | 'CreateBatchPredictionResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'cbprBatchPredictionId' @::@ 'Maybe' 'Text' --- -createBatchPredictionResponse :: CreateBatchPredictionResponse -createBatchPredictionResponse = CreateBatchPredictionResponse - { _cbprBatchPredictionId = Nothing - } +instance ToHeaders CreateBatchPrediction where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.CreateBatchPrediction" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. This value --- is identical to the value of the 'BatchPredictionId' in the request. -cbprBatchPredictionId :: Lens' CreateBatchPredictionResponse (Maybe Text) -cbprBatchPredictionId = - lens _cbprBatchPredictionId (\s a -> s { _cbprBatchPredictionId = a }) +instance ToJSON CreateBatchPrediction where + toJSON CreateBatchPrediction'{..} + = object + ["BatchPredictionName" .= _cbpBatchPredictionName, + "BatchPredictionId" .= _cbpBatchPredictionId, + "MLModelId" .= _cbpMLModelId, + "BatchPredictionDataSourceId" .= + _cbpBatchPredictionDataSourceId, + "OutputUri" .= _cbpOutputURI] instance ToPath CreateBatchPrediction where - toPath = const "/" + toPath = const "/" instance ToQuery CreateBatchPrediction where - toQuery = const mempty - -instance ToHeaders CreateBatchPrediction + toQuery = const mempty -instance ToJSON CreateBatchPrediction where - toJSON CreateBatchPrediction{..} = object - [ "BatchPredictionId" .= _cbpBatchPredictionId - , "BatchPredictionName" .= _cbpBatchPredictionName - , "MLModelId" .= _cbpMLModelId - , "BatchPredictionDataSourceId" .= _cbpBatchPredictionDataSourceId - , "OutputUri" .= _cbpOutputUri - ] +-- | Represents the output of a CreateBatchPrediction operation, and is an +-- acknowledgement that Amazon ML received the request. +-- +-- The CreateBatchPrediction operation is asynchronous. You can poll for +-- status updates by using the GetBatchPrediction operation and checking +-- the 'Status' parameter of the result. +-- +-- /See:/ 'createBatchPredictionResponse' smart constructor. +data CreateBatchPredictionResponse = CreateBatchPredictionResponse' + { _cbprsBatchPredictionId :: !(Maybe Text) + , _cbprsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest CreateBatchPrediction where - type Sv CreateBatchPrediction = MachineLearning - type Rs CreateBatchPrediction = CreateBatchPredictionResponse +-- | Creates a value of 'CreateBatchPredictionResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'cbprsBatchPredictionId' +-- +-- * 'cbprsStatus' +createBatchPredictionResponse + :: Int -- ^ 'cbprsStatus' + -> CreateBatchPredictionResponse +createBatchPredictionResponse pStatus_ = + CreateBatchPredictionResponse' + { _cbprsBatchPredictionId = Nothing + , _cbprsStatus = pStatus_ + } - request = post "CreateBatchPrediction" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. This +-- value is identical to the value of the 'BatchPredictionId' in the +-- request. +cbprsBatchPredictionId :: Lens' CreateBatchPredictionResponse (Maybe Text) +cbprsBatchPredictionId = lens _cbprsBatchPredictionId (\ s a -> s{_cbprsBatchPredictionId = a}); -instance FromJSON CreateBatchPredictionResponse where - parseJSON = withObject "CreateBatchPredictionResponse" $ \o -> CreateBatchPredictionResponse - <$> o .:? "BatchPredictionId" +-- | The response status code. +cbprsStatus :: Lens' CreateBatchPredictionResponse Int +cbprsStatus = lens _cbprsStatus (\ s a -> s{_cbprsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs b/gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs --- a/gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs +++ b/gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs @@ -1,212 +1,250 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.CreateDataSourceFromRDS --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Creates a 'DataSource' object from an --- (Amazon RDS). A 'DataSource' references data that can be used to perform 'CreateMLModel', 'CreateEvaluation', or 'CreateBatchPrediction' operations. +-- Creates a 'DataSource' object from an +-- (Amazon +-- RDS). A 'DataSource' references data that can be used to perform +-- CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations. -- --- 'CreateDataSourceFromRDS' is an asynchronous operation. In response to 'CreateDataSourceFromRDS', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'DataSource' status to 'PENDING'. After the 'DataSource' is created and ready for use, Amazon --- ML sets the 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or 'PENDING' --- status can only be used to perform 'CreateMLModel', 'CreateEvaluation', or 'CreateBatchPrediction' operations. +-- 'CreateDataSourceFromRDS' is an asynchronous operation. In response to +-- 'CreateDataSourceFromRDS', Amazon Machine Learning (Amazon ML) +-- immediately returns and sets the 'DataSource' status to 'PENDING'. After +-- the 'DataSource' is created and ready for use, Amazon ML sets the +-- 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or +-- 'PENDING' status can only be used to perform CreateMLModel, +-- CreateEvaluation, or CreateBatchPrediction operations. -- --- If Amazon ML cannot accept the input source, it sets the 'Status' parameter --- to 'FAILED' and includes an error message in the 'Message' attribute of the 'GetDataSource' operation response. +-- If Amazon ML cannot accept the input source, it sets the 'Status' +-- parameter to 'FAILED' and includes an error message in the 'Message' +-- attribute of the GetDataSource operation response. -- --- +-- /See:/ for CreateDataSourceFromRDS. module Network.AWS.MachineLearning.CreateDataSourceFromRDS ( - -- * Request - CreateDataSourceFromRDS - -- ** Request constructor - , createDataSourceFromRDS - -- ** Request lenses + -- * Creating a Request + createDataSourceFromRDS + , CreateDataSourceFromRDS + -- * Request Lenses + , cdsfrdsDataSourceName , cdsfrdsComputeStatistics , cdsfrdsDataSourceId - , cdsfrdsDataSourceName , cdsfrdsRDSData , cdsfrdsRoleARN - -- * Response - , CreateDataSourceFromRDSResponse - -- ** Response constructor + -- * Destructuring the Response , createDataSourceFromRDSResponse - -- ** Response lenses - , cdsfrdsrDataSourceId + , CreateDataSourceFromRDSResponse + -- * Response Lenses + , cdsfrdsrsDataSourceId + , cdsfrdsrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data CreateDataSourceFromRDS = CreateDataSourceFromRDS - { _cdsfrdsComputeStatistics :: Maybe Bool - , _cdsfrdsDataSourceId :: Text - , _cdsfrdsDataSourceName :: Maybe Text - , _cdsfrdsRDSData :: RDSDataSpec - , _cdsfrdsRoleARN :: Text - } deriving (Eq, Read, Show) +-- | /See:/ 'createDataSourceFromRDS' smart constructor. +data CreateDataSourceFromRDS = CreateDataSourceFromRDS' + { _cdsfrdsDataSourceName :: !(Maybe Text) + , _cdsfrdsComputeStatistics :: !(Maybe Bool) + , _cdsfrdsDataSourceId :: !Text + , _cdsfrdsRDSData :: !RDSDataSpec + , _cdsfrdsRoleARN :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'CreateDataSourceFromRDS' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'CreateDataSourceFromRDS' with the minimum fields required to make a request. -- --- * 'cdsfrdsComputeStatistics' @::@ 'Maybe' 'Bool' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'cdsfrdsDataSourceId' @::@ 'Text' +-- * 'cdsfrdsDataSourceName' -- --- * 'cdsfrdsDataSourceName' @::@ 'Maybe' 'Text' +-- * 'cdsfrdsComputeStatistics' -- --- * 'cdsfrdsRDSData' @::@ 'RDSDataSpec' +-- * 'cdsfrdsDataSourceId' -- --- * 'cdsfrdsRoleARN' @::@ 'Text' +-- * 'cdsfrdsRDSData' -- -createDataSourceFromRDS :: Text -- ^ 'cdsfrdsDataSourceId' - -> RDSDataSpec -- ^ 'cdsfrdsRDSData' - -> Text -- ^ 'cdsfrdsRoleARN' - -> CreateDataSourceFromRDS -createDataSourceFromRDS p1 p2 p3 = CreateDataSourceFromRDS - { _cdsfrdsDataSourceId = p1 - , _cdsfrdsRDSData = p2 - , _cdsfrdsRoleARN = p3 - , _cdsfrdsDataSourceName = Nothing +-- * 'cdsfrdsRoleARN' +createDataSourceFromRDS + :: Text -- ^ 'cdsfrdsDataSourceId' + -> RDSDataSpec -- ^ 'cdsfrdsRDSData' + -> Text -- ^ 'cdsfrdsRoleARN' + -> CreateDataSourceFromRDS +createDataSourceFromRDS pDataSourceId_ pRDSData_ pRoleARN_ = + CreateDataSourceFromRDS' + { _cdsfrdsDataSourceName = Nothing , _cdsfrdsComputeStatistics = Nothing + , _cdsfrdsDataSourceId = pDataSourceId_ + , _cdsfrdsRDSData = pRDSData_ + , _cdsfrdsRoleARN = pRoleARN_ } --- | The compute statistics for a 'DataSource'. The statistics are generated from --- the observation data referenced by a 'DataSource'. Amazon ML uses the --- statistics internally during an 'MLModel' training. This parameter must be set --- to 'true' if the ''DataSource'' needs to be used for 'MLModel' training. +-- | A user-supplied name or description of the 'DataSource'. +cdsfrdsDataSourceName :: Lens' CreateDataSourceFromRDS (Maybe Text) +cdsfrdsDataSourceName = lens _cdsfrdsDataSourceName (\ s a -> s{_cdsfrdsDataSourceName = a}); + +-- | The compute statistics for a 'DataSource'. The statistics are generated +-- from the observation data referenced by a 'DataSource'. Amazon ML uses +-- the statistics internally during an 'MLModel' training. This parameter +-- must be set to 'true' if the ''DataSource'' needs to be used for +-- 'MLModel' training. cdsfrdsComputeStatistics :: Lens' CreateDataSourceFromRDS (Maybe Bool) -cdsfrdsComputeStatistics = - lens _cdsfrdsComputeStatistics - (\s a -> s { _cdsfrdsComputeStatistics = a }) +cdsfrdsComputeStatistics = lens _cdsfrdsComputeStatistics (\ s a -> s{_cdsfrdsComputeStatistics = a}); --- | A user-supplied ID that uniquely identifies the 'DataSource'. Typically, an --- Amazon Resource Number (ARN) becomes the ID for a 'DataSource'. +-- | A user-supplied ID that uniquely identifies the 'DataSource'. Typically, +-- an Amazon Resource Number (ARN) becomes the ID for a 'DataSource'. cdsfrdsDataSourceId :: Lens' CreateDataSourceFromRDS Text -cdsfrdsDataSourceId = - lens _cdsfrdsDataSourceId (\s a -> s { _cdsfrdsDataSourceId = a }) - --- | A user-supplied name or description of the 'DataSource'. -cdsfrdsDataSourceName :: Lens' CreateDataSourceFromRDS (Maybe Text) -cdsfrdsDataSourceName = - lens _cdsfrdsDataSourceName (\s a -> s { _cdsfrdsDataSourceName = a }) +cdsfrdsDataSourceId = lens _cdsfrdsDataSourceId (\ s a -> s{_cdsfrdsDataSourceId = a}); -- | The data specification of an Amazon RDS 'DataSource': -- --- DatabaseInformation - 'DatabaseName ' - Name of the Amazon RDS database. 'InstanceIdentifier ' - Unique identifier for the Amazon RDS database instance. --- --- --- DatabaseCredentials - AWS Identity and Access Management (IAM) credentials --- that are used to connect to the Amazon RDS database. --- --- ResourceRole - Role (DataPipelineDefaultResourceRole) assumed by an Amazon --- Elastic Compute Cloud (EC2) instance to carry out the copy task from Amazon --- RDS to Amazon S3. For more information, see for data pipelines. +-- - DatabaseInformation - -- --- ServiceRole - Role (DataPipelineDefaultRole) assumed by the AWS Data --- Pipeline service to monitor the progress of the copy task from Amazon RDS to --- Amazon Simple Storage Service (S3). For more information, see --- for data pipelines. +-- - 'DatabaseName ' - Name of the Amazon RDS database. +-- - ' InstanceIdentifier ' - Unique identifier for the Amazon RDS +-- database instance. +-- - DatabaseCredentials - AWS Identity and Access Management (IAM) +-- credentials that are used to connect to the Amazon RDS database. -- --- SecurityInfo - Security information to use to access an Amazon RDS instance. --- You need to set up appropriate ingress rules for the security entity IDs --- provided to allow access to the Amazon RDS instance. Specify a ['SubnetId', 'SecurityGroupIds'] pair for a VPC-based Amazon RDS instance. +-- - ResourceRole - Role (DataPipelineDefaultResourceRole) assumed by an +-- Amazon Elastic Compute Cloud (EC2) instance to carry out the copy +-- task from Amazon RDS to Amazon S3. For more information, see +-- +-- for data pipelines. -- --- SelectSqlQuery - Query that is used to retrieve the observation data for the 'Datasource'. +-- - ServiceRole - Role (DataPipelineDefaultRole) assumed by the AWS Data +-- Pipeline service to monitor the progress of the copy task from +-- Amazon RDS to Amazon Simple Storage Service (S3). For more +-- information, see +-- +-- for data pipelines. -- --- S3StagingLocation - Amazon S3 location for staging RDS data. The data --- retrieved from Amazon RDS using 'SelectSqlQuery' is stored in this location. +-- - SecurityInfo - Security information to use to access an Amazon RDS +-- instance. You need to set up appropriate ingress rules for the +-- security entity IDs provided to allow access to the Amazon RDS +-- instance. Specify a ['SubnetId', 'SecurityGroupIds'] pair for a +-- VPC-based Amazon RDS instance. -- --- DataSchemaUri - Amazon S3 location of the 'DataSchema'. +-- - SelectSqlQuery - Query that is used to retrieve the observation data +-- for the 'Datasource'. -- --- DataSchema - A JSON string representing the schema. This is not required if 'DataSchemaUri' is specified. +-- - S3StagingLocation - Amazon S3 location for staging RDS data. The +-- data retrieved from Amazon RDS using 'SelectSqlQuery' is stored in +-- this location. -- --- DataRearrangement - A JSON string representing the splitting requirement of --- a 'Datasource'. +-- - DataSchemaUri - Amazon S3 location of the 'DataSchema'. -- +-- - DataSchema - A JSON string representing the schema. This is not +-- required if 'DataSchemaUri' is specified. -- --- Sample - ' "{\"randomSeed\":\"some-random-seed\",\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"' +-- - DataRearrangement - A JSON string representing the splitting +-- requirement of a 'Datasource'. -- +-- Sample - +-- ' \"{\\\"randomSeed\\\":\\\"some-random-seed\\\", \\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"' -- cdsfrdsRDSData :: Lens' CreateDataSourceFromRDS RDSDataSpec -cdsfrdsRDSData = lens _cdsfrdsRDSData (\s a -> s { _cdsfrdsRDSData = a }) +cdsfrdsRDSData = lens _cdsfrdsRDSData (\ s a -> s{_cdsfrdsRDSData = a}); --- | The role that Amazon ML assumes on behalf of the user to create and activate --- a data pipeline in the user’s account and copy data (using the 'SelectSqlQuery') query from Amazon RDS to Amazon S3. --- --- +-- | The role that Amazon ML assumes on behalf of the user to create and +-- activate a data pipeline in the user’s account and copy data (using the +-- 'SelectSqlQuery') query from Amazon RDS to Amazon S3. -- cdsfrdsRoleARN :: Lens' CreateDataSourceFromRDS Text -cdsfrdsRoleARN = lens _cdsfrdsRoleARN (\s a -> s { _cdsfrdsRoleARN = a }) +cdsfrdsRoleARN = lens _cdsfrdsRoleARN (\ s a -> s{_cdsfrdsRoleARN = a}); -newtype CreateDataSourceFromRDSResponse = CreateDataSourceFromRDSResponse - { _cdsfrdsrDataSourceId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest CreateDataSourceFromRDS where + type Sv CreateDataSourceFromRDS = MachineLearning + type Rs CreateDataSourceFromRDS = + CreateDataSourceFromRDSResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + CreateDataSourceFromRDSResponse' <$> + (x .?> "DataSourceId") <*> (pure (fromEnum s))) --- | 'CreateDataSourceFromRDSResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'cdsfrdsrDataSourceId' @::@ 'Maybe' 'Text' --- -createDataSourceFromRDSResponse :: CreateDataSourceFromRDSResponse -createDataSourceFromRDSResponse = CreateDataSourceFromRDSResponse - { _cdsfrdsrDataSourceId = Nothing - } +instance ToHeaders CreateDataSourceFromRDS where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.CreateDataSourceFromRDS" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | A user-supplied ID that uniquely identifies the datasource. This value should --- be identical to the value of the 'DataSourceID' in the request. -cdsfrdsrDataSourceId :: Lens' CreateDataSourceFromRDSResponse (Maybe Text) -cdsfrdsrDataSourceId = - lens _cdsfrdsrDataSourceId (\s a -> s { _cdsfrdsrDataSourceId = a }) +instance ToJSON CreateDataSourceFromRDS where + toJSON CreateDataSourceFromRDS'{..} + = object + ["DataSourceName" .= _cdsfrdsDataSourceName, + "ComputeStatistics" .= _cdsfrdsComputeStatistics, + "DataSourceId" .= _cdsfrdsDataSourceId, + "RDSData" .= _cdsfrdsRDSData, + "RoleARN" .= _cdsfrdsRoleARN] instance ToPath CreateDataSourceFromRDS where - toPath = const "/" + toPath = const "/" instance ToQuery CreateDataSourceFromRDS where - toQuery = const mempty - -instance ToHeaders CreateDataSourceFromRDS + toQuery = const mempty -instance ToJSON CreateDataSourceFromRDS where - toJSON CreateDataSourceFromRDS{..} = object - [ "DataSourceId" .= _cdsfrdsDataSourceId - , "DataSourceName" .= _cdsfrdsDataSourceName - , "RDSData" .= _cdsfrdsRDSData - , "RoleARN" .= _cdsfrdsRoleARN - , "ComputeStatistics" .= _cdsfrdsComputeStatistics - ] +-- | Represents the output of a CreateDataSourceFromRDS operation, and is an +-- acknowledgement that Amazon ML received the request. +-- +-- The CreateDataSourceFromRDS operation is asynchronous. You can poll for +-- updates by using the GetBatchPrediction operation and checking the +-- 'Status' parameter. You can inspect the 'Message' when 'Status' shows up +-- as 'FAILED'. You can also check the progress of the copy operation by +-- going to the 'DataPipeline' console and looking up the pipeline using +-- the pipelineId from the describe call. +-- +-- /See:/ 'createDataSourceFromRDSResponse' smart constructor. +data CreateDataSourceFromRDSResponse = CreateDataSourceFromRDSResponse' + { _cdsfrdsrsDataSourceId :: !(Maybe Text) + , _cdsfrdsrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest CreateDataSourceFromRDS where - type Sv CreateDataSourceFromRDS = MachineLearning - type Rs CreateDataSourceFromRDS = CreateDataSourceFromRDSResponse +-- | Creates a value of 'CreateDataSourceFromRDSResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'cdsfrdsrsDataSourceId' +-- +-- * 'cdsfrdsrsStatus' +createDataSourceFromRDSResponse + :: Int -- ^ 'cdsfrdsrsStatus' + -> CreateDataSourceFromRDSResponse +createDataSourceFromRDSResponse pStatus_ = + CreateDataSourceFromRDSResponse' + { _cdsfrdsrsDataSourceId = Nothing + , _cdsfrdsrsStatus = pStatus_ + } - request = post "CreateDataSourceFromRDS" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the datasource. This value +-- should be identical to the value of the 'DataSourceID' in the request. +cdsfrdsrsDataSourceId :: Lens' CreateDataSourceFromRDSResponse (Maybe Text) +cdsfrdsrsDataSourceId = lens _cdsfrdsrsDataSourceId (\ s a -> s{_cdsfrdsrsDataSourceId = a}); -instance FromJSON CreateDataSourceFromRDSResponse where - parseJSON = withObject "CreateDataSourceFromRDSResponse" $ \o -> CreateDataSourceFromRDSResponse - <$> o .:? "DataSourceId" +-- | The response status code. +cdsfrdsrsStatus :: Lens' CreateDataSourceFromRDSResponse Int +cdsfrdsrsStatus = lens _cdsfrdsrsStatus (\ s a -> s{_cdsfrdsrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs b/gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs --- a/gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs +++ b/gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs @@ -1,214 +1,254 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.CreateDataSourceFromRedshift --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Creates a 'DataSource' from . A 'DataSource' references data that --- can be used to perform either 'CreateMLModel', 'CreateEvaluation' or 'CreateBatchPrediction' operations. +-- Creates a 'DataSource' from +-- . A 'DataSource' +-- references data that can be used to perform either CreateMLModel, +-- CreateEvaluation or CreateBatchPrediction operations. -- --- 'CreateDataSourceFromRedshift' is an asynchronous operation. In response to 'CreateDataSourceFromRedshift', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'DataSource' status to 'PENDING'. After the 'DataSource' is created and ready for use, Amazon --- ML sets the 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or 'PENDING' --- status can only be used to perform 'CreateMLModel', 'CreateEvaluation', or 'CreateBatchPrediction' operations. +-- 'CreateDataSourceFromRedshift' is an asynchronous operation. In response +-- to 'CreateDataSourceFromRedshift', Amazon Machine Learning (Amazon ML) +-- immediately returns and sets the 'DataSource' status to 'PENDING'. After +-- the 'DataSource' is created and ready for use, Amazon ML sets the +-- 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or +-- 'PENDING' status can only be used to perform CreateMLModel, +-- CreateEvaluation, or CreateBatchPrediction operations. -- --- If Amazon ML cannot accept the input source, it sets the 'Status' parameter --- to 'FAILED' and includes an error message in the 'Message' attribute of the 'GetDataSource' operation response. +-- If Amazon ML cannot accept the input source, it sets the 'Status' +-- parameter to 'FAILED' and includes an error message in the 'Message' +-- attribute of the GetDataSource operation response. -- --- The observations should exist in the database hosted on an Amazon Redshift --- cluster and should be specified by a 'SelectSqlQuery'. Amazon ML executes command in Amazon Redshift to transfer the result set of 'SelectSqlQuery' --- to 'S3StagingLocation.' +-- The observations should exist in the database hosted on an Amazon +-- Redshift cluster and should be specified by a 'SelectSqlQuery'. Amazon +-- ML executes +-- +-- command in Amazon Redshift to transfer the result set of +-- 'SelectSqlQuery' to 'S3StagingLocation.' -- --- After the 'DataSource' is created, it's ready for use in evaluations and batch --- predictions. If you plan to use the 'DataSource' to train an 'MLModel', the 'DataSource' requires another item -- a recipe. A recipe describes the observation --- variables that participate in training an 'MLModel'. A recipe describes how --- each input variable will be used in training. Will the variable be included --- or excluded from training? Will the variable be manipulated, for example, --- combined with another variable or split apart into word combinations? The --- recipe provides answers to these questions. For more information, see the --- Amazon Machine Learning Developer Guide. +-- After the 'DataSource' is created, it\'s ready for use in evaluations +-- and batch predictions. If you plan to use the 'DataSource' to train an +-- 'MLModel', the 'DataSource' requires another item -- a recipe. A recipe +-- describes the observation variables that participate in training an +-- 'MLModel'. A recipe describes how each input variable will be used in +-- training. Will the variable be included or excluded from training? Will +-- the variable be manipulated, for example, combined with another variable +-- or split apart into word combinations? The recipe provides answers to +-- these questions. For more information, see the Amazon Machine Learning +-- Developer Guide. -- --- +-- /See:/ for CreateDataSourceFromRedshift. module Network.AWS.MachineLearning.CreateDataSourceFromRedshift ( - -- * Request - CreateDataSourceFromRedshift - -- ** Request constructor - , createDataSourceFromRedshift - -- ** Request lenses + -- * Creating a Request + createDataSourceFromRedshift + , CreateDataSourceFromRedshift + -- * Request Lenses + , cdsfrDataSourceName , cdsfrComputeStatistics , cdsfrDataSourceId - , cdsfrDataSourceName , cdsfrDataSpec , cdsfrRoleARN - -- * Response - , CreateDataSourceFromRedshiftResponse - -- ** Response constructor + -- * Destructuring the Response , createDataSourceFromRedshiftResponse - -- ** Response lenses - , cdsfrrDataSourceId + , CreateDataSourceFromRedshiftResponse + -- * Response Lenses + , cdsfrrsDataSourceId + , cdsfrrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data CreateDataSourceFromRedshift = CreateDataSourceFromRedshift - { _cdsfrComputeStatistics :: Maybe Bool - , _cdsfrDataSourceId :: Text - , _cdsfrDataSourceName :: Maybe Text - , _cdsfrDataSpec :: RedshiftDataSpec - , _cdsfrRoleARN :: Text - } deriving (Eq, Read, Show) +-- | /See:/ 'createDataSourceFromRedshift' smart constructor. +data CreateDataSourceFromRedshift = CreateDataSourceFromRedshift' + { _cdsfrDataSourceName :: !(Maybe Text) + , _cdsfrComputeStatistics :: !(Maybe Bool) + , _cdsfrDataSourceId :: !Text + , _cdsfrDataSpec :: !RedshiftDataSpec + , _cdsfrRoleARN :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'CreateDataSourceFromRedshift' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'CreateDataSourceFromRedshift' with the minimum fields required to make a request. -- --- * 'cdsfrComputeStatistics' @::@ 'Maybe' 'Bool' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'cdsfrDataSourceId' @::@ 'Text' +-- * 'cdsfrDataSourceName' -- --- * 'cdsfrDataSourceName' @::@ 'Maybe' 'Text' +-- * 'cdsfrComputeStatistics' -- --- * 'cdsfrDataSpec' @::@ 'RedshiftDataSpec' +-- * 'cdsfrDataSourceId' -- --- * 'cdsfrRoleARN' @::@ 'Text' +-- * 'cdsfrDataSpec' -- -createDataSourceFromRedshift :: Text -- ^ 'cdsfrDataSourceId' - -> RedshiftDataSpec -- ^ 'cdsfrDataSpec' - -> Text -- ^ 'cdsfrRoleARN' - -> CreateDataSourceFromRedshift -createDataSourceFromRedshift p1 p2 p3 = CreateDataSourceFromRedshift - { _cdsfrDataSourceId = p1 - , _cdsfrDataSpec = p2 - , _cdsfrRoleARN = p3 - , _cdsfrDataSourceName = Nothing +-- * 'cdsfrRoleARN' +createDataSourceFromRedshift + :: Text -- ^ 'cdsfrDataSourceId' + -> RedshiftDataSpec -- ^ 'cdsfrDataSpec' + -> Text -- ^ 'cdsfrRoleARN' + -> CreateDataSourceFromRedshift +createDataSourceFromRedshift pDataSourceId_ pDataSpec_ pRoleARN_ = + CreateDataSourceFromRedshift' + { _cdsfrDataSourceName = Nothing , _cdsfrComputeStatistics = Nothing + , _cdsfrDataSourceId = pDataSourceId_ + , _cdsfrDataSpec = pDataSpec_ + , _cdsfrRoleARN = pRoleARN_ } --- | The compute statistics for a 'DataSource'. The statistics are generated from --- the observation data referenced by a 'DataSource'. Amazon ML uses the --- statistics internally during 'MLModel' training. This parameter must be set to 'true' if the ''DataSource'' needs to be used for 'MLModel' training +-- | A user-supplied name or description of the 'DataSource'. +cdsfrDataSourceName :: Lens' CreateDataSourceFromRedshift (Maybe Text) +cdsfrDataSourceName = lens _cdsfrDataSourceName (\ s a -> s{_cdsfrDataSourceName = a}); + +-- | The compute statistics for a 'DataSource'. The statistics are generated +-- from the observation data referenced by a 'DataSource'. Amazon ML uses +-- the statistics internally during 'MLModel' training. This parameter must +-- be set to 'true' if the ''DataSource'' needs to be used for 'MLModel' +-- training cdsfrComputeStatistics :: Lens' CreateDataSourceFromRedshift (Maybe Bool) -cdsfrComputeStatistics = - lens _cdsfrComputeStatistics (\s a -> s { _cdsfrComputeStatistics = a }) +cdsfrComputeStatistics = lens _cdsfrComputeStatistics (\ s a -> s{_cdsfrComputeStatistics = a}); -- | A user-supplied ID that uniquely identifies the 'DataSource'. cdsfrDataSourceId :: Lens' CreateDataSourceFromRedshift Text -cdsfrDataSourceId = - lens _cdsfrDataSourceId (\s a -> s { _cdsfrDataSourceId = a }) - --- | A user-supplied name or description of the 'DataSource'. -cdsfrDataSourceName :: Lens' CreateDataSourceFromRedshift (Maybe Text) -cdsfrDataSourceName = - lens _cdsfrDataSourceName (\s a -> s { _cdsfrDataSourceName = a }) +cdsfrDataSourceId = lens _cdsfrDataSourceId (\ s a -> s{_cdsfrDataSourceId = a}); -- | The data specification of an Amazon Redshift 'DataSource': -- --- DatabaseInformation - 'DatabaseName ' - Name of the Amazon Redshift --- database. ' ClusterIdentifier ' - Unique ID for the Amazon Redshift cluster. --- --- DatabaseCredentials - AWS Identity abd Access Management (IAM) credentials --- that are used to connect to the Amazon Redshift database. --- --- SelectSqlQuery - Query that is used to retrieve the observation data for the 'Datasource'. +-- - DatabaseInformation - -- --- S3StagingLocation - Amazon Simple Storage Service (Amazon S3) location for --- staging Amazon Redshift data. The data retrieved from Amazon Relational --- Database Service (Amazon RDS) using 'SelectSqlQuery' is stored in this location. +-- - 'DatabaseName ' - Name of the Amazon Redshift database. +-- - ' ClusterIdentifier ' - Unique ID for the Amazon Redshift +-- cluster. +-- - DatabaseCredentials - AWS Identity abd Access Management (IAM) +-- credentials that are used to connect to the Amazon Redshift +-- database. -- --- DataSchemaUri - Amazon S3 location of the 'DataSchema'. +-- - SelectSqlQuery - Query that is used to retrieve the observation data +-- for the 'Datasource'. -- --- DataSchema - A JSON string representing the schema. This is not required if 'DataSchemaUri' is specified. +-- - S3StagingLocation - Amazon Simple Storage Service (Amazon S3) +-- location for staging Amazon Redshift data. The data retrieved from +-- Amazon Relational Database Service (Amazon RDS) using +-- 'SelectSqlQuery' is stored in this location. -- --- DataRearrangement - A JSON string representing the splitting requirement of --- a 'Datasource'. +-- - DataSchemaUri - Amazon S3 location of the 'DataSchema'. -- +-- - DataSchema - A JSON string representing the schema. This is not +-- required if 'DataSchemaUri' is specified. -- --- Sample - ' "{\"randomSeed\":\"some-random-seed\",\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"' +-- - DataRearrangement - A JSON string representing the splitting +-- requirement of a 'Datasource'. -- +-- Sample - +-- ' \"{\\\"randomSeed\\\":\\\"some-random-seed\\\", \\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"' -- cdsfrDataSpec :: Lens' CreateDataSourceFromRedshift RedshiftDataSpec -cdsfrDataSpec = lens _cdsfrDataSpec (\s a -> s { _cdsfrDataSpec = a }) +cdsfrDataSpec = lens _cdsfrDataSpec (\ s a -> s{_cdsfrDataSpec = a}); --- | A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role --- on behalf of the user to create the following: --- --- A security group to allow Amazon ML to execute the 'SelectSqlQuery' query on --- an Amazon Redshift cluster +-- | A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the +-- role on behalf of the user to create the following: -- --- An Amazon S3 bucket policy to grant Amazon ML read/write permissions on the 'S3StagingLocation' +-- - A security group to allow Amazon ML to execute the 'SelectSqlQuery' +-- query on an Amazon Redshift cluster -- +-- - An Amazon S3 bucket policy to grant Amazon ML read\/write +-- permissions on the 'S3StagingLocation' -- cdsfrRoleARN :: Lens' CreateDataSourceFromRedshift Text -cdsfrRoleARN = lens _cdsfrRoleARN (\s a -> s { _cdsfrRoleARN = a }) +cdsfrRoleARN = lens _cdsfrRoleARN (\ s a -> s{_cdsfrRoleARN = a}); -newtype CreateDataSourceFromRedshiftResponse = CreateDataSourceFromRedshiftResponse - { _cdsfrrDataSourceId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest CreateDataSourceFromRedshift + where + type Sv CreateDataSourceFromRedshift = + MachineLearning + type Rs CreateDataSourceFromRedshift = + CreateDataSourceFromRedshiftResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + CreateDataSourceFromRedshiftResponse' <$> + (x .?> "DataSourceId") <*> (pure (fromEnum s))) --- | 'CreateDataSourceFromRedshiftResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'cdsfrrDataSourceId' @::@ 'Maybe' 'Text' --- -createDataSourceFromRedshiftResponse :: CreateDataSourceFromRedshiftResponse -createDataSourceFromRedshiftResponse = CreateDataSourceFromRedshiftResponse - { _cdsfrrDataSourceId = Nothing - } +instance ToHeaders CreateDataSourceFromRedshift where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.CreateDataSourceFromRedshift" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | A user-supplied ID that uniquely identifies the datasource. This value should --- be identical to the value of the 'DataSourceID' in the request. -cdsfrrDataSourceId :: Lens' CreateDataSourceFromRedshiftResponse (Maybe Text) -cdsfrrDataSourceId = - lens _cdsfrrDataSourceId (\s a -> s { _cdsfrrDataSourceId = a }) +instance ToJSON CreateDataSourceFromRedshift where + toJSON CreateDataSourceFromRedshift'{..} + = object + ["DataSourceName" .= _cdsfrDataSourceName, + "ComputeStatistics" .= _cdsfrComputeStatistics, + "DataSourceId" .= _cdsfrDataSourceId, + "DataSpec" .= _cdsfrDataSpec, + "RoleARN" .= _cdsfrRoleARN] instance ToPath CreateDataSourceFromRedshift where - toPath = const "/" + toPath = const "/" instance ToQuery CreateDataSourceFromRedshift where - toQuery = const mempty - -instance ToHeaders CreateDataSourceFromRedshift + toQuery = const mempty -instance ToJSON CreateDataSourceFromRedshift where - toJSON CreateDataSourceFromRedshift{..} = object - [ "DataSourceId" .= _cdsfrDataSourceId - , "DataSourceName" .= _cdsfrDataSourceName - , "DataSpec" .= _cdsfrDataSpec - , "RoleARN" .= _cdsfrRoleARN - , "ComputeStatistics" .= _cdsfrComputeStatistics - ] +-- | Represents the output of a CreateDataSourceFromRedshift operation, and +-- is an acknowledgement that Amazon ML received the request. +-- +-- The CreateDataSourceFromRedshift operation is asynchronous. You can poll +-- for updates by using the GetBatchPrediction operation and checking the +-- 'Status' parameter. +-- +-- /See:/ 'createDataSourceFromRedshiftResponse' smart constructor. +data CreateDataSourceFromRedshiftResponse = CreateDataSourceFromRedshiftResponse' + { _cdsfrrsDataSourceId :: !(Maybe Text) + , _cdsfrrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest CreateDataSourceFromRedshift where - type Sv CreateDataSourceFromRedshift = MachineLearning - type Rs CreateDataSourceFromRedshift = CreateDataSourceFromRedshiftResponse +-- | Creates a value of 'CreateDataSourceFromRedshiftResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'cdsfrrsDataSourceId' +-- +-- * 'cdsfrrsStatus' +createDataSourceFromRedshiftResponse + :: Int -- ^ 'cdsfrrsStatus' + -> CreateDataSourceFromRedshiftResponse +createDataSourceFromRedshiftResponse pStatus_ = + CreateDataSourceFromRedshiftResponse' + { _cdsfrrsDataSourceId = Nothing + , _cdsfrrsStatus = pStatus_ + } - request = post "CreateDataSourceFromRedshift" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the datasource. This value +-- should be identical to the value of the 'DataSourceID' in the request. +cdsfrrsDataSourceId :: Lens' CreateDataSourceFromRedshiftResponse (Maybe Text) +cdsfrrsDataSourceId = lens _cdsfrrsDataSourceId (\ s a -> s{_cdsfrrsDataSourceId = a}); -instance FromJSON CreateDataSourceFromRedshiftResponse where - parseJSON = withObject "CreateDataSourceFromRedshiftResponse" $ \o -> CreateDataSourceFromRedshiftResponse - <$> o .:? "DataSourceId" +-- | The response status code. +cdsfrrsStatus :: Lens' CreateDataSourceFromRedshiftResponse Int +cdsfrrsStatus = lens _cdsfrrsStatus (\ s a -> s{_cdsfrrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/CreateDataSourceFromS.hs b/gen/Network/AWS/MachineLearning/CreateDataSourceFromS.hs --- a/gen/Network/AWS/MachineLearning/CreateDataSourceFromS.hs +++ b/gen/Network/AWS/MachineLearning/CreateDataSourceFromS.hs @@ -1,190 +1,219 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.CreateDataSourceFromS --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Creates a 'DataSource' object. A 'DataSource' references data that can be used to --- perform 'CreateMLModel', 'CreateEvaluation', or 'CreateBatchPrediction' operations. +-- Creates a 'DataSource' object. A 'DataSource' references data that can +-- be used to perform CreateMLModel, CreateEvaluation, or +-- CreateBatchPrediction operations. -- --- 'CreateDataSourceFromS3' is an asynchronous operation. In response to 'CreateDataSourceFromS3', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'DataSource' status to 'PENDING'. After the 'DataSource' is created and ready for use, Amazon --- ML sets the 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or 'PENDING' --- status can only be used to perform 'CreateMLModel', 'CreateEvaluation' or 'CreateBatchPrediction' operations. +-- 'CreateDataSourceFromS3' is an asynchronous operation. In response to +-- 'CreateDataSourceFromS3', Amazon Machine Learning (Amazon ML) +-- immediately returns and sets the 'DataSource' status to 'PENDING'. After +-- the 'DataSource' is created and ready for use, Amazon ML sets the +-- 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or +-- 'PENDING' status can only be used to perform CreateMLModel, +-- CreateEvaluation or CreateBatchPrediction operations. -- --- If Amazon ML cannot accept the input source, it sets the 'Status' parameter --- to 'FAILED' and includes an error message in the 'Message' attribute of the 'GetDataSource' operation response. +-- If Amazon ML cannot accept the input source, it sets the 'Status' +-- parameter to 'FAILED' and includes an error message in the 'Message' +-- attribute of the GetDataSource operation response. -- --- The observation data used in a 'DataSource' should be ready to use; that is, --- it should have a consistent structure, and missing data values should be kept --- to a minimum. The observation data must reside in one or more CSV files in an --- Amazon Simple Storage Service (Amazon S3) bucket, along with a schema that --- describes the data items by name and type. The same schema must be used for --- all of the data files referenced by the 'DataSource'. +-- The observation data used in a 'DataSource' should be ready to use; that +-- is, it should have a consistent structure, and missing data values +-- should be kept to a minimum. The observation data must reside in one or +-- more CSV files in an Amazon Simple Storage Service (Amazon S3) bucket, +-- along with a schema that describes the data items by name and type. The +-- same schema must be used for all of the data files referenced by the +-- 'DataSource'. -- --- After the 'DataSource' has been created, it's ready to use in evaluations and --- batch predictions. If you plan to use the 'DataSource' to train an 'MLModel', the 'DataSource' requires another item: a recipe. A recipe describes the --- observation variables that participate in training an 'MLModel'. A recipe --- describes how each input variable will be used in training. Will the variable --- be included or excluded from training? Will the variable be manipulated, for --- example, combined with another variable, or split apart into word --- combinations? The recipe provides answers to these questions. For more --- information, see the . +-- After the 'DataSource' has been created, it\'s ready to use in +-- evaluations and batch predictions. If you plan to use the 'DataSource' +-- to train an 'MLModel', the 'DataSource' requires another item: a recipe. +-- A recipe describes the observation variables that participate in +-- training an 'MLModel'. A recipe describes how each input variable will +-- be used in training. Will the variable be included or excluded from +-- training? Will the variable be manipulated, for example, combined with +-- another variable, or split apart into word combinations? The recipe +-- provides answers to these questions. For more information, see the +-- . -- --- +-- /See:/ for CreateDataSourceFromS. module Network.AWS.MachineLearning.CreateDataSourceFromS ( - -- * Request - CreateDataSourceFromS3 - -- ** Request constructor - , createDataSourceFromS3 - -- ** Request lenses + -- * Creating a Request + createDataSourceFromS + , CreateDataSourceFromS + -- * Request Lenses + , cdsfsDataSourceName , cdsfsComputeStatistics , cdsfsDataSourceId - , cdsfsDataSourceName , cdsfsDataSpec - -- * Response - , CreateDataSourceFromS3Response - -- ** Response constructor - , createDataSourceFromS3Response - -- ** Response lenses - , cdsfsrDataSourceId + -- * Destructuring the Response + , createDataSourceFromSResponse + , CreateDataSourceFromSResponse + -- * Response Lenses + , cdsfsrsDataSourceId + , cdsfsrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data CreateDataSourceFromS3 = CreateDataSourceFromS3 - { _cdsfsComputeStatistics :: Maybe Bool - , _cdsfsDataSourceId :: Text - , _cdsfsDataSourceName :: Maybe Text - , _cdsfsDataSpec :: S3DataSpec - } deriving (Eq, Read, Show) +-- | /See:/ 'createDataSourceFromS' smart constructor. +data CreateDataSourceFromS = CreateDataSourceFromS' + { _cdsfsDataSourceName :: !(Maybe Text) + , _cdsfsComputeStatistics :: !(Maybe Bool) + , _cdsfsDataSourceId :: !Text + , _cdsfsDataSpec :: !S3DataSpec + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'CreateDataSourceFromS3' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'CreateDataSourceFromS' with the minimum fields required to make a request. -- --- * 'cdsfsComputeStatistics' @::@ 'Maybe' 'Bool' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'cdsfsDataSourceId' @::@ 'Text' +-- * 'cdsfsDataSourceName' -- --- * 'cdsfsDataSourceName' @::@ 'Maybe' 'Text' +-- * 'cdsfsComputeStatistics' -- --- * 'cdsfsDataSpec' @::@ 'S3DataSpec' +-- * 'cdsfsDataSourceId' -- -createDataSourceFromS3 :: Text -- ^ 'cdsfsDataSourceId' - -> S3DataSpec -- ^ 'cdsfsDataSpec' - -> CreateDataSourceFromS3 -createDataSourceFromS3 p1 p2 = CreateDataSourceFromS3 - { _cdsfsDataSourceId = p1 - , _cdsfsDataSpec = p2 - , _cdsfsDataSourceName = Nothing +-- * 'cdsfsDataSpec' +createDataSourceFromS + :: Text -- ^ 'cdsfsDataSourceId' + -> S3DataSpec -- ^ 'cdsfsDataSpec' + -> CreateDataSourceFromS +createDataSourceFromS pDataSourceId_ pDataSpec_ = + CreateDataSourceFromS' + { _cdsfsDataSourceName = Nothing , _cdsfsComputeStatistics = Nothing + , _cdsfsDataSourceId = pDataSourceId_ + , _cdsfsDataSpec = pDataSpec_ } --- | The compute statistics for a 'DataSource'. The statistics are generated from --- the observation data referenced by a 'DataSource'. Amazon ML uses the --- statistics internally during an 'MLModel' training. This parameter must be set --- to 'true' if the ''DataSource'' needs to be used for 'MLModel' training -cdsfsComputeStatistics :: Lens' CreateDataSourceFromS3 (Maybe Bool) -cdsfsComputeStatistics = - lens _cdsfsComputeStatistics (\s a -> s { _cdsfsComputeStatistics = a }) +-- | A user-supplied name or description of the 'DataSource'. +cdsfsDataSourceName :: Lens' CreateDataSourceFromS (Maybe Text) +cdsfsDataSourceName = lens _cdsfsDataSourceName (\ s a -> s{_cdsfsDataSourceName = a}); --- | A user-supplied identifier that uniquely identifies the 'DataSource'. -cdsfsDataSourceId :: Lens' CreateDataSourceFromS3 Text -cdsfsDataSourceId = - lens _cdsfsDataSourceId (\s a -> s { _cdsfsDataSourceId = a }) +-- | The compute statistics for a 'DataSource'. The statistics are generated +-- from the observation data referenced by a 'DataSource'. Amazon ML uses +-- the statistics internally during an 'MLModel' training. This parameter +-- must be set to 'true' if the ''DataSource'' needs to be used for +-- 'MLModel' training +cdsfsComputeStatistics :: Lens' CreateDataSourceFromS (Maybe Bool) +cdsfsComputeStatistics = lens _cdsfsComputeStatistics (\ s a -> s{_cdsfsComputeStatistics = a}); --- | A user-supplied name or description of the 'DataSource'. -cdsfsDataSourceName :: Lens' CreateDataSourceFromS3 (Maybe Text) -cdsfsDataSourceName = - lens _cdsfsDataSourceName (\s a -> s { _cdsfsDataSourceName = a }) +-- | A user-supplied identifier that uniquely identifies the 'DataSource'. +cdsfsDataSourceId :: Lens' CreateDataSourceFromS Text +cdsfsDataSourceId = lens _cdsfsDataSourceId (\ s a -> s{_cdsfsDataSourceId = a}); -- | The data specification of a 'DataSource': -- --- DataLocationS3 - Amazon Simple Storage Service (Amazon S3) location of the --- observation data. --- --- DataSchemaLocationS3 - Amazon S3 location of the 'DataSchema'. --- --- DataSchema - A JSON string representing the schema. This is not required if 'DataSchemaUri' is specified. +-- - DataLocationS3 - Amazon Simple Storage Service (Amazon S3) location +-- of the observation data. -- --- DataRearrangement - A JSON string representing the splitting requirement of --- a 'Datasource'. +-- - DataSchemaLocationS3 - Amazon S3 location of the 'DataSchema'. -- +-- - DataSchema - A JSON string representing the schema. This is not +-- required if 'DataSchemaUri' is specified. -- --- Sample - ' "{\"randomSeed\":\"some-random-seed\",\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"' +-- - DataRearrangement - A JSON string representing the splitting +-- requirement of a 'Datasource'. -- +-- Sample - +-- ' \"{\\\"randomSeed\\\":\\\"some-random-seed\\\", \\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"' -- -cdsfsDataSpec :: Lens' CreateDataSourceFromS3 S3DataSpec -cdsfsDataSpec = lens _cdsfsDataSpec (\s a -> s { _cdsfsDataSpec = a }) - -newtype CreateDataSourceFromS3Response = CreateDataSourceFromS3Response - { _cdsfsrDataSourceId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +cdsfsDataSpec :: Lens' CreateDataSourceFromS S3DataSpec +cdsfsDataSpec = lens _cdsfsDataSpec (\ s a -> s{_cdsfsDataSpec = a}); --- | 'CreateDataSourceFromS3Response' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'cdsfsrDataSourceId' @::@ 'Maybe' 'Text' --- -createDataSourceFromS3Response :: CreateDataSourceFromS3Response -createDataSourceFromS3Response = CreateDataSourceFromS3Response - { _cdsfsrDataSourceId = Nothing - } +instance AWSRequest CreateDataSourceFromS where + type Sv CreateDataSourceFromS = MachineLearning + type Rs CreateDataSourceFromS = + CreateDataSourceFromSResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + CreateDataSourceFromSResponse' <$> + (x .?> "DataSourceId") <*> (pure (fromEnum s))) --- | A user-supplied ID that uniquely identifies the datasource. This value should --- be identical to the value of the 'DataSourceID' in the request. -cdsfsrDataSourceId :: Lens' CreateDataSourceFromS3Response (Maybe Text) -cdsfsrDataSourceId = - lens _cdsfsrDataSourceId (\s a -> s { _cdsfsrDataSourceId = a }) +instance ToHeaders CreateDataSourceFromS where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.CreateDataSourceFromS" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) -instance ToPath CreateDataSourceFromS3 where - toPath = const "/" +instance ToJSON CreateDataSourceFromS where + toJSON CreateDataSourceFromS'{..} + = object + ["DataSourceName" .= _cdsfsDataSourceName, + "ComputeStatistics" .= _cdsfsComputeStatistics, + "DataSourceId" .= _cdsfsDataSourceId, + "DataSpec" .= _cdsfsDataSpec] -instance ToQuery CreateDataSourceFromS3 where - toQuery = const mempty +instance ToPath CreateDataSourceFromS where + toPath = const "/" -instance ToHeaders CreateDataSourceFromS3 +instance ToQuery CreateDataSourceFromS where + toQuery = const mempty -instance ToJSON CreateDataSourceFromS3 where - toJSON CreateDataSourceFromS3{..} = object - [ "DataSourceId" .= _cdsfsDataSourceId - , "DataSourceName" .= _cdsfsDataSourceName - , "DataSpec" .= _cdsfsDataSpec - , "ComputeStatistics" .= _cdsfsComputeStatistics - ] +-- | Represents the output of a CreateDataSourceFromS3 operation, and is an +-- acknowledgement that Amazon ML received the request. +-- +-- The CreateDataSourceFromS3 operation is asynchronous. You can poll for +-- updates by using the GetBatchPrediction operation and checking the +-- 'Status' parameter. +-- +-- /See:/ 'createDataSourceFromSResponse' smart constructor. +data CreateDataSourceFromSResponse = CreateDataSourceFromSResponse' + { _cdsfsrsDataSourceId :: !(Maybe Text) + , _cdsfsrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest CreateDataSourceFromS3 where - type Sv CreateDataSourceFromS3 = MachineLearning - type Rs CreateDataSourceFromS3 = CreateDataSourceFromS3Response +-- | Creates a value of 'CreateDataSourceFromSResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'cdsfsrsDataSourceId' +-- +-- * 'cdsfsrsStatus' +createDataSourceFromSResponse + :: Int -- ^ 'cdsfsrsStatus' + -> CreateDataSourceFromSResponse +createDataSourceFromSResponse pStatus_ = + CreateDataSourceFromSResponse' + { _cdsfsrsDataSourceId = Nothing + , _cdsfsrsStatus = pStatus_ + } - request = post "CreateDataSourceFromS3" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the datasource. This value +-- should be identical to the value of the 'DataSourceID' in the request. +cdsfsrsDataSourceId :: Lens' CreateDataSourceFromSResponse (Maybe Text) +cdsfsrsDataSourceId = lens _cdsfsrsDataSourceId (\ s a -> s{_cdsfsrsDataSourceId = a}); -instance FromJSON CreateDataSourceFromS3Response where - parseJSON = withObject "CreateDataSourceFromS3Response" $ \o -> CreateDataSourceFromS3Response - <$> o .:? "DataSourceId" +-- | The response status code. +cdsfsrsStatus :: Lens' CreateDataSourceFromSResponse Int +cdsfsrsStatus = lens _cdsfsrsStatus (\ s a -> s{_cdsfsrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/CreateEvaluation.hs b/gen/Network/AWS/MachineLearning/CreateEvaluation.hs --- a/gen/Network/AWS/MachineLearning/CreateEvaluation.hs +++ b/gen/Network/AWS/MachineLearning/CreateEvaluation.hs @@ -1,163 +1,189 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.CreateEvaluation --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Creates a new 'Evaluation' of an 'MLModel'. An 'MLModel' is evaluated on a set of --- observations associated to a 'DataSource'. Like a 'DataSource' for an 'MLModel', --- the 'DataSource' for an 'Evaluation' contains values for the Target Variable. The 'Evaluation' compares the predicted result for each observation to the actual --- outcome and provides a summary so that you know how effective the 'MLModel' --- functions on the test data. Evaluation generates a relevant performance --- metric such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the --- corresponding 'MLModelType': 'BINARY', 'REGRESSION' or 'MULTICLASS'. +-- Creates a new 'Evaluation' of an 'MLModel'. An 'MLModel' is evaluated on +-- a set of observations associated to a 'DataSource'. Like a 'DataSource' +-- for an 'MLModel', the 'DataSource' for an 'Evaluation' contains values +-- for the Target Variable. The 'Evaluation' compares the predicted result +-- for each observation to the actual outcome and provides a summary so +-- that you know how effective the 'MLModel' functions on the test data. +-- Evaluation generates a relevant performance metric such as BinaryAUC, +-- RegressionRMSE or MulticlassAvgFScore based on the corresponding +-- 'MLModelType': 'BINARY', 'REGRESSION' or 'MULTICLASS'. -- --- 'CreateEvaluation' is an asynchronous operation. In response to 'CreateEvaluation', Amazon Machine Learning (Amazon ML) immediately returns and sets the --- evaluation status to 'PENDING'. After the 'Evaluation' is created and ready for --- use, Amazon ML sets the status to 'COMPLETED'. +-- 'CreateEvaluation' is an asynchronous operation. In response to +-- 'CreateEvaluation', Amazon Machine Learning (Amazon ML) immediately +-- returns and sets the evaluation status to 'PENDING'. After the +-- 'Evaluation' is created and ready for use, Amazon ML sets the status to +-- 'COMPLETED'. -- --- You can use the 'GetEvaluation' operation to check progress of the evaluation --- during the creation operation. +-- You can use the GetEvaluation operation to check progress of the +-- evaluation during the creation operation. -- --- +-- /See:/ for CreateEvaluation. module Network.AWS.MachineLearning.CreateEvaluation ( - -- * Request - CreateEvaluation - -- ** Request constructor - , createEvaluation - -- ** Request lenses - , ceEvaluationDataSourceId - , ceEvaluationId + -- * Creating a Request + createEvaluation + , CreateEvaluation + -- * Request Lenses , ceEvaluationName + , ceEvaluationId , ceMLModelId + , ceEvaluationDataSourceId - -- * Response - , CreateEvaluationResponse - -- ** Response constructor + -- * Destructuring the Response , createEvaluationResponse - -- ** Response lenses - , cerEvaluationId + , CreateEvaluationResponse + -- * Response Lenses + , cersEvaluationId + , cersStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data CreateEvaluation = CreateEvaluation - { _ceEvaluationDataSourceId :: Text - , _ceEvaluationId :: Text - , _ceEvaluationName :: Maybe Text - , _ceMLModelId :: Text - } deriving (Eq, Ord, Read, Show) +-- | /See:/ 'createEvaluation' smart constructor. +data CreateEvaluation = CreateEvaluation' + { _ceEvaluationName :: !(Maybe Text) + , _ceEvaluationId :: !Text + , _ceMLModelId :: !Text + , _ceEvaluationDataSourceId :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'CreateEvaluation' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'CreateEvaluation' with the minimum fields required to make a request. -- --- * 'ceEvaluationDataSourceId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'ceEvaluationId' @::@ 'Text' +-- * 'ceEvaluationName' -- --- * 'ceEvaluationName' @::@ 'Maybe' 'Text' +-- * 'ceEvaluationId' -- --- * 'ceMLModelId' @::@ 'Text' +-- * 'ceMLModelId' -- -createEvaluation :: Text -- ^ 'ceEvaluationId' - -> Text -- ^ 'ceMLModelId' - -> Text -- ^ 'ceEvaluationDataSourceId' - -> CreateEvaluation -createEvaluation p1 p2 p3 = CreateEvaluation - { _ceEvaluationId = p1 - , _ceMLModelId = p2 - , _ceEvaluationDataSourceId = p3 - , _ceEvaluationName = Nothing +-- * 'ceEvaluationDataSourceId' +createEvaluation + :: Text -- ^ 'ceEvaluationId' + -> Text -- ^ 'ceMLModelId' + -> Text -- ^ 'ceEvaluationDataSourceId' + -> CreateEvaluation +createEvaluation pEvaluationId_ pMLModelId_ pEvaluationDataSourceId_ = + CreateEvaluation' + { _ceEvaluationName = Nothing + , _ceEvaluationId = pEvaluationId_ + , _ceMLModelId = pMLModelId_ + , _ceEvaluationDataSourceId = pEvaluationDataSourceId_ } --- | The ID of the 'DataSource' for the evaluation. The schema of the 'DataSource' --- must match the schema used to create the 'MLModel'. -ceEvaluationDataSourceId :: Lens' CreateEvaluation Text -ceEvaluationDataSourceId = - lens _ceEvaluationDataSourceId - (\s a -> s { _ceEvaluationDataSourceId = a }) +-- | A user-supplied name or description of the 'Evaluation'. +ceEvaluationName :: Lens' CreateEvaluation (Maybe Text) +ceEvaluationName = lens _ceEvaluationName (\ s a -> s{_ceEvaluationName = a}); -- | A user-supplied ID that uniquely identifies the 'Evaluation'. ceEvaluationId :: Lens' CreateEvaluation Text -ceEvaluationId = lens _ceEvaluationId (\s a -> s { _ceEvaluationId = a }) - --- | A user-supplied name or description of the 'Evaluation'. -ceEvaluationName :: Lens' CreateEvaluation (Maybe Text) -ceEvaluationName = lens _ceEvaluationName (\s a -> s { _ceEvaluationName = a }) +ceEvaluationId = lens _ceEvaluationId (\ s a -> s{_ceEvaluationId = a}); -- | The ID of the 'MLModel' to evaluate. -- --- The schema used in creating the 'MLModel' must match the schema of the 'DataSource' used in the 'Evaluation'. +-- The schema used in creating the 'MLModel' must match the schema of the +-- 'DataSource' used in the 'Evaluation'. ceMLModelId :: Lens' CreateEvaluation Text -ceMLModelId = lens _ceMLModelId (\s a -> s { _ceMLModelId = a }) +ceMLModelId = lens _ceMLModelId (\ s a -> s{_ceMLModelId = a}); -newtype CreateEvaluationResponse = CreateEvaluationResponse - { _cerEvaluationId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +-- | The ID of the 'DataSource' for the evaluation. The schema of the +-- 'DataSource' must match the schema used to create the 'MLModel'. +ceEvaluationDataSourceId :: Lens' CreateEvaluation Text +ceEvaluationDataSourceId = lens _ceEvaluationDataSourceId (\ s a -> s{_ceEvaluationDataSourceId = a}); --- | 'CreateEvaluationResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'cerEvaluationId' @::@ 'Maybe' 'Text' --- -createEvaluationResponse :: CreateEvaluationResponse -createEvaluationResponse = CreateEvaluationResponse - { _cerEvaluationId = Nothing - } +instance AWSRequest CreateEvaluation where + type Sv CreateEvaluation = MachineLearning + type Rs CreateEvaluation = CreateEvaluationResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + CreateEvaluationResponse' <$> + (x .?> "EvaluationId") <*> (pure (fromEnum s))) --- | The user-supplied ID that uniquely identifies the 'Evaluation'. This value --- should be identical to the value of the 'EvaluationId' in the request. -cerEvaluationId :: Lens' CreateEvaluationResponse (Maybe Text) -cerEvaluationId = lens _cerEvaluationId (\s a -> s { _cerEvaluationId = a }) +instance ToHeaders CreateEvaluation where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.CreateEvaluation" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) +instance ToJSON CreateEvaluation where + toJSON CreateEvaluation'{..} + = object + ["EvaluationName" .= _ceEvaluationName, + "EvaluationId" .= _ceEvaluationId, + "MLModelId" .= _ceMLModelId, + "EvaluationDataSourceId" .= + _ceEvaluationDataSourceId] + instance ToPath CreateEvaluation where - toPath = const "/" + toPath = const "/" instance ToQuery CreateEvaluation where - toQuery = const mempty - -instance ToHeaders CreateEvaluation + toQuery = const mempty -instance ToJSON CreateEvaluation where - toJSON CreateEvaluation{..} = object - [ "EvaluationId" .= _ceEvaluationId - , "EvaluationName" .= _ceEvaluationName - , "MLModelId" .= _ceMLModelId - , "EvaluationDataSourceId" .= _ceEvaluationDataSourceId - ] +-- | Represents the output of a CreateEvaluation operation, and is an +-- acknowledgement that Amazon ML received the request. +-- +-- CreateEvaluation operation is asynchronous. You can poll for status +-- updates by using the GetEvaluation operation and checking the 'Status' +-- parameter. +-- +-- /See:/ 'createEvaluationResponse' smart constructor. +data CreateEvaluationResponse = CreateEvaluationResponse' + { _cersEvaluationId :: !(Maybe Text) + , _cersStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest CreateEvaluation where - type Sv CreateEvaluation = MachineLearning - type Rs CreateEvaluation = CreateEvaluationResponse +-- | Creates a value of 'CreateEvaluationResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'cersEvaluationId' +-- +-- * 'cersStatus' +createEvaluationResponse + :: Int -- ^ 'cersStatus' + -> CreateEvaluationResponse +createEvaluationResponse pStatus_ = + CreateEvaluationResponse' + { _cersEvaluationId = Nothing + , _cersStatus = pStatus_ + } - request = post "CreateEvaluation" - response = jsonResponse +-- | The user-supplied ID that uniquely identifies the 'Evaluation'. This +-- value should be identical to the value of the 'EvaluationId' in the +-- request. +cersEvaluationId :: Lens' CreateEvaluationResponse (Maybe Text) +cersEvaluationId = lens _cersEvaluationId (\ s a -> s{_cersEvaluationId = a}); -instance FromJSON CreateEvaluationResponse where - parseJSON = withObject "CreateEvaluationResponse" $ \o -> CreateEvaluationResponse - <$> o .:? "EvaluationId" +-- | The response status code. +cersStatus :: Lens' CreateEvaluationResponse Int +cersStatus = lens _cersStatus (\ s a -> s{_cersStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/CreateMLModel.hs b/gen/Network/AWS/MachineLearning/CreateMLModel.hs --- a/gen/Network/AWS/MachineLearning/CreateMLModel.hs +++ b/gen/Network/AWS/MachineLearning/CreateMLModel.hs @@ -1,235 +1,264 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.CreateMLModel --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Creates a new 'MLModel' using the data files and the recipe as information --- sources. +-- Creates a new 'MLModel' using the data files and the recipe as +-- information sources. -- --- An 'MLModel' is nearly immutable. Users can only update the 'MLModelName' and --- the 'ScoreThreshold' in an 'MLModel' without creating a new 'MLModel'. +-- An 'MLModel' is nearly immutable. Users can only update the +-- 'MLModelName' and the 'ScoreThreshold' in an 'MLModel' without creating +-- a new 'MLModel'. -- --- 'CreateMLModel' is an asynchronous operation. In response to 'CreateMLModel', --- Amazon Machine Learning (Amazon ML) immediately returns and sets the 'MLModel' --- status to 'PENDING'. After the 'MLModel' is created and ready for use, Amazon ML --- sets the status to 'COMPLETED'. +-- 'CreateMLModel' is an asynchronous operation. In response to +-- 'CreateMLModel', Amazon Machine Learning (Amazon ML) immediately returns +-- and sets the 'MLModel' status to 'PENDING'. After the 'MLModel' is +-- created and ready for use, Amazon ML sets the status to 'COMPLETED'. -- --- You can use the 'GetMLModel' operation to check progress of the 'MLModel' during --- the creation operation. +-- You can use the GetMLModel operation to check progress of the 'MLModel' +-- during the creation operation. -- --- 'CreateMLModel' requires a 'DataSource' with computed statistics, which can be --- created by setting 'ComputeStatistics' to 'true' in 'CreateDataSourceFromRDS', 'CreateDataSourceFromS3', or 'CreateDataSourceFromRedshift' operations. +-- CreateMLModel requires a 'DataSource' with computed statistics, which +-- can be created by setting 'ComputeStatistics' to 'true' in +-- CreateDataSourceFromRDS, CreateDataSourceFromS3, or +-- CreateDataSourceFromRedshift operations. -- --- +-- /See:/ for CreateMLModel. module Network.AWS.MachineLearning.CreateMLModel ( - -- * Request - CreateMLModel - -- ** Request constructor - , createMLModel - -- ** Request lenses - , cmlmMLModelId + -- * Creating a Request + createMLModel + , CreateMLModel + -- * Request Lenses + , cmlmRecipe + , cmlmRecipeURI , cmlmMLModelName - , cmlmMLModelType , cmlmParameters - , cmlmRecipe - , cmlmRecipeUri + , cmlmMLModelId + , cmlmMLModelType , cmlmTrainingDataSourceId - -- * Response - , CreateMLModelResponse - -- ** Response constructor + -- * Destructuring the Response , createMLModelResponse - -- ** Response lenses - , cmlmrMLModelId + , CreateMLModelResponse + -- * Response Lenses + , cmlmrsMLModelId + , cmlmrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data CreateMLModel = CreateMLModel - { _cmlmMLModelId :: Text - , _cmlmMLModelName :: Maybe Text - , _cmlmMLModelType :: MLModelType - , _cmlmParameters :: Map Text Text - , _cmlmRecipe :: Maybe Text - , _cmlmRecipeUri :: Maybe Text - , _cmlmTrainingDataSourceId :: Text - } deriving (Eq, Read, Show) +-- | /See:/ 'createMLModel' smart constructor. +data CreateMLModel = CreateMLModel' + { _cmlmRecipe :: !(Maybe Text) + , _cmlmRecipeURI :: !(Maybe Text) + , _cmlmMLModelName :: !(Maybe Text) + , _cmlmParameters :: !(Maybe (Map Text Text)) + , _cmlmMLModelId :: !Text + , _cmlmMLModelType :: !MLModelType + , _cmlmTrainingDataSourceId :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'CreateMLModel' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'CreateMLModel' with the minimum fields required to make a request. -- --- * 'cmlmMLModelId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'cmlmMLModelName' @::@ 'Maybe' 'Text' +-- * 'cmlmRecipe' -- --- * 'cmlmMLModelType' @::@ 'MLModelType' +-- * 'cmlmRecipeURI' -- --- * 'cmlmParameters' @::@ 'HashMap' 'Text' 'Text' +-- * 'cmlmMLModelName' -- --- * 'cmlmRecipe' @::@ 'Maybe' 'Text' +-- * 'cmlmParameters' -- --- * 'cmlmRecipeUri' @::@ 'Maybe' 'Text' +-- * 'cmlmMLModelId' -- --- * 'cmlmTrainingDataSourceId' @::@ 'Text' +-- * 'cmlmMLModelType' -- -createMLModel :: Text -- ^ 'cmlmMLModelId' - -> MLModelType -- ^ 'cmlmMLModelType' - -> Text -- ^ 'cmlmTrainingDataSourceId' - -> CreateMLModel -createMLModel p1 p2 p3 = CreateMLModel - { _cmlmMLModelId = p1 - , _cmlmMLModelType = p2 - , _cmlmTrainingDataSourceId = p3 - , _cmlmMLModelName = Nothing - , _cmlmParameters = mempty - , _cmlmRecipe = Nothing - , _cmlmRecipeUri = Nothing +-- * 'cmlmTrainingDataSourceId' +createMLModel + :: Text -- ^ 'cmlmMLModelId' + -> MLModelType -- ^ 'cmlmMLModelType' + -> Text -- ^ 'cmlmTrainingDataSourceId' + -> CreateMLModel +createMLModel pMLModelId_ pMLModelType_ pTrainingDataSourceId_ = + CreateMLModel' + { _cmlmRecipe = Nothing + , _cmlmRecipeURI = Nothing + , _cmlmMLModelName = Nothing + , _cmlmParameters = Nothing + , _cmlmMLModelId = pMLModelId_ + , _cmlmMLModelType = pMLModelType_ + , _cmlmTrainingDataSourceId = pTrainingDataSourceId_ } --- | A user-supplied ID that uniquely identifies the 'MLModel'. -cmlmMLModelId :: Lens' CreateMLModel Text -cmlmMLModelId = lens _cmlmMLModelId (\s a -> s { _cmlmMLModelId = a }) +-- | The data recipe for creating 'MLModel'. You must specify either the +-- recipe or its URI. If you don’t specify a recipe or its URI, Amazon ML +-- creates a default. +cmlmRecipe :: Lens' CreateMLModel (Maybe Text) +cmlmRecipe = lens _cmlmRecipe (\ s a -> s{_cmlmRecipe = a}); +-- | The Amazon Simple Storage Service (Amazon S3) location and file name +-- that contains the 'MLModel' recipe. You must specify either the recipe +-- or its URI. If you don’t specify a recipe or its URI, Amazon ML creates +-- a default. +cmlmRecipeURI :: Lens' CreateMLModel (Maybe Text) +cmlmRecipeURI = lens _cmlmRecipeURI (\ s a -> s{_cmlmRecipeURI = a}); + -- | A user-supplied name or description of the 'MLModel'. cmlmMLModelName :: Lens' CreateMLModel (Maybe Text) -cmlmMLModelName = lens _cmlmMLModelName (\s a -> s { _cmlmMLModelName = a }) - --- | The category of supervised learning that this 'MLModel' will address. Choose --- from the following types: --- --- Choose 'REGRESSION' if the 'MLModel' will be used to predict a numeric value. Choose --- 'BINARY' if the 'MLModel' result has two possible values. Choose 'MULTICLASS' if --- the 'MLModel' result has a limited number of values. For more information, --- see the . -cmlmMLModelType :: Lens' CreateMLModel MLModelType -cmlmMLModelType = lens _cmlmMLModelType (\s a -> s { _cmlmMLModelType = a }) +cmlmMLModelName = lens _cmlmMLModelName (\ s a -> s{_cmlmMLModelName = a}); --- | A list of the training parameters in the 'MLModel'. The list is implemented as --- a map of key/value pairs. +-- | A list of the training parameters in the 'MLModel'. The list is +-- implemented as a map of key\/value pairs. -- -- The following is the current set of training parameters: -- --- 'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. It --- controls overfitting the data by penalizing large coefficients. This tends to --- drive coefficients to zero, resulting in sparse feature set. If you use this --- parameter, start by specifying a small value such as 1.0E-08. --- --- The value is a double that ranges from 0 to MAX_DOUBLE. The default is not --- to use L1 normalization. The parameter cannot be used when 'L2' is specified. --- Use this parameter sparingly. +-- - 'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. +-- It controls overfitting the data by penalizing large coefficients. +-- This tends to drive coefficients to zero, resulting in sparse +-- feature set. If you use this parameter, start by specifying a small +-- value such as 1.0E-08. -- --- 'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. It --- controls overfitting the data by penalizing large coefficients. This tends to --- drive coefficients to small, nonzero values. If you use this parameter, start --- by specifying a small value such as 1.0E-08. +-- The value is a double that ranges from 0 to MAX_DOUBLE. The default +-- is not to use L1 normalization. The parameter cannot be used when +-- 'L2' is specified. Use this parameter sparingly. -- --- The valuseis a double that ranges from 0 to MAX_DOUBLE. The default is not --- to use L2 normalization. This cannot be used when 'L1' is specified. Use this --- parameter sparingly. +-- - 'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. +-- It controls overfitting the data by penalizing large coefficients. +-- This tends to drive coefficients to small, nonzero values. If you +-- use this parameter, start by specifying a small value such as +-- 1.0E-08. -- --- 'sgd.maxPasses' - Number of times that the training process traverses the --- observations to build the 'MLModel'. The value is an integer that ranges from 1 --- to 10000. The default value is 10. +-- The valuseis a double that ranges from 0 to MAX_DOUBLE. The default +-- is not to use L2 normalization. This cannot be used when 'L1' is +-- specified. Use this parameter sparingly. -- --- 'sgd.maxMLModelSizeInBytes' - Maximum allowed size of the model. Depending on --- the input data, the size of the model might affect its performance. +-- - 'sgd.maxPasses' - Number of times that the training process +-- traverses the observations to build the 'MLModel'. The value is an +-- integer that ranges from 1 to 10000. The default value is 10. -- --- The value is an integer that ranges from 100000 to 2147483648. The default --- value is 33554432. +-- - 'sgd.maxMLModelSizeInBytes' - Maximum allowed size of the model. +-- Depending on the input data, the size of the model might affect its +-- performance. -- +-- The value is an integer that ranges from 100000 to 2147483648. The +-- default value is 33554432. -- cmlmParameters :: Lens' CreateMLModel (HashMap Text Text) -cmlmParameters = lens _cmlmParameters (\s a -> s { _cmlmParameters = a }) . _Map +cmlmParameters = lens _cmlmParameters (\ s a -> s{_cmlmParameters = a}) . _Default . _Map; --- | The data recipe for creating 'MLModel'. You must specify either the recipe or --- its URI. If you don’t specify a recipe or its URI, Amazon ML creates a --- default. -cmlmRecipe :: Lens' CreateMLModel (Maybe Text) -cmlmRecipe = lens _cmlmRecipe (\s a -> s { _cmlmRecipe = a }) +-- | A user-supplied ID that uniquely identifies the 'MLModel'. +cmlmMLModelId :: Lens' CreateMLModel Text +cmlmMLModelId = lens _cmlmMLModelId (\ s a -> s{_cmlmMLModelId = a}); --- | The Amazon Simple Storage Service (Amazon S3) location and file name that --- contains the 'MLModel' recipe. You must specify either the recipe or its URI. --- If you don’t specify a recipe or its URI, Amazon ML creates a default. -cmlmRecipeUri :: Lens' CreateMLModel (Maybe Text) -cmlmRecipeUri = lens _cmlmRecipeUri (\s a -> s { _cmlmRecipeUri = a }) +-- | The category of supervised learning that this 'MLModel' will address. +-- Choose from the following types: +-- +-- - Choose 'REGRESSION' if the 'MLModel' will be used to predict a +-- numeric value. +-- - Choose 'BINARY' if the 'MLModel' result has two possible values. +-- - Choose 'MULTICLASS' if the 'MLModel' result has a limited number of +-- values. +-- +-- For more information, see the +-- . +cmlmMLModelType :: Lens' CreateMLModel MLModelType +cmlmMLModelType = lens _cmlmMLModelType (\ s a -> s{_cmlmMLModelType = a}); -- | The 'DataSource' that points to the training data. cmlmTrainingDataSourceId :: Lens' CreateMLModel Text -cmlmTrainingDataSourceId = - lens _cmlmTrainingDataSourceId - (\s a -> s { _cmlmTrainingDataSourceId = a }) +cmlmTrainingDataSourceId = lens _cmlmTrainingDataSourceId (\ s a -> s{_cmlmTrainingDataSourceId = a}); -newtype CreateMLModelResponse = CreateMLModelResponse - { _cmlmrMLModelId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest CreateMLModel where + type Sv CreateMLModel = MachineLearning + type Rs CreateMLModel = CreateMLModelResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + CreateMLModelResponse' <$> + (x .?> "MLModelId") <*> (pure (fromEnum s))) --- | 'CreateMLModelResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'cmlmrMLModelId' @::@ 'Maybe' 'Text' --- -createMLModelResponse :: CreateMLModelResponse -createMLModelResponse = CreateMLModelResponse - { _cmlmrMLModelId = Nothing - } +instance ToHeaders CreateMLModel where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.CreateMLModel" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | A user-supplied ID that uniquely identifies the 'MLModel'. This value should be --- identical to the value of the 'MLModelId' in the request. -cmlmrMLModelId :: Lens' CreateMLModelResponse (Maybe Text) -cmlmrMLModelId = lens _cmlmrMLModelId (\s a -> s { _cmlmrMLModelId = a }) +instance ToJSON CreateMLModel where + toJSON CreateMLModel'{..} + = object + ["Recipe" .= _cmlmRecipe, + "RecipeUri" .= _cmlmRecipeURI, + "MLModelName" .= _cmlmMLModelName, + "Parameters" .= _cmlmParameters, + "MLModelId" .= _cmlmMLModelId, + "MLModelType" .= _cmlmMLModelType, + "TrainingDataSourceId" .= _cmlmTrainingDataSourceId] instance ToPath CreateMLModel where - toPath = const "/" + toPath = const "/" instance ToQuery CreateMLModel where - toQuery = const mempty - -instance ToHeaders CreateMLModel + toQuery = const mempty -instance ToJSON CreateMLModel where - toJSON CreateMLModel{..} = object - [ "MLModelId" .= _cmlmMLModelId - , "MLModelName" .= _cmlmMLModelName - , "MLModelType" .= _cmlmMLModelType - , "Parameters" .= _cmlmParameters - , "TrainingDataSourceId" .= _cmlmTrainingDataSourceId - , "Recipe" .= _cmlmRecipe - , "RecipeUri" .= _cmlmRecipeUri - ] +-- | Represents the output of a CreateMLModel operation, and is an +-- acknowledgement that Amazon ML received the request. +-- +-- The CreateMLModel operation is asynchronous. You can poll for status +-- updates by using the GetMLModel operation and checking the 'Status' +-- parameter. +-- +-- /See:/ 'createMLModelResponse' smart constructor. +data CreateMLModelResponse = CreateMLModelResponse' + { _cmlmrsMLModelId :: !(Maybe Text) + , _cmlmrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest CreateMLModel where - type Sv CreateMLModel = MachineLearning - type Rs CreateMLModel = CreateMLModelResponse +-- | Creates a value of 'CreateMLModelResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'cmlmrsMLModelId' +-- +-- * 'cmlmrsStatus' +createMLModelResponse + :: Int -- ^ 'cmlmrsStatus' + -> CreateMLModelResponse +createMLModelResponse pStatus_ = + CreateMLModelResponse' + { _cmlmrsMLModelId = Nothing + , _cmlmrsStatus = pStatus_ + } - request = post "CreateMLModel" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the 'MLModel'. This value +-- should be identical to the value of the 'MLModelId' in the request. +cmlmrsMLModelId :: Lens' CreateMLModelResponse (Maybe Text) +cmlmrsMLModelId = lens _cmlmrsMLModelId (\ s a -> s{_cmlmrsMLModelId = a}); -instance FromJSON CreateMLModelResponse where - parseJSON = withObject "CreateMLModelResponse" $ \o -> CreateMLModelResponse - <$> o .:? "MLModelId" +-- | The response status code. +cmlmrsStatus :: Lens' CreateMLModelResponse Int +cmlmrsStatus = lens _cmlmrsStatus (\ s a -> s{_cmlmrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs b/gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs --- a/gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs +++ b/gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs @@ -1,127 +1,149 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.CreateRealtimeEndpoint --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Creates a real-time endpoint for the 'MLModel'. The endpoint contains the URI --- of the 'MLModel'; that is, the location to send real-time prediction requests --- for the specified 'MLModel'. +-- Creates a real-time endpoint for the 'MLModel'. The endpoint contains +-- the URI of the 'MLModel'; that is, the location to send real-time +-- prediction requests for the specified 'MLModel'. -- --- +-- /See:/ for CreateRealtimeEndpoint. module Network.AWS.MachineLearning.CreateRealtimeEndpoint ( - -- * Request - CreateRealtimeEndpoint - -- ** Request constructor - , createRealtimeEndpoint - -- ** Request lenses + -- * Creating a Request + createRealtimeEndpoint + , CreateRealtimeEndpoint + -- * Request Lenses , creMLModelId - -- * Response - , CreateRealtimeEndpointResponse - -- ** Response constructor + -- * Destructuring the Response , createRealtimeEndpointResponse - -- ** Response lenses - , crerMLModelId - , crerRealtimeEndpointInfo + , CreateRealtimeEndpointResponse + -- * Response Lenses + , crersRealtimeEndpointInfo + , crersMLModelId + , crersStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -newtype CreateRealtimeEndpoint = CreateRealtimeEndpoint +-- | /See:/ 'createRealtimeEndpoint' smart constructor. +newtype CreateRealtimeEndpoint = CreateRealtimeEndpoint' { _creMLModelId :: Text - } deriving (Eq, Ord, Read, Show, Monoid, IsString) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'CreateRealtimeEndpoint' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'CreateRealtimeEndpoint' with the minimum fields required to make a request. -- --- * 'creMLModelId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- -createRealtimeEndpoint :: Text -- ^ 'creMLModelId' - -> CreateRealtimeEndpoint -createRealtimeEndpoint p1 = CreateRealtimeEndpoint - { _creMLModelId = p1 +-- * 'creMLModelId' +createRealtimeEndpoint + :: Text -- ^ 'creMLModelId' + -> CreateRealtimeEndpoint +createRealtimeEndpoint pMLModelId_ = + CreateRealtimeEndpoint' + { _creMLModelId = pMLModelId_ } -- | The ID assigned to the 'MLModel' during creation. creMLModelId :: Lens' CreateRealtimeEndpoint Text -creMLModelId = lens _creMLModelId (\s a -> s { _creMLModelId = a }) - -data CreateRealtimeEndpointResponse = CreateRealtimeEndpointResponse - { _crerMLModelId :: Maybe Text - , _crerRealtimeEndpointInfo :: Maybe RealtimeEndpointInfo - } deriving (Eq, Read, Show) +creMLModelId = lens _creMLModelId (\ s a -> s{_creMLModelId = a}); --- | 'CreateRealtimeEndpointResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'crerMLModelId' @::@ 'Maybe' 'Text' --- --- * 'crerRealtimeEndpointInfo' @::@ 'Maybe' 'RealtimeEndpointInfo' --- -createRealtimeEndpointResponse :: CreateRealtimeEndpointResponse -createRealtimeEndpointResponse = CreateRealtimeEndpointResponse - { _crerMLModelId = Nothing - , _crerRealtimeEndpointInfo = Nothing - } +instance AWSRequest CreateRealtimeEndpoint where + type Sv CreateRealtimeEndpoint = MachineLearning + type Rs CreateRealtimeEndpoint = + CreateRealtimeEndpointResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + CreateRealtimeEndpointResponse' <$> + (x .?> "RealtimeEndpointInfo") <*> + (x .?> "MLModelId") + <*> (pure (fromEnum s))) --- | A user-supplied ID that uniquely identifies the 'MLModel'. This value should be --- identical to the value of the 'MLModelId' in the request. -crerMLModelId :: Lens' CreateRealtimeEndpointResponse (Maybe Text) -crerMLModelId = lens _crerMLModelId (\s a -> s { _crerMLModelId = a }) +instance ToHeaders CreateRealtimeEndpoint where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.CreateRealtimeEndpoint" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | The endpoint information of the 'MLModel' -crerRealtimeEndpointInfo :: Lens' CreateRealtimeEndpointResponse (Maybe RealtimeEndpointInfo) -crerRealtimeEndpointInfo = - lens _crerRealtimeEndpointInfo - (\s a -> s { _crerRealtimeEndpointInfo = a }) +instance ToJSON CreateRealtimeEndpoint where + toJSON CreateRealtimeEndpoint'{..} + = object ["MLModelId" .= _creMLModelId] instance ToPath CreateRealtimeEndpoint where - toPath = const "/" + toPath = const "/" instance ToQuery CreateRealtimeEndpoint where - toQuery = const mempty + toQuery = const mempty -instance ToHeaders CreateRealtimeEndpoint +-- | Represents the output of an CreateRealtimeEndpoint operation. +-- +-- The result contains the 'MLModelId' and the endpoint information for the +-- 'MLModel'. +-- +-- The endpoint information includes the URI of the 'MLModel'; that is, the +-- location to send online prediction requests for the specified 'MLModel'. +-- +-- /See:/ 'createRealtimeEndpointResponse' smart constructor. +data CreateRealtimeEndpointResponse = CreateRealtimeEndpointResponse' + { _crersRealtimeEndpointInfo :: !(Maybe RealtimeEndpointInfo) + , _crersMLModelId :: !(Maybe Text) + , _crersStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance ToJSON CreateRealtimeEndpoint where - toJSON CreateRealtimeEndpoint{..} = object - [ "MLModelId" .= _creMLModelId - ] +-- | Creates a value of 'CreateRealtimeEndpointResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'crersRealtimeEndpointInfo' +-- +-- * 'crersMLModelId' +-- +-- * 'crersStatus' +createRealtimeEndpointResponse + :: Int -- ^ 'crersStatus' + -> CreateRealtimeEndpointResponse +createRealtimeEndpointResponse pStatus_ = + CreateRealtimeEndpointResponse' + { _crersRealtimeEndpointInfo = Nothing + , _crersMLModelId = Nothing + , _crersStatus = pStatus_ + } -instance AWSRequest CreateRealtimeEndpoint where - type Sv CreateRealtimeEndpoint = MachineLearning - type Rs CreateRealtimeEndpoint = CreateRealtimeEndpointResponse +-- | The endpoint information of the 'MLModel' +crersRealtimeEndpointInfo :: Lens' CreateRealtimeEndpointResponse (Maybe RealtimeEndpointInfo) +crersRealtimeEndpointInfo = lens _crersRealtimeEndpointInfo (\ s a -> s{_crersRealtimeEndpointInfo = a}); - request = post "CreateRealtimeEndpoint" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the 'MLModel'. This value +-- should be identical to the value of the 'MLModelId' in the request. +crersMLModelId :: Lens' CreateRealtimeEndpointResponse (Maybe Text) +crersMLModelId = lens _crersMLModelId (\ s a -> s{_crersMLModelId = a}); -instance FromJSON CreateRealtimeEndpointResponse where - parseJSON = withObject "CreateRealtimeEndpointResponse" $ \o -> CreateRealtimeEndpointResponse - <$> o .:? "MLModelId" - <*> o .:? "RealtimeEndpointInfo" +-- | The response status code. +crersStatus :: Lens' CreateRealtimeEndpointResponse Int +crersStatus = lens _crersStatus (\ s a -> s{_crersStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs b/gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs --- a/gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs +++ b/gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs @@ -1,121 +1,145 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.DeleteBatchPrediction --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Assigns the DELETED status to a 'BatchPrediction', rendering it unusable. +-- Assigns the DELETED status to a 'BatchPrediction', rendering it +-- unusable. -- --- After using the 'DeleteBatchPrediction' operation, you can use the 'GetBatchPrediction' operation to verify that the status of the 'BatchPrediction' changed to --- DELETED. +-- After using the 'DeleteBatchPrediction' operation, you can use the +-- GetBatchPrediction operation to verify that the status of the +-- 'BatchPrediction' changed to DELETED. -- --- Caution The result of the 'DeleteBatchPrediction' operation is irreversible. +-- Caution -- +-- The result of the 'DeleteBatchPrediction' operation is irreversible. -- --- +-- /See:/ for DeleteBatchPrediction. module Network.AWS.MachineLearning.DeleteBatchPrediction ( - -- * Request - DeleteBatchPrediction - -- ** Request constructor - , deleteBatchPrediction - -- ** Request lenses + -- * Creating a Request + deleteBatchPrediction + , DeleteBatchPrediction + -- * Request Lenses , dbpBatchPredictionId - -- * Response - , DeleteBatchPredictionResponse - -- ** Response constructor + -- * Destructuring the Response , deleteBatchPredictionResponse - -- ** Response lenses - , dbprBatchPredictionId + , DeleteBatchPredictionResponse + -- * Response Lenses + , dbprsBatchPredictionId + , dbprsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -newtype DeleteBatchPrediction = DeleteBatchPrediction +-- | /See:/ 'deleteBatchPrediction' smart constructor. +newtype DeleteBatchPrediction = DeleteBatchPrediction' { _dbpBatchPredictionId :: Text - } deriving (Eq, Ord, Read, Show, Monoid, IsString) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'DeleteBatchPrediction' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'DeleteBatchPrediction' with the minimum fields required to make a request. -- --- * 'dbpBatchPredictionId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- -deleteBatchPrediction :: Text -- ^ 'dbpBatchPredictionId' - -> DeleteBatchPrediction -deleteBatchPrediction p1 = DeleteBatchPrediction - { _dbpBatchPredictionId = p1 +-- * 'dbpBatchPredictionId' +deleteBatchPrediction + :: Text -- ^ 'dbpBatchPredictionId' + -> DeleteBatchPrediction +deleteBatchPrediction pBatchPredictionId_ = + DeleteBatchPrediction' + { _dbpBatchPredictionId = pBatchPredictionId_ } -- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. dbpBatchPredictionId :: Lens' DeleteBatchPrediction Text -dbpBatchPredictionId = - lens _dbpBatchPredictionId (\s a -> s { _dbpBatchPredictionId = a }) +dbpBatchPredictionId = lens _dbpBatchPredictionId (\ s a -> s{_dbpBatchPredictionId = a}); -newtype DeleteBatchPredictionResponse = DeleteBatchPredictionResponse - { _dbprBatchPredictionId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest DeleteBatchPrediction where + type Sv DeleteBatchPrediction = MachineLearning + type Rs DeleteBatchPrediction = + DeleteBatchPredictionResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + DeleteBatchPredictionResponse' <$> + (x .?> "BatchPredictionId") <*> (pure (fromEnum s))) --- | 'DeleteBatchPredictionResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'dbprBatchPredictionId' @::@ 'Maybe' 'Text' --- -deleteBatchPredictionResponse :: DeleteBatchPredictionResponse -deleteBatchPredictionResponse = DeleteBatchPredictionResponse - { _dbprBatchPredictionId = Nothing - } +instance ToHeaders DeleteBatchPrediction where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.DeleteBatchPrediction" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. This value --- should be identical to the value of the 'BatchPredictionID' in the request. -dbprBatchPredictionId :: Lens' DeleteBatchPredictionResponse (Maybe Text) -dbprBatchPredictionId = - lens _dbprBatchPredictionId (\s a -> s { _dbprBatchPredictionId = a }) +instance ToJSON DeleteBatchPrediction where + toJSON DeleteBatchPrediction'{..} + = object + ["BatchPredictionId" .= _dbpBatchPredictionId] instance ToPath DeleteBatchPrediction where - toPath = const "/" + toPath = const "/" instance ToQuery DeleteBatchPrediction where - toQuery = const mempty - -instance ToHeaders DeleteBatchPrediction + toQuery = const mempty -instance ToJSON DeleteBatchPrediction where - toJSON DeleteBatchPrediction{..} = object - [ "BatchPredictionId" .= _dbpBatchPredictionId - ] +-- | Represents the output of a DeleteBatchPrediction operation. +-- +-- You can use the GetBatchPrediction operation and check the value of the +-- 'Status' parameter to see whether a 'BatchPrediction' is marked as +-- 'DELETED'. +-- +-- /See:/ 'deleteBatchPredictionResponse' smart constructor. +data DeleteBatchPredictionResponse = DeleteBatchPredictionResponse' + { _dbprsBatchPredictionId :: !(Maybe Text) + , _dbprsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest DeleteBatchPrediction where - type Sv DeleteBatchPrediction = MachineLearning - type Rs DeleteBatchPrediction = DeleteBatchPredictionResponse +-- | Creates a value of 'DeleteBatchPredictionResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'dbprsBatchPredictionId' +-- +-- * 'dbprsStatus' +deleteBatchPredictionResponse + :: Int -- ^ 'dbprsStatus' + -> DeleteBatchPredictionResponse +deleteBatchPredictionResponse pStatus_ = + DeleteBatchPredictionResponse' + { _dbprsBatchPredictionId = Nothing + , _dbprsStatus = pStatus_ + } - request = post "DeleteBatchPrediction" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. This +-- value should be identical to the value of the 'BatchPredictionID' in the +-- request. +dbprsBatchPredictionId :: Lens' DeleteBatchPredictionResponse (Maybe Text) +dbprsBatchPredictionId = lens _dbprsBatchPredictionId (\ s a -> s{_dbprsBatchPredictionId = a}); -instance FromJSON DeleteBatchPredictionResponse where - parseJSON = withObject "DeleteBatchPredictionResponse" $ \o -> DeleteBatchPredictionResponse - <$> o .:? "BatchPredictionId" +-- | The response status code. +dbprsStatus :: Lens' DeleteBatchPredictionResponse Int +dbprsStatus = lens _dbprsStatus (\ s a -> s{_dbprsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/DeleteDataSource.hs b/gen/Network/AWS/MachineLearning/DeleteDataSource.hs --- a/gen/Network/AWS/MachineLearning/DeleteDataSource.hs +++ b/gen/Network/AWS/MachineLearning/DeleteDataSource.hs @@ -1,119 +1,136 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.DeleteDataSource --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Assigns the DELETED status to a 'DataSource', rendering it unusable. +-- Assigns the DELETED status to a 'DataSource', rendering it unusable. -- --- After using the 'DeleteDataSource' operation, you can use the 'GetDataSource' --- operation to verify that the status of the 'DataSource' changed to DELETED. +-- After using the 'DeleteDataSource' operation, you can use the +-- GetDataSource operation to verify that the status of the 'DataSource' +-- changed to DELETED. -- --- Caution The results of the 'DeleteDataSource' operation are irreversible. +-- Caution -- +-- The results of the 'DeleteDataSource' operation are irreversible. -- --- +-- /See:/ for DeleteDataSource. module Network.AWS.MachineLearning.DeleteDataSource ( - -- * Request - DeleteDataSource - -- ** Request constructor - , deleteDataSource - -- ** Request lenses + -- * Creating a Request + deleteDataSource + , DeleteDataSource + -- * Request Lenses , ddsDataSourceId - -- * Response - , DeleteDataSourceResponse - -- ** Response constructor + -- * Destructuring the Response , deleteDataSourceResponse - -- ** Response lenses - , ddsrDataSourceId + , DeleteDataSourceResponse + -- * Response Lenses + , ddsrsDataSourceId + , ddsrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -newtype DeleteDataSource = DeleteDataSource +-- | /See:/ 'deleteDataSource' smart constructor. +newtype DeleteDataSource = DeleteDataSource' { _ddsDataSourceId :: Text - } deriving (Eq, Ord, Read, Show, Monoid, IsString) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'DeleteDataSource' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'DeleteDataSource' with the minimum fields required to make a request. -- --- * 'ddsDataSourceId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- -deleteDataSource :: Text -- ^ 'ddsDataSourceId' - -> DeleteDataSource -deleteDataSource p1 = DeleteDataSource - { _ddsDataSourceId = p1 +-- * 'ddsDataSourceId' +deleteDataSource + :: Text -- ^ 'ddsDataSourceId' + -> DeleteDataSource +deleteDataSource pDataSourceId_ = + DeleteDataSource' + { _ddsDataSourceId = pDataSourceId_ } -- | A user-supplied ID that uniquely identifies the 'DataSource'. ddsDataSourceId :: Lens' DeleteDataSource Text -ddsDataSourceId = lens _ddsDataSourceId (\s a -> s { _ddsDataSourceId = a }) +ddsDataSourceId = lens _ddsDataSourceId (\ s a -> s{_ddsDataSourceId = a}); -newtype DeleteDataSourceResponse = DeleteDataSourceResponse - { _ddsrDataSourceId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest DeleteDataSource where + type Sv DeleteDataSource = MachineLearning + type Rs DeleteDataSource = DeleteDataSourceResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + DeleteDataSourceResponse' <$> + (x .?> "DataSourceId") <*> (pure (fromEnum s))) --- | 'DeleteDataSourceResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'ddsrDataSourceId' @::@ 'Maybe' 'Text' --- -deleteDataSourceResponse :: DeleteDataSourceResponse -deleteDataSourceResponse = DeleteDataSourceResponse - { _ddsrDataSourceId = Nothing - } +instance ToHeaders DeleteDataSource where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.DeleteDataSource" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | A user-supplied ID that uniquely identifies the 'DataSource'. This value should --- be identical to the value of the 'DataSourceID' in the request. -ddsrDataSourceId :: Lens' DeleteDataSourceResponse (Maybe Text) -ddsrDataSourceId = lens _ddsrDataSourceId (\s a -> s { _ddsrDataSourceId = a }) +instance ToJSON DeleteDataSource where + toJSON DeleteDataSource'{..} + = object ["DataSourceId" .= _ddsDataSourceId] instance ToPath DeleteDataSource where - toPath = const "/" + toPath = const "/" instance ToQuery DeleteDataSource where - toQuery = const mempty - -instance ToHeaders DeleteDataSource + toQuery = const mempty -instance ToJSON DeleteDataSource where - toJSON DeleteDataSource{..} = object - [ "DataSourceId" .= _ddsDataSourceId - ] +-- | Represents the output of a DeleteDataSource operation. +-- +-- /See:/ 'deleteDataSourceResponse' smart constructor. +data DeleteDataSourceResponse = DeleteDataSourceResponse' + { _ddsrsDataSourceId :: !(Maybe Text) + , _ddsrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest DeleteDataSource where - type Sv DeleteDataSource = MachineLearning - type Rs DeleteDataSource = DeleteDataSourceResponse +-- | Creates a value of 'DeleteDataSourceResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'ddsrsDataSourceId' +-- +-- * 'ddsrsStatus' +deleteDataSourceResponse + :: Int -- ^ 'ddsrsStatus' + -> DeleteDataSourceResponse +deleteDataSourceResponse pStatus_ = + DeleteDataSourceResponse' + { _ddsrsDataSourceId = Nothing + , _ddsrsStatus = pStatus_ + } - request = post "DeleteDataSource" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the 'DataSource'. This value +-- should be identical to the value of the 'DataSourceID' in the request. +ddsrsDataSourceId :: Lens' DeleteDataSourceResponse (Maybe Text) +ddsrsDataSourceId = lens _ddsrsDataSourceId (\ s a -> s{_ddsrsDataSourceId = a}); -instance FromJSON DeleteDataSourceResponse where - parseJSON = withObject "DeleteDataSourceResponse" $ \o -> DeleteDataSourceResponse - <$> o .:? "DataSourceId" +-- | The response status code. +ddsrsStatus :: Lens' DeleteDataSourceResponse Int +ddsrsStatus = lens _ddsrsStatus (\ s a -> s{_ddsrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/DeleteEvaluation.hs b/gen/Network/AWS/MachineLearning/DeleteEvaluation.hs --- a/gen/Network/AWS/MachineLearning/DeleteEvaluation.hs +++ b/gen/Network/AWS/MachineLearning/DeleteEvaluation.hs @@ -1,119 +1,141 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.DeleteEvaluation --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Assigns the 'DELETED' status to an 'Evaluation', rendering it unusable. +-- Assigns the 'DELETED' status to an 'Evaluation', rendering it unusable. -- --- After invoking the 'DeleteEvaluation' operation, you can use the 'GetEvaluation' --- operation to verify that the status of the 'Evaluation' changed to 'DELETED'. +-- After invoking the 'DeleteEvaluation' operation, you can use the +-- GetEvaluation operation to verify that the status of the 'Evaluation' +-- changed to 'DELETED'. -- --- Caution The results of the 'DeleteEvaluation' operation are irreversible. +-- Caution -- +-- The results of the 'DeleteEvaluation' operation are irreversible. -- --- +-- /See:/ for DeleteEvaluation. module Network.AWS.MachineLearning.DeleteEvaluation ( - -- * Request - DeleteEvaluation - -- ** Request constructor - , deleteEvaluation - -- ** Request lenses + -- * Creating a Request + deleteEvaluation + , DeleteEvaluation + -- * Request Lenses , deEvaluationId - -- * Response - , DeleteEvaluationResponse - -- ** Response constructor + -- * Destructuring the Response , deleteEvaluationResponse - -- ** Response lenses - , derEvaluationId + , DeleteEvaluationResponse + -- * Response Lenses + , dersEvaluationId + , dersStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -newtype DeleteEvaluation = DeleteEvaluation +-- | /See:/ 'deleteEvaluation' smart constructor. +newtype DeleteEvaluation = DeleteEvaluation' { _deEvaluationId :: Text - } deriving (Eq, Ord, Read, Show, Monoid, IsString) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'DeleteEvaluation' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'DeleteEvaluation' with the minimum fields required to make a request. -- --- * 'deEvaluationId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- -deleteEvaluation :: Text -- ^ 'deEvaluationId' - -> DeleteEvaluation -deleteEvaluation p1 = DeleteEvaluation - { _deEvaluationId = p1 +-- * 'deEvaluationId' +deleteEvaluation + :: Text -- ^ 'deEvaluationId' + -> DeleteEvaluation +deleteEvaluation pEvaluationId_ = + DeleteEvaluation' + { _deEvaluationId = pEvaluationId_ } -- | A user-supplied ID that uniquely identifies the 'Evaluation' to delete. deEvaluationId :: Lens' DeleteEvaluation Text -deEvaluationId = lens _deEvaluationId (\s a -> s { _deEvaluationId = a }) +deEvaluationId = lens _deEvaluationId (\ s a -> s{_deEvaluationId = a}); -newtype DeleteEvaluationResponse = DeleteEvaluationResponse - { _derEvaluationId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest DeleteEvaluation where + type Sv DeleteEvaluation = MachineLearning + type Rs DeleteEvaluation = DeleteEvaluationResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + DeleteEvaluationResponse' <$> + (x .?> "EvaluationId") <*> (pure (fromEnum s))) --- | 'DeleteEvaluationResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'derEvaluationId' @::@ 'Maybe' 'Text' --- -deleteEvaluationResponse :: DeleteEvaluationResponse -deleteEvaluationResponse = DeleteEvaluationResponse - { _derEvaluationId = Nothing - } +instance ToHeaders DeleteEvaluation where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.DeleteEvaluation" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | A user-supplied ID that uniquely identifies the 'Evaluation'. This value should --- be identical to the value of the 'EvaluationId' in the request. -derEvaluationId :: Lens' DeleteEvaluationResponse (Maybe Text) -derEvaluationId = lens _derEvaluationId (\s a -> s { _derEvaluationId = a }) +instance ToJSON DeleteEvaluation where + toJSON DeleteEvaluation'{..} + = object ["EvaluationId" .= _deEvaluationId] instance ToPath DeleteEvaluation where - toPath = const "/" + toPath = const "/" instance ToQuery DeleteEvaluation where - toQuery = const mempty - -instance ToHeaders DeleteEvaluation + toQuery = const mempty -instance ToJSON DeleteEvaluation where - toJSON DeleteEvaluation{..} = object - [ "EvaluationId" .= _deEvaluationId - ] +-- | Represents the output of a DeleteEvaluation operation. The output +-- indicates that Amazon Machine Learning (Amazon ML) received the request. +-- +-- You can use the GetEvaluation operation and check the value of the +-- 'Status' parameter to see whether an 'Evaluation' is marked as +-- 'DELETED'. +-- +-- /See:/ 'deleteEvaluationResponse' smart constructor. +data DeleteEvaluationResponse = DeleteEvaluationResponse' + { _dersEvaluationId :: !(Maybe Text) + , _dersStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest DeleteEvaluation where - type Sv DeleteEvaluation = MachineLearning - type Rs DeleteEvaluation = DeleteEvaluationResponse +-- | Creates a value of 'DeleteEvaluationResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'dersEvaluationId' +-- +-- * 'dersStatus' +deleteEvaluationResponse + :: Int -- ^ 'dersStatus' + -> DeleteEvaluationResponse +deleteEvaluationResponse pStatus_ = + DeleteEvaluationResponse' + { _dersEvaluationId = Nothing + , _dersStatus = pStatus_ + } - request = post "DeleteEvaluation" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the 'Evaluation'. This value +-- should be identical to the value of the 'EvaluationId' in the request. +dersEvaluationId :: Lens' DeleteEvaluationResponse (Maybe Text) +dersEvaluationId = lens _dersEvaluationId (\ s a -> s{_dersEvaluationId = a}); -instance FromJSON DeleteEvaluationResponse where - parseJSON = withObject "DeleteEvaluationResponse" $ \o -> DeleteEvaluationResponse - <$> o .:? "EvaluationId" +-- | The response status code. +dersStatus :: Lens' DeleteEvaluationResponse Int +dersStatus = lens _dersStatus (\ s a -> s{_dersStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/DeleteMLModel.hs b/gen/Network/AWS/MachineLearning/DeleteMLModel.hs --- a/gen/Network/AWS/MachineLearning/DeleteMLModel.hs +++ b/gen/Network/AWS/MachineLearning/DeleteMLModel.hs @@ -1,119 +1,138 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.DeleteMLModel --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Assigns the DELETED status to an 'MLModel', rendering it unusable. +-- Assigns the DELETED status to an 'MLModel', rendering it unusable. -- --- After using the 'DeleteMLModel' operation, you can use the 'GetMLModel' +-- After using the 'DeleteMLModel' operation, you can use the GetMLModel -- operation to verify that the status of the 'MLModel' changed to DELETED. -- --- Caution The result of the 'DeleteMLModel' operation is irreversible. +-- Caution -- +-- The result of the 'DeleteMLModel' operation is irreversible. -- --- +-- /See:/ for DeleteMLModel. module Network.AWS.MachineLearning.DeleteMLModel ( - -- * Request - DeleteMLModel - -- ** Request constructor - , deleteMLModel - -- ** Request lenses + -- * Creating a Request + deleteMLModel + , DeleteMLModel + -- * Request Lenses , dmlmMLModelId - -- * Response - , DeleteMLModelResponse - -- ** Response constructor + -- * Destructuring the Response , deleteMLModelResponse - -- ** Response lenses - , dmlmrMLModelId + , DeleteMLModelResponse + -- * Response Lenses + , dmlmrsMLModelId + , dmlmrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -newtype DeleteMLModel = DeleteMLModel +-- | /See:/ 'deleteMLModel' smart constructor. +newtype DeleteMLModel = DeleteMLModel' { _dmlmMLModelId :: Text - } deriving (Eq, Ord, Read, Show, Monoid, IsString) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'DeleteMLModel' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'DeleteMLModel' with the minimum fields required to make a request. -- --- * 'dmlmMLModelId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- -deleteMLModel :: Text -- ^ 'dmlmMLModelId' - -> DeleteMLModel -deleteMLModel p1 = DeleteMLModel - { _dmlmMLModelId = p1 +-- * 'dmlmMLModelId' +deleteMLModel + :: Text -- ^ 'dmlmMLModelId' + -> DeleteMLModel +deleteMLModel pMLModelId_ = + DeleteMLModel' + { _dmlmMLModelId = pMLModelId_ } -- | A user-supplied ID that uniquely identifies the 'MLModel'. dmlmMLModelId :: Lens' DeleteMLModel Text -dmlmMLModelId = lens _dmlmMLModelId (\s a -> s { _dmlmMLModelId = a }) +dmlmMLModelId = lens _dmlmMLModelId (\ s a -> s{_dmlmMLModelId = a}); -newtype DeleteMLModelResponse = DeleteMLModelResponse - { _dmlmrMLModelId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest DeleteMLModel where + type Sv DeleteMLModel = MachineLearning + type Rs DeleteMLModel = DeleteMLModelResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + DeleteMLModelResponse' <$> + (x .?> "MLModelId") <*> (pure (fromEnum s))) --- | 'DeleteMLModelResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'dmlmrMLModelId' @::@ 'Maybe' 'Text' --- -deleteMLModelResponse :: DeleteMLModelResponse -deleteMLModelResponse = DeleteMLModelResponse - { _dmlmrMLModelId = Nothing - } +instance ToHeaders DeleteMLModel where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.DeleteMLModel" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | A user-supplied ID that uniquely identifies the 'MLModel'. This value should be --- identical to the value of the 'MLModelID' in the request. -dmlmrMLModelId :: Lens' DeleteMLModelResponse (Maybe Text) -dmlmrMLModelId = lens _dmlmrMLModelId (\s a -> s { _dmlmrMLModelId = a }) +instance ToJSON DeleteMLModel where + toJSON DeleteMLModel'{..} + = object ["MLModelId" .= _dmlmMLModelId] instance ToPath DeleteMLModel where - toPath = const "/" + toPath = const "/" instance ToQuery DeleteMLModel where - toQuery = const mempty - -instance ToHeaders DeleteMLModel + toQuery = const mempty -instance ToJSON DeleteMLModel where - toJSON DeleteMLModel{..} = object - [ "MLModelId" .= _dmlmMLModelId - ] +-- | Represents the output of a DeleteMLModel operation. +-- +-- You can use the GetMLModel operation and check the value of the 'Status' +-- parameter to see whether an 'MLModel' is marked as 'DELETED'. +-- +-- /See:/ 'deleteMLModelResponse' smart constructor. +data DeleteMLModelResponse = DeleteMLModelResponse' + { _dmlmrsMLModelId :: !(Maybe Text) + , _dmlmrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest DeleteMLModel where - type Sv DeleteMLModel = MachineLearning - type Rs DeleteMLModel = DeleteMLModelResponse +-- | Creates a value of 'DeleteMLModelResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'dmlmrsMLModelId' +-- +-- * 'dmlmrsStatus' +deleteMLModelResponse + :: Int -- ^ 'dmlmrsStatus' + -> DeleteMLModelResponse +deleteMLModelResponse pStatus_ = + DeleteMLModelResponse' + { _dmlmrsMLModelId = Nothing + , _dmlmrsStatus = pStatus_ + } - request = post "DeleteMLModel" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the 'MLModel'. This value +-- should be identical to the value of the 'MLModelID' in the request. +dmlmrsMLModelId :: Lens' DeleteMLModelResponse (Maybe Text) +dmlmrsMLModelId = lens _dmlmrsMLModelId (\ s a -> s{_dmlmrsMLModelId = a}); -instance FromJSON DeleteMLModelResponse where - parseJSON = withObject "DeleteMLModelResponse" $ \o -> DeleteMLModelResponse - <$> o .:? "MLModelId" +-- | The response status code. +dmlmrsStatus :: Lens' DeleteMLModelResponse Int +dmlmrsStatus = lens _dmlmrsStatus (\ s a -> s{_dmlmrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs b/gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs --- a/gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs +++ b/gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs @@ -1,125 +1,144 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.DeleteRealtimeEndpoint --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Deletes a real time endpoint of an 'MLModel'. +-- Deletes a real time endpoint of an 'MLModel'. -- --- +-- /See:/ for DeleteRealtimeEndpoint. module Network.AWS.MachineLearning.DeleteRealtimeEndpoint ( - -- * Request - DeleteRealtimeEndpoint - -- ** Request constructor - , deleteRealtimeEndpoint - -- ** Request lenses + -- * Creating a Request + deleteRealtimeEndpoint + , DeleteRealtimeEndpoint + -- * Request Lenses , dreMLModelId - -- * Response - , DeleteRealtimeEndpointResponse - -- ** Response constructor + -- * Destructuring the Response , deleteRealtimeEndpointResponse - -- ** Response lenses - , drerMLModelId - , drerRealtimeEndpointInfo + , DeleteRealtimeEndpointResponse + -- * Response Lenses + , drersRealtimeEndpointInfo + , drersMLModelId + , drersStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -newtype DeleteRealtimeEndpoint = DeleteRealtimeEndpoint +-- | /See:/ 'deleteRealtimeEndpoint' smart constructor. +newtype DeleteRealtimeEndpoint = DeleteRealtimeEndpoint' { _dreMLModelId :: Text - } deriving (Eq, Ord, Read, Show, Monoid, IsString) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'DeleteRealtimeEndpoint' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'DeleteRealtimeEndpoint' with the minimum fields required to make a request. -- --- * 'dreMLModelId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- -deleteRealtimeEndpoint :: Text -- ^ 'dreMLModelId' - -> DeleteRealtimeEndpoint -deleteRealtimeEndpoint p1 = DeleteRealtimeEndpoint - { _dreMLModelId = p1 +-- * 'dreMLModelId' +deleteRealtimeEndpoint + :: Text -- ^ 'dreMLModelId' + -> DeleteRealtimeEndpoint +deleteRealtimeEndpoint pMLModelId_ = + DeleteRealtimeEndpoint' + { _dreMLModelId = pMLModelId_ } -- | The ID assigned to the 'MLModel' during creation. dreMLModelId :: Lens' DeleteRealtimeEndpoint Text -dreMLModelId = lens _dreMLModelId (\s a -> s { _dreMLModelId = a }) - -data DeleteRealtimeEndpointResponse = DeleteRealtimeEndpointResponse - { _drerMLModelId :: Maybe Text - , _drerRealtimeEndpointInfo :: Maybe RealtimeEndpointInfo - } deriving (Eq, Read, Show) +dreMLModelId = lens _dreMLModelId (\ s a -> s{_dreMLModelId = a}); --- | 'DeleteRealtimeEndpointResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'drerMLModelId' @::@ 'Maybe' 'Text' --- --- * 'drerRealtimeEndpointInfo' @::@ 'Maybe' 'RealtimeEndpointInfo' --- -deleteRealtimeEndpointResponse :: DeleteRealtimeEndpointResponse -deleteRealtimeEndpointResponse = DeleteRealtimeEndpointResponse - { _drerMLModelId = Nothing - , _drerRealtimeEndpointInfo = Nothing - } +instance AWSRequest DeleteRealtimeEndpoint where + type Sv DeleteRealtimeEndpoint = MachineLearning + type Rs DeleteRealtimeEndpoint = + DeleteRealtimeEndpointResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + DeleteRealtimeEndpointResponse' <$> + (x .?> "RealtimeEndpointInfo") <*> + (x .?> "MLModelId") + <*> (pure (fromEnum s))) --- | A user-supplied ID that uniquely identifies the 'MLModel'. This value should be --- identical to the value of the 'MLModelId' in the request. -drerMLModelId :: Lens' DeleteRealtimeEndpointResponse (Maybe Text) -drerMLModelId = lens _drerMLModelId (\s a -> s { _drerMLModelId = a }) +instance ToHeaders DeleteRealtimeEndpoint where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.DeleteRealtimeEndpoint" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | The endpoint information of the 'MLModel' -drerRealtimeEndpointInfo :: Lens' DeleteRealtimeEndpointResponse (Maybe RealtimeEndpointInfo) -drerRealtimeEndpointInfo = - lens _drerRealtimeEndpointInfo - (\s a -> s { _drerRealtimeEndpointInfo = a }) +instance ToJSON DeleteRealtimeEndpoint where + toJSON DeleteRealtimeEndpoint'{..} + = object ["MLModelId" .= _dreMLModelId] instance ToPath DeleteRealtimeEndpoint where - toPath = const "/" + toPath = const "/" instance ToQuery DeleteRealtimeEndpoint where - toQuery = const mempty + toQuery = const mempty -instance ToHeaders DeleteRealtimeEndpoint +-- | Represents the output of an DeleteRealtimeEndpoint operation. +-- +-- The result contains the 'MLModelId' and the endpoint information for the +-- 'MLModel'. +-- +-- /See:/ 'deleteRealtimeEndpointResponse' smart constructor. +data DeleteRealtimeEndpointResponse = DeleteRealtimeEndpointResponse' + { _drersRealtimeEndpointInfo :: !(Maybe RealtimeEndpointInfo) + , _drersMLModelId :: !(Maybe Text) + , _drersStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance ToJSON DeleteRealtimeEndpoint where - toJSON DeleteRealtimeEndpoint{..} = object - [ "MLModelId" .= _dreMLModelId - ] +-- | Creates a value of 'DeleteRealtimeEndpointResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'drersRealtimeEndpointInfo' +-- +-- * 'drersMLModelId' +-- +-- * 'drersStatus' +deleteRealtimeEndpointResponse + :: Int -- ^ 'drersStatus' + -> DeleteRealtimeEndpointResponse +deleteRealtimeEndpointResponse pStatus_ = + DeleteRealtimeEndpointResponse' + { _drersRealtimeEndpointInfo = Nothing + , _drersMLModelId = Nothing + , _drersStatus = pStatus_ + } -instance AWSRequest DeleteRealtimeEndpoint where - type Sv DeleteRealtimeEndpoint = MachineLearning - type Rs DeleteRealtimeEndpoint = DeleteRealtimeEndpointResponse +-- | The endpoint information of the 'MLModel' +drersRealtimeEndpointInfo :: Lens' DeleteRealtimeEndpointResponse (Maybe RealtimeEndpointInfo) +drersRealtimeEndpointInfo = lens _drersRealtimeEndpointInfo (\ s a -> s{_drersRealtimeEndpointInfo = a}); - request = post "DeleteRealtimeEndpoint" - response = jsonResponse +-- | A user-supplied ID that uniquely identifies the 'MLModel'. This value +-- should be identical to the value of the 'MLModelId' in the request. +drersMLModelId :: Lens' DeleteRealtimeEndpointResponse (Maybe Text) +drersMLModelId = lens _drersMLModelId (\ s a -> s{_drersMLModelId = a}); -instance FromJSON DeleteRealtimeEndpointResponse where - parseJSON = withObject "DeleteRealtimeEndpointResponse" $ \o -> DeleteRealtimeEndpointResponse - <$> o .:? "MLModelId" - <*> o .:? "RealtimeEndpointInfo" +-- | The response status code. +drersStatus :: Lens' DeleteRealtimeEndpointResponse Int +drersStatus = lens _drersStatus (\ s a -> s{_drersStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs b/gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs --- a/gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs +++ b/gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs @@ -1,252 +1,295 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.DescribeBatchPredictions --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Returns a list of 'BatchPrediction' operations that match the search criteria --- in the request. +-- Returns a list of 'BatchPrediction' operations that match the search +-- criteria in the request. -- --- +-- /See:/ for DescribeBatchPredictions. +-- +-- This operation returns paginated results. module Network.AWS.MachineLearning.DescribeBatchPredictions ( - -- * Request - DescribeBatchPredictions - -- ** Request constructor - , describeBatchPredictions - -- ** Request lenses + -- * Creating a Request + describeBatchPredictions + , DescribeBatchPredictions + -- * Request Lenses , dbpEQ - , dbpFilterVariable , dbpGE + , dbpPrefix , dbpGT - , dbpLE - , dbpLT - , dbpLimit , dbpNE , dbpNextToken - , dbpPrefix , dbpSortOrder + , dbpLimit + , dbpLT + , dbpFilterVariable + , dbpLE - -- * Response - , DescribeBatchPredictionsResponse - -- ** Response constructor + -- * Destructuring the Response , describeBatchPredictionsResponse - -- ** Response lenses - , dbprNextToken - , dbprResults + , DescribeBatchPredictionsResponse + -- * Response Lenses + , drsResults + , drsNextToken + , drsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Pager +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data DescribeBatchPredictions = DescribeBatchPredictions - { _dbpEQ :: Maybe Text - , _dbpFilterVariable :: Maybe BatchPredictionFilterVariable - , _dbpGE :: Maybe Text - , _dbpGT :: Maybe Text - , _dbpLE :: Maybe Text - , _dbpLT :: Maybe Text - , _dbpLimit :: Maybe Nat - , _dbpNE :: Maybe Text - , _dbpNextToken :: Maybe Text - , _dbpPrefix :: Maybe Text - , _dbpSortOrder :: Maybe SortOrder - } deriving (Eq, Read, Show) +-- | /See:/ 'describeBatchPredictions' smart constructor. +data DescribeBatchPredictions = DescribeBatchPredictions' + { _dbpEQ :: !(Maybe Text) + , _dbpGE :: !(Maybe Text) + , _dbpPrefix :: !(Maybe Text) + , _dbpGT :: !(Maybe Text) + , _dbpNE :: !(Maybe Text) + , _dbpNextToken :: !(Maybe Text) + , _dbpSortOrder :: !(Maybe SortOrder) + , _dbpLimit :: !(Maybe Nat) + , _dbpLT :: !(Maybe Text) + , _dbpFilterVariable :: !(Maybe BatchPredictionFilterVariable) + , _dbpLE :: !(Maybe Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'DescribeBatchPredictions' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'DescribeBatchPredictions' with the minimum fields required to make a request. -- --- * 'dbpEQ' @::@ 'Maybe' 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'dbpFilterVariable' @::@ 'Maybe' 'BatchPredictionFilterVariable' +-- * 'dbpEQ' -- --- * 'dbpGE' @::@ 'Maybe' 'Text' +-- * 'dbpGE' -- --- * 'dbpGT' @::@ 'Maybe' 'Text' +-- * 'dbpPrefix' -- --- * 'dbpLE' @::@ 'Maybe' 'Text' +-- * 'dbpGT' -- --- * 'dbpLT' @::@ 'Maybe' 'Text' +-- * 'dbpNE' -- --- * 'dbpLimit' @::@ 'Maybe' 'Natural' +-- * 'dbpNextToken' -- --- * 'dbpNE' @::@ 'Maybe' 'Text' +-- * 'dbpSortOrder' -- --- * 'dbpNextToken' @::@ 'Maybe' 'Text' +-- * 'dbpLimit' -- --- * 'dbpPrefix' @::@ 'Maybe' 'Text' +-- * 'dbpLT' -- --- * 'dbpSortOrder' @::@ 'Maybe' 'SortOrder' +-- * 'dbpFilterVariable' -- -describeBatchPredictions :: DescribeBatchPredictions -describeBatchPredictions = DescribeBatchPredictions - { _dbpFilterVariable = Nothing - , _dbpEQ = Nothing - , _dbpGT = Nothing - , _dbpLT = Nothing - , _dbpGE = Nothing - , _dbpLE = Nothing - , _dbpNE = Nothing - , _dbpPrefix = Nothing - , _dbpSortOrder = Nothing - , _dbpNextToken = Nothing - , _dbpLimit = Nothing +-- * 'dbpLE' +describeBatchPredictions + :: DescribeBatchPredictions +describeBatchPredictions = + DescribeBatchPredictions' + { _dbpEQ = Nothing + , _dbpGE = Nothing + , _dbpPrefix = Nothing + , _dbpGT = Nothing + , _dbpNE = Nothing + , _dbpNextToken = Nothing + , _dbpSortOrder = Nothing + , _dbpLimit = Nothing + , _dbpLT = Nothing + , _dbpFilterVariable = Nothing + , _dbpLE = Nothing } --- | The equal to operator. The 'BatchPrediction' results will have 'FilterVariable' --- values that exactly match the value specified with 'EQ'. +-- | The equal to operator. The 'BatchPrediction' results will have +-- 'FilterVariable' values that exactly match the value specified with +-- 'EQ'. dbpEQ :: Lens' DescribeBatchPredictions (Maybe Text) -dbpEQ = lens _dbpEQ (\s a -> s { _dbpEQ = a }) - --- | Use one of the following variables to filter a list of 'BatchPrediction': --- --- 'CreatedAt' - Sets the search criteria to the 'BatchPrediction' creation date. --- 'Status' - Sets the search criteria to the 'BatchPrediction' status. 'Name' - --- Sets the search criteria to the contents of the 'BatchPrediction' 'Name'. 'IAMUser' - Sets the search criteria to the user account that invoked the 'BatchPrediction' creation. 'MLModelId' - Sets the search criteria to the 'MLModel' used in the 'BatchPrediction'. 'DataSourceId' - Sets the search criteria to the 'DataSource' used in the 'BatchPrediction'. 'DataURI' - Sets the search criteria to the data file(s) used in the 'BatchPrediction'. The URL can identify either a file or an Amazon Simple Storage Solution --- (Amazon S3) bucket or directory. -dbpFilterVariable :: Lens' DescribeBatchPredictions (Maybe BatchPredictionFilterVariable) -dbpFilterVariable = - lens _dbpFilterVariable (\s a -> s { _dbpFilterVariable = a }) +dbpEQ = lens _dbpEQ (\ s a -> s{_dbpEQ = a}); --- | The greater than or equal to operator. The 'BatchPrediction' results will have 'FilterVariable' values that are greater than or equal to the value specified with 'GE'. +-- | The greater than or equal to operator. The 'BatchPrediction' results +-- will have 'FilterVariable' values that are greater than or equal to the +-- value specified with 'GE'. dbpGE :: Lens' DescribeBatchPredictions (Maybe Text) -dbpGE = lens _dbpGE (\s a -> s { _dbpGE = a }) - --- | The greater than operator. The 'BatchPrediction' results will have 'FilterVariable' values that are greater than the value specified with 'GT'. -dbpGT :: Lens' DescribeBatchPredictions (Maybe Text) -dbpGT = lens _dbpGT (\s a -> s { _dbpGT = a }) - --- | The less than or equal to operator. The 'BatchPrediction' results will have 'FilterVariable' values that are less than or equal to the value specified with 'LE'. -dbpLE :: Lens' DescribeBatchPredictions (Maybe Text) -dbpLE = lens _dbpLE (\s a -> s { _dbpLE = a }) +dbpGE = lens _dbpGE (\ s a -> s{_dbpGE = a}); --- | The less than operator. The 'BatchPrediction' results will have 'FilterVariable' --- values that are less than the value specified with 'LT'. -dbpLT :: Lens' DescribeBatchPredictions (Maybe Text) -dbpLT = lens _dbpLT (\s a -> s { _dbpLT = a }) +-- | A string that is found at the beginning of a variable, such as 'Name' or +-- 'Id'. +-- +-- For example, a 'Batch Prediction' operation could have the 'Name' +-- '2014-09-09-HolidayGiftMailer'. To search for this 'BatchPrediction', +-- select 'Name' for the 'FilterVariable' and any of the following strings +-- for the 'Prefix': +-- +-- - 2014-09 +-- +-- - 2014-09-09 +-- +-- - 2014-09-09-Holiday +-- +dbpPrefix :: Lens' DescribeBatchPredictions (Maybe Text) +dbpPrefix = lens _dbpPrefix (\ s a -> s{_dbpPrefix = a}); --- | The number of pages of information to include in the result. The range of --- acceptable values is 1 through 100. The default value is 100. -dbpLimit :: Lens' DescribeBatchPredictions (Maybe Natural) -dbpLimit = lens _dbpLimit (\s a -> s { _dbpLimit = a }) . mapping _Nat +-- | The greater than operator. The 'BatchPrediction' results will have +-- 'FilterVariable' values that are greater than the value specified with +-- 'GT'. +dbpGT :: Lens' DescribeBatchPredictions (Maybe Text) +dbpGT = lens _dbpGT (\ s a -> s{_dbpGT = a}); --- | The not equal to operator. The 'BatchPrediction' results will have 'FilterVariable' values not equal to the value specified with 'NE'. +-- | The not equal to operator. The 'BatchPrediction' results will have +-- 'FilterVariable' values not equal to the value specified with 'NE'. dbpNE :: Lens' DescribeBatchPredictions (Maybe Text) -dbpNE = lens _dbpNE (\s a -> s { _dbpNE = a }) +dbpNE = lens _dbpNE (\ s a -> s{_dbpNE = a}); -- | An ID of the page in the paginated results. dbpNextToken :: Lens' DescribeBatchPredictions (Maybe Text) -dbpNextToken = lens _dbpNextToken (\s a -> s { _dbpNextToken = a }) +dbpNextToken = lens _dbpNextToken (\ s a -> s{_dbpNextToken = a}); --- | A string that is found at the beginning of a variable, such as 'Name' or 'Id'. --- --- For example, a 'Batch Prediction' operation could have the 'Name' '2014-09-09-HolidayGiftMailer'. To search for this 'BatchPrediction', select 'Name' for the 'FilterVariable' and --- any of the following strings for the 'Prefix': --- --- 2014-09 --- --- 2014-09-09 --- --- 2014-09-09-Holiday --- +-- | A two-value parameter that determines the sequence of the resulting list +-- of 'MLModel's. -- -dbpPrefix :: Lens' DescribeBatchPredictions (Maybe Text) -dbpPrefix = lens _dbpPrefix (\s a -> s { _dbpPrefix = a }) - --- | A two-value parameter that determines the sequence of the resulting list of 'MLModel's. +-- - 'asc' - Arranges the list in ascending order (A-Z, 0-9). +-- - 'dsc' - Arranges the list in descending order (Z-A, 9-0). -- --- 'asc' - Arranges the list in ascending order (A-Z, 0-9). 'dsc' - Arranges the --- list in descending order (Z-A, 9-0). Results are sorted by 'FilterVariable'. +-- Results are sorted by 'FilterVariable'. dbpSortOrder :: Lens' DescribeBatchPredictions (Maybe SortOrder) -dbpSortOrder = lens _dbpSortOrder (\s a -> s { _dbpSortOrder = a }) +dbpSortOrder = lens _dbpSortOrder (\ s a -> s{_dbpSortOrder = a}); -data DescribeBatchPredictionsResponse = DescribeBatchPredictionsResponse - { _dbprNextToken :: Maybe Text - , _dbprResults :: List "Results" BatchPrediction - } deriving (Eq, Read, Show) +-- | The number of pages of information to include in the result. The range +-- of acceptable values is 1 through 100. The default value is 100. +dbpLimit :: Lens' DescribeBatchPredictions (Maybe Natural) +dbpLimit = lens _dbpLimit (\ s a -> s{_dbpLimit = a}) . mapping _Nat; --- | 'DescribeBatchPredictionsResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'dbprNextToken' @::@ 'Maybe' 'Text' --- --- * 'dbprResults' @::@ ['BatchPrediction'] +-- | The less than operator. The 'BatchPrediction' results will have +-- 'FilterVariable' values that are less than the value specified with +-- 'LT'. +dbpLT :: Lens' DescribeBatchPredictions (Maybe Text) +dbpLT = lens _dbpLT (\ s a -> s{_dbpLT = a}); + +-- | Use one of the following variables to filter a list of +-- 'BatchPrediction': -- -describeBatchPredictionsResponse :: DescribeBatchPredictionsResponse -describeBatchPredictionsResponse = DescribeBatchPredictionsResponse - { _dbprResults = mempty - , _dbprNextToken = Nothing - } +-- - 'CreatedAt' - Sets the search criteria to the 'BatchPrediction' +-- creation date. +-- - 'Status' - Sets the search criteria to the 'BatchPrediction' status. +-- - 'Name' - Sets the search criteria to the contents of the +-- 'BatchPrediction' ____ 'Name'. +-- - 'IAMUser' - Sets the search criteria to the user account that +-- invoked the 'BatchPrediction' creation. +-- - 'MLModelId' - Sets the search criteria to the 'MLModel' used in the +-- 'BatchPrediction'. +-- - 'DataSourceId' - Sets the search criteria to the 'DataSource' used +-- in the 'BatchPrediction'. +-- - 'DataURI' - Sets the search criteria to the data file(s) used in the +-- 'BatchPrediction'. The URL can identify either a file or an Amazon +-- Simple Storage Solution (Amazon S3) bucket or directory. +dbpFilterVariable :: Lens' DescribeBatchPredictions (Maybe BatchPredictionFilterVariable) +dbpFilterVariable = lens _dbpFilterVariable (\ s a -> s{_dbpFilterVariable = a}); --- | The ID of the next page in the paginated results that indicates at least one --- more page follows. -dbprNextToken :: Lens' DescribeBatchPredictionsResponse (Maybe Text) -dbprNextToken = lens _dbprNextToken (\s a -> s { _dbprNextToken = a }) +-- | The less than or equal to operator. The 'BatchPrediction' results will +-- have 'FilterVariable' values that are less than or equal to the value +-- specified with 'LE'. +dbpLE :: Lens' DescribeBatchPredictions (Maybe Text) +dbpLE = lens _dbpLE (\ s a -> s{_dbpLE = a}); --- | A list of 'BatchPrediction' objects that meet the search criteria. -dbprResults :: Lens' DescribeBatchPredictionsResponse [BatchPrediction] -dbprResults = lens _dbprResults (\s a -> s { _dbprResults = a }) . _List +instance AWSPager DescribeBatchPredictions where + page rq rs + | stop (rs ^. drsNextToken) = Nothing + | stop (rs ^. drsResults) = Nothing + | otherwise = + Just $ rq & dbpNextToken .~ rs ^. drsNextToken +instance AWSRequest DescribeBatchPredictions where + type Sv DescribeBatchPredictions = MachineLearning + type Rs DescribeBatchPredictions = + DescribeBatchPredictionsResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + DescribeBatchPredictionsResponse' <$> + (x .?> "Results" .!@ mempty) <*> (x .?> "NextToken") + <*> (pure (fromEnum s))) + +instance ToHeaders DescribeBatchPredictions where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.DescribeBatchPredictions" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) + +instance ToJSON DescribeBatchPredictions where + toJSON DescribeBatchPredictions'{..} + = object + ["EQ" .= _dbpEQ, "GE" .= _dbpGE, + "Prefix" .= _dbpPrefix, "GT" .= _dbpGT, + "NE" .= _dbpNE, "NextToken" .= _dbpNextToken, + "SortOrder" .= _dbpSortOrder, "Limit" .= _dbpLimit, + "LT" .= _dbpLT, + "FilterVariable" .= _dbpFilterVariable, + "LE" .= _dbpLE] + instance ToPath DescribeBatchPredictions where - toPath = const "/" + toPath = const "/" instance ToQuery DescribeBatchPredictions where - toQuery = const mempty - -instance ToHeaders DescribeBatchPredictions + toQuery = const mempty -instance ToJSON DescribeBatchPredictions where - toJSON DescribeBatchPredictions{..} = object - [ "FilterVariable" .= _dbpFilterVariable - , "EQ" .= _dbpEQ - , "GT" .= _dbpGT - , "LT" .= _dbpLT - , "GE" .= _dbpGE - , "LE" .= _dbpLE - , "NE" .= _dbpNE - , "Prefix" .= _dbpPrefix - , "SortOrder" .= _dbpSortOrder - , "NextToken" .= _dbpNextToken - , "Limit" .= _dbpLimit - ] +-- | Represents the output of a DescribeBatchPredictions operation. The +-- content is essentially a list of 'BatchPrediction's. +-- +-- /See:/ 'describeBatchPredictionsResponse' smart constructor. +data DescribeBatchPredictionsResponse = DescribeBatchPredictionsResponse' + { _drsResults :: !(Maybe [BatchPrediction]) + , _drsNextToken :: !(Maybe Text) + , _drsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest DescribeBatchPredictions where - type Sv DescribeBatchPredictions = MachineLearning - type Rs DescribeBatchPredictions = DescribeBatchPredictionsResponse +-- | Creates a value of 'DescribeBatchPredictionsResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'drsResults' +-- +-- * 'drsNextToken' +-- +-- * 'drsStatus' +describeBatchPredictionsResponse + :: Int -- ^ 'drsStatus' + -> DescribeBatchPredictionsResponse +describeBatchPredictionsResponse pStatus_ = + DescribeBatchPredictionsResponse' + { _drsResults = Nothing + , _drsNextToken = Nothing + , _drsStatus = pStatus_ + } - request = post "DescribeBatchPredictions" - response = jsonResponse +-- | A list of BatchPrediction objects that meet the search criteria. +drsResults :: Lens' DescribeBatchPredictionsResponse [BatchPrediction] +drsResults = lens _drsResults (\ s a -> s{_drsResults = a}) . _Default . _Coerce; -instance FromJSON DescribeBatchPredictionsResponse where - parseJSON = withObject "DescribeBatchPredictionsResponse" $ \o -> DescribeBatchPredictionsResponse - <$> o .:? "NextToken" - <*> o .:? "Results" .!= mempty +-- | The ID of the next page in the paginated results that indicates at least +-- one more page follows. +drsNextToken :: Lens' DescribeBatchPredictionsResponse (Maybe Text) +drsNextToken = lens _drsNextToken (\ s a -> s{_drsNextToken = a}); -instance AWSPager DescribeBatchPredictions where - page rq rs - | stop (rs ^. dbprNextToken) = Nothing - | otherwise = (\x -> rq & dbpNextToken ?~ x) - <$> (rs ^. dbprNextToken) +-- | The response status code. +drsStatus :: Lens' DescribeBatchPredictionsResponse Int +drsStatus = lens _drsStatus (\ s a -> s{_drsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/DescribeDataSources.hs b/gen/Network/AWS/MachineLearning/DescribeDataSources.hs --- a/gen/Network/AWS/MachineLearning/DescribeDataSources.hs +++ b/gen/Network/AWS/MachineLearning/DescribeDataSources.hs @@ -1,256 +1,289 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.DescribeDataSources --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Returns a list of 'DataSource' that match the search criteria in the request. +-- Returns a list of 'DataSource' that match the search criteria in the +-- request. -- --- +-- /See:/ for DescribeDataSources. +-- +-- This operation returns paginated results. module Network.AWS.MachineLearning.DescribeDataSources ( - -- * Request - DescribeDataSources - -- ** Request constructor - , describeDataSources - -- ** Request lenses + -- * Creating a Request + describeDataSources + , DescribeDataSources + -- * Request Lenses , ddsEQ - , ddsFilterVariable , ddsGE + , ddsPrefix , ddsGT - , ddsLE - , ddsLT - , ddsLimit , ddsNE , ddsNextToken - , ddsPrefix , ddsSortOrder + , ddsLimit + , ddsLT + , ddsFilterVariable + , ddsLE - -- * Response - , DescribeDataSourcesResponse - -- ** Response constructor + -- * Destructuring the Response , describeDataSourcesResponse - -- ** Response lenses - , ddsrNextToken - , ddsrResults + , DescribeDataSourcesResponse + -- * Response Lenses + , ddssrsResults + , ddssrsNextToken + , ddssrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Pager +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data DescribeDataSources = DescribeDataSources - { _ddsEQ :: Maybe Text - , _ddsFilterVariable :: Maybe DataSourceFilterVariable - , _ddsGE :: Maybe Text - , _ddsGT :: Maybe Text - , _ddsLE :: Maybe Text - , _ddsLT :: Maybe Text - , _ddsLimit :: Maybe Nat - , _ddsNE :: Maybe Text - , _ddsNextToken :: Maybe Text - , _ddsPrefix :: Maybe Text - , _ddsSortOrder :: Maybe SortOrder - } deriving (Eq, Read, Show) +-- | /See:/ 'describeDataSources' smart constructor. +data DescribeDataSources = DescribeDataSources' + { _ddsEQ :: !(Maybe Text) + , _ddsGE :: !(Maybe Text) + , _ddsPrefix :: !(Maybe Text) + , _ddsGT :: !(Maybe Text) + , _ddsNE :: !(Maybe Text) + , _ddsNextToken :: !(Maybe Text) + , _ddsSortOrder :: !(Maybe SortOrder) + , _ddsLimit :: !(Maybe Nat) + , _ddsLT :: !(Maybe Text) + , _ddsFilterVariable :: !(Maybe DataSourceFilterVariable) + , _ddsLE :: !(Maybe Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'DescribeDataSources' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'DescribeDataSources' with the minimum fields required to make a request. -- --- * 'ddsEQ' @::@ 'Maybe' 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'ddsFilterVariable' @::@ 'Maybe' 'DataSourceFilterVariable' +-- * 'ddsEQ' -- --- * 'ddsGE' @::@ 'Maybe' 'Text' +-- * 'ddsGE' -- --- * 'ddsGT' @::@ 'Maybe' 'Text' +-- * 'ddsPrefix' -- --- * 'ddsLE' @::@ 'Maybe' 'Text' +-- * 'ddsGT' -- --- * 'ddsLT' @::@ 'Maybe' 'Text' +-- * 'ddsNE' -- --- * 'ddsLimit' @::@ 'Maybe' 'Natural' +-- * 'ddsNextToken' -- --- * 'ddsNE' @::@ 'Maybe' 'Text' +-- * 'ddsSortOrder' -- --- * 'ddsNextToken' @::@ 'Maybe' 'Text' +-- * 'ddsLimit' -- --- * 'ddsPrefix' @::@ 'Maybe' 'Text' +-- * 'ddsLT' -- --- * 'ddsSortOrder' @::@ 'Maybe' 'SortOrder' +-- * 'ddsFilterVariable' -- -describeDataSources :: DescribeDataSources -describeDataSources = DescribeDataSources - { _ddsFilterVariable = Nothing - , _ddsEQ = Nothing - , _ddsGT = Nothing - , _ddsLT = Nothing - , _ddsGE = Nothing - , _ddsLE = Nothing - , _ddsNE = Nothing - , _ddsPrefix = Nothing - , _ddsSortOrder = Nothing - , _ddsNextToken = Nothing - , _ddsLimit = Nothing +-- * 'ddsLE' +describeDataSources + :: DescribeDataSources +describeDataSources = + DescribeDataSources' + { _ddsEQ = Nothing + , _ddsGE = Nothing + , _ddsPrefix = Nothing + , _ddsGT = Nothing + , _ddsNE = Nothing + , _ddsNextToken = Nothing + , _ddsSortOrder = Nothing + , _ddsLimit = Nothing + , _ddsLT = Nothing + , _ddsFilterVariable = Nothing + , _ddsLE = Nothing } --- | The equal to operator. The 'DataSource' results will have 'FilterVariable' values --- that exactly match the value specified with 'EQ'. +-- | The equal to operator. The 'DataSource' results will have +-- 'FilterVariable' values that exactly match the value specified with +-- 'EQ'. ddsEQ :: Lens' DescribeDataSources (Maybe Text) -ddsEQ = lens _ddsEQ (\s a -> s { _ddsEQ = a }) - --- | Use one of the following variables to filter a list of 'DataSource': --- --- 'CreatedAt' - Sets the search criteria to 'DataSource' creation dates. 'Status' --- - Sets the search criteria to 'DataSource' statuses. 'Name' - Sets the search --- criteria to the contents of 'DataSource' 'Name'. 'DataUri' - Sets the search --- criteria to the URI of data files used to create the 'DataSource'. The URI can --- identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket --- or directory. 'IAMUser' - Sets the search criteria to the user account that --- invoked the 'DataSource' creation. -ddsFilterVariable :: Lens' DescribeDataSources (Maybe DataSourceFilterVariable) -ddsFilterVariable = - lens _ddsFilterVariable (\s a -> s { _ddsFilterVariable = a }) +ddsEQ = lens _ddsEQ (\ s a -> s{_ddsEQ = a}); --- | The greater than or equal to operator. The 'DataSource' results will have 'FilterVariable' values that are greater than or equal to the value specified with 'GE'. +-- | The greater than or equal to operator. The 'DataSource' results will +-- have 'FilterVariable' values that are greater than or equal to the value +-- specified with 'GE'. ddsGE :: Lens' DescribeDataSources (Maybe Text) -ddsGE = lens _ddsGE (\s a -> s { _ddsGE = a }) - --- | The greater than operator. The 'DataSource' results will have 'FilterVariable' --- values that are greater than the value specified with 'GT'. -ddsGT :: Lens' DescribeDataSources (Maybe Text) -ddsGT = lens _ddsGT (\s a -> s { _ddsGT = a }) - --- | The less than or equal to operator. The 'DataSource' results will have 'FilterVariable' values that are less than or equal to the value specified with 'LE'. -ddsLE :: Lens' DescribeDataSources (Maybe Text) -ddsLE = lens _ddsLE (\s a -> s { _ddsLE = a }) +ddsGE = lens _ddsGE (\ s a -> s{_ddsGE = a}); --- | The less than operator. The 'DataSource' results will have 'FilterVariable' --- values that are less than the value specified with 'LT'. -ddsLT :: Lens' DescribeDataSources (Maybe Text) -ddsLT = lens _ddsLT (\s a -> s { _ddsLT = a }) +-- | A string that is found at the beginning of a variable, such as 'Name' or +-- 'Id'. +-- +-- For example, a 'DataSource' could have the 'Name' +-- '2014-09-09-HolidayGiftMailer'. To search for this 'DataSource', select +-- 'Name' for the 'FilterVariable' and any of the following strings for the +-- 'Prefix': +-- +-- - 2014-09 +-- +-- - 2014-09-09 +-- +-- - 2014-09-09-Holiday +-- +ddsPrefix :: Lens' DescribeDataSources (Maybe Text) +ddsPrefix = lens _ddsPrefix (\ s a -> s{_ddsPrefix = a}); --- | The maximum number of 'DataSource' to include in the result. -ddsLimit :: Lens' DescribeDataSources (Maybe Natural) -ddsLimit = lens _ddsLimit (\s a -> s { _ddsLimit = a }) . mapping _Nat +-- | The greater than operator. The 'DataSource' results will have +-- 'FilterVariable' values that are greater than the value specified with +-- 'GT'. +ddsGT :: Lens' DescribeDataSources (Maybe Text) +ddsGT = lens _ddsGT (\ s a -> s{_ddsGT = a}); --- | The not equal to operator. The 'DataSource' results will have 'FilterVariable' --- values not equal to the value specified with 'NE'. +-- | The not equal to operator. The 'DataSource' results will have +-- 'FilterVariable' values not equal to the value specified with 'NE'. ddsNE :: Lens' DescribeDataSources (Maybe Text) -ddsNE = lens _ddsNE (\s a -> s { _ddsNE = a }) +ddsNE = lens _ddsNE (\ s a -> s{_ddsNE = a}); -- | The ID of the page in the paginated results. ddsNextToken :: Lens' DescribeDataSources (Maybe Text) -ddsNextToken = lens _ddsNextToken (\s a -> s { _ddsNextToken = a }) +ddsNextToken = lens _ddsNextToken (\ s a -> s{_ddsNextToken = a}); --- | A string that is found at the beginning of a variable, such as 'Name' or 'Id'. --- --- For example, a 'DataSource' could have the 'Name' '2014-09-09-HolidayGiftMailer'. --- To search for this 'DataSource', select 'Name' for the 'FilterVariable' and any of --- the following strings for the 'Prefix': --- --- 2014-09 --- --- 2014-09-09 --- --- 2014-09-09-Holiday --- +-- | A two-value parameter that determines the sequence of the resulting list +-- of 'DataSource'. -- -ddsPrefix :: Lens' DescribeDataSources (Maybe Text) -ddsPrefix = lens _ddsPrefix (\s a -> s { _ddsPrefix = a }) - --- | A two-value parameter that determines the sequence of the resulting list of 'DataSource'. +-- - 'asc' - Arranges the list in ascending order (A-Z, 0-9). +-- - 'dsc' - Arranges the list in descending order (Z-A, 9-0). -- --- 'asc' - Arranges the list in ascending order (A-Z, 0-9). 'dsc' - Arranges the --- list in descending order (Z-A, 9-0). Results are sorted by 'FilterVariable'. +-- Results are sorted by 'FilterVariable'. ddsSortOrder :: Lens' DescribeDataSources (Maybe SortOrder) -ddsSortOrder = lens _ddsSortOrder (\s a -> s { _ddsSortOrder = a }) +ddsSortOrder = lens _ddsSortOrder (\ s a -> s{_ddsSortOrder = a}); -data DescribeDataSourcesResponse = DescribeDataSourcesResponse - { _ddsrNextToken :: Maybe Text - , _ddsrResults :: List "Results" DataSource - } deriving (Eq, Read, Show) +-- | The maximum number of 'DataSource' to include in the result. +ddsLimit :: Lens' DescribeDataSources (Maybe Natural) +ddsLimit = lens _ddsLimit (\ s a -> s{_ddsLimit = a}) . mapping _Nat; --- | 'DescribeDataSourcesResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'ddsrNextToken' @::@ 'Maybe' 'Text' --- --- * 'ddsrResults' @::@ ['DataSource'] +-- | The less than operator. The 'DataSource' results will have +-- 'FilterVariable' values that are less than the value specified with +-- 'LT'. +ddsLT :: Lens' DescribeDataSources (Maybe Text) +ddsLT = lens _ddsLT (\ s a -> s{_ddsLT = a}); + +-- | Use one of the following variables to filter a list of 'DataSource': -- -describeDataSourcesResponse :: DescribeDataSourcesResponse -describeDataSourcesResponse = DescribeDataSourcesResponse - { _ddsrResults = mempty - , _ddsrNextToken = Nothing - } +-- - 'CreatedAt' - Sets the search criteria to 'DataSource' creation +-- dates. +-- - 'Status' - Sets the search criteria to 'DataSource' statuses. +-- - 'Name' - Sets the search criteria to the contents of 'DataSource' +-- ____ 'Name'. +-- - 'DataUri' - Sets the search criteria to the URI of data files used +-- to create the 'DataSource'. The URI can identify either a file or an +-- Amazon Simple Storage Service (Amazon S3) bucket or directory. +-- - 'IAMUser' - Sets the search criteria to the user account that +-- invoked the 'DataSource' creation. +ddsFilterVariable :: Lens' DescribeDataSources (Maybe DataSourceFilterVariable) +ddsFilterVariable = lens _ddsFilterVariable (\ s a -> s{_ddsFilterVariable = a}); --- | An ID of the next page in the paginated results that indicates at least one --- more page follows. -ddsrNextToken :: Lens' DescribeDataSourcesResponse (Maybe Text) -ddsrNextToken = lens _ddsrNextToken (\s a -> s { _ddsrNextToken = a }) +-- | The less than or equal to operator. The 'DataSource' results will have +-- 'FilterVariable' values that are less than or equal to the value +-- specified with 'LE'. +ddsLE :: Lens' DescribeDataSources (Maybe Text) +ddsLE = lens _ddsLE (\ s a -> s{_ddsLE = a}); --- | A list of 'DataSource' that meet the search criteria. -ddsrResults :: Lens' DescribeDataSourcesResponse [DataSource] -ddsrResults = lens _ddsrResults (\s a -> s { _ddsrResults = a }) . _List +instance AWSPager DescribeDataSources where + page rq rs + | stop (rs ^. ddssrsNextToken) = Nothing + | stop (rs ^. ddssrsResults) = Nothing + | otherwise = + Just $ rq & ddsNextToken .~ rs ^. ddssrsNextToken +instance AWSRequest DescribeDataSources where + type Sv DescribeDataSources = MachineLearning + type Rs DescribeDataSources = + DescribeDataSourcesResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + DescribeDataSourcesResponse' <$> + (x .?> "Results" .!@ mempty) <*> (x .?> "NextToken") + <*> (pure (fromEnum s))) + +instance ToHeaders DescribeDataSources where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.DescribeDataSources" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) + +instance ToJSON DescribeDataSources where + toJSON DescribeDataSources'{..} + = object + ["EQ" .= _ddsEQ, "GE" .= _ddsGE, + "Prefix" .= _ddsPrefix, "GT" .= _ddsGT, + "NE" .= _ddsNE, "NextToken" .= _ddsNextToken, + "SortOrder" .= _ddsSortOrder, "Limit" .= _ddsLimit, + "LT" .= _ddsLT, + "FilterVariable" .= _ddsFilterVariable, + "LE" .= _ddsLE] + instance ToPath DescribeDataSources where - toPath = const "/" + toPath = const "/" instance ToQuery DescribeDataSources where - toQuery = const mempty - -instance ToHeaders DescribeDataSources + toQuery = const mempty -instance ToJSON DescribeDataSources where - toJSON DescribeDataSources{..} = object - [ "FilterVariable" .= _ddsFilterVariable - , "EQ" .= _ddsEQ - , "GT" .= _ddsGT - , "LT" .= _ddsLT - , "GE" .= _ddsGE - , "LE" .= _ddsLE - , "NE" .= _ddsNE - , "Prefix" .= _ddsPrefix - , "SortOrder" .= _ddsSortOrder - , "NextToken" .= _ddsNextToken - , "Limit" .= _ddsLimit - ] +-- | Represents the query results from a DescribeDataSources operation. The +-- content is essentially a list of 'DataSource'. +-- +-- /See:/ 'describeDataSourcesResponse' smart constructor. +data DescribeDataSourcesResponse = DescribeDataSourcesResponse' + { _ddssrsResults :: !(Maybe [DataSource]) + , _ddssrsNextToken :: !(Maybe Text) + , _ddssrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest DescribeDataSources where - type Sv DescribeDataSources = MachineLearning - type Rs DescribeDataSources = DescribeDataSourcesResponse +-- | Creates a value of 'DescribeDataSourcesResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'ddssrsResults' +-- +-- * 'ddssrsNextToken' +-- +-- * 'ddssrsStatus' +describeDataSourcesResponse + :: Int -- ^ 'ddssrsStatus' + -> DescribeDataSourcesResponse +describeDataSourcesResponse pStatus_ = + DescribeDataSourcesResponse' + { _ddssrsResults = Nothing + , _ddssrsNextToken = Nothing + , _ddssrsStatus = pStatus_ + } - request = post "DescribeDataSources" - response = jsonResponse +-- | A list of 'DataSource' that meet the search criteria. +ddssrsResults :: Lens' DescribeDataSourcesResponse [DataSource] +ddssrsResults = lens _ddssrsResults (\ s a -> s{_ddssrsResults = a}) . _Default . _Coerce; -instance FromJSON DescribeDataSourcesResponse where - parseJSON = withObject "DescribeDataSourcesResponse" $ \o -> DescribeDataSourcesResponse - <$> o .:? "NextToken" - <*> o .:? "Results" .!= mempty +-- | An ID of the next page in the paginated results that indicates at least +-- one more page follows. +ddssrsNextToken :: Lens' DescribeDataSourcesResponse (Maybe Text) +ddssrsNextToken = lens _ddssrsNextToken (\ s a -> s{_ddssrsNextToken = a}); -instance AWSPager DescribeDataSources where - page rq rs - | stop (rs ^. ddsrNextToken) = Nothing - | otherwise = (\x -> rq & ddsNextToken ?~ x) - <$> (rs ^. ddsrNextToken) +-- | The response status code. +ddssrsStatus :: Lens' DescribeDataSourcesResponse Int +ddssrsStatus = lens _ddssrsStatus (\ s a -> s{_ddssrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/DescribeEvaluations.hs b/gen/Network/AWS/MachineLearning/DescribeEvaluations.hs --- a/gen/Network/AWS/MachineLearning/DescribeEvaluations.hs +++ b/gen/Network/AWS/MachineLearning/DescribeEvaluations.hs @@ -1,257 +1,293 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.DescribeEvaluations --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Returns a list of 'DescribeEvaluations' that match the search criteria in the --- request. +-- Returns a list of 'DescribeEvaluations' that match the search criteria +-- in the request. -- --- +-- /See:/ for DescribeEvaluations. +-- +-- This operation returns paginated results. module Network.AWS.MachineLearning.DescribeEvaluations ( - -- * Request - DescribeEvaluations - -- ** Request constructor - , describeEvaluations - -- ** Request lenses + -- * Creating a Request + describeEvaluations + , DescribeEvaluations + -- * Request Lenses , deEQ - , deFilterVariable , deGE + , dePrefix , deGT - , deLE - , deLT - , deLimit , deNE , deNextToken - , dePrefix , deSortOrder + , deLimit + , deLT + , deFilterVariable + , deLE - -- * Response - , DescribeEvaluationsResponse - -- ** Response constructor + -- * Destructuring the Response , describeEvaluationsResponse - -- ** Response lenses - , derNextToken - , derResults + , DescribeEvaluationsResponse + -- * Response Lenses + , desrsResults + , desrsNextToken + , desrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Pager +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data DescribeEvaluations = DescribeEvaluations - { _deEQ :: Maybe Text - , _deFilterVariable :: Maybe EvaluationFilterVariable - , _deGE :: Maybe Text - , _deGT :: Maybe Text - , _deLE :: Maybe Text - , _deLT :: Maybe Text - , _deLimit :: Maybe Nat - , _deNE :: Maybe Text - , _deNextToken :: Maybe Text - , _dePrefix :: Maybe Text - , _deSortOrder :: Maybe SortOrder - } deriving (Eq, Read, Show) +-- | /See:/ 'describeEvaluations' smart constructor. +data DescribeEvaluations = DescribeEvaluations' + { _deEQ :: !(Maybe Text) + , _deGE :: !(Maybe Text) + , _dePrefix :: !(Maybe Text) + , _deGT :: !(Maybe Text) + , _deNE :: !(Maybe Text) + , _deNextToken :: !(Maybe Text) + , _deSortOrder :: !(Maybe SortOrder) + , _deLimit :: !(Maybe Nat) + , _deLT :: !(Maybe Text) + , _deFilterVariable :: !(Maybe EvaluationFilterVariable) + , _deLE :: !(Maybe Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'DescribeEvaluations' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'DescribeEvaluations' with the minimum fields required to make a request. -- --- * 'deEQ' @::@ 'Maybe' 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'deFilterVariable' @::@ 'Maybe' 'EvaluationFilterVariable' +-- * 'deEQ' -- --- * 'deGE' @::@ 'Maybe' 'Text' +-- * 'deGE' -- --- * 'deGT' @::@ 'Maybe' 'Text' +-- * 'dePrefix' -- --- * 'deLE' @::@ 'Maybe' 'Text' +-- * 'deGT' -- --- * 'deLT' @::@ 'Maybe' 'Text' +-- * 'deNE' -- --- * 'deLimit' @::@ 'Maybe' 'Natural' +-- * 'deNextToken' -- --- * 'deNE' @::@ 'Maybe' 'Text' +-- * 'deSortOrder' -- --- * 'deNextToken' @::@ 'Maybe' 'Text' +-- * 'deLimit' -- --- * 'dePrefix' @::@ 'Maybe' 'Text' +-- * 'deLT' -- --- * 'deSortOrder' @::@ 'Maybe' 'SortOrder' +-- * 'deFilterVariable' -- -describeEvaluations :: DescribeEvaluations -describeEvaluations = DescribeEvaluations - { _deFilterVariable = Nothing - , _deEQ = Nothing - , _deGT = Nothing - , _deLT = Nothing - , _deGE = Nothing - , _deLE = Nothing - , _deNE = Nothing - , _dePrefix = Nothing - , _deSortOrder = Nothing - , _deNextToken = Nothing - , _deLimit = Nothing +-- * 'deLE' +describeEvaluations + :: DescribeEvaluations +describeEvaluations = + DescribeEvaluations' + { _deEQ = Nothing + , _deGE = Nothing + , _dePrefix = Nothing + , _deGT = Nothing + , _deNE = Nothing + , _deNextToken = Nothing + , _deSortOrder = Nothing + , _deLimit = Nothing + , _deLT = Nothing + , _deFilterVariable = Nothing + , _deLE = Nothing } --- | The equal to operator. The 'Evaluation' results will have 'FilterVariable' values --- that exactly match the value specified with 'EQ'. +-- | The equal to operator. The 'Evaluation' results will have +-- 'FilterVariable' values that exactly match the value specified with +-- 'EQ'. deEQ :: Lens' DescribeEvaluations (Maybe Text) -deEQ = lens _deEQ (\s a -> s { _deEQ = a }) - --- | Use one of the following variable to filter a list of 'Evaluation' objects: --- --- 'CreatedAt' - Sets the search criteria to the 'Evaluation' creation date. 'Status' - Sets the search criteria to the 'Evaluation' status. 'Name' - Sets the search --- criteria to the contents of 'Evaluation' 'Name'. 'IAMUser' - Sets the search --- criteria to the user account that invoked an 'Evaluation'. 'MLModelId' - Sets --- the search criteria to the 'MLModel' that was evaluated. 'DataSourceId' - Sets --- the search criteria to the 'DataSource' used in 'Evaluation'. 'DataUri' - Sets the --- search criteria to the data file(s) used in 'Evaluation'. The URL can identify --- either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or --- directory. -deFilterVariable :: Lens' DescribeEvaluations (Maybe EvaluationFilterVariable) -deFilterVariable = lens _deFilterVariable (\s a -> s { _deFilterVariable = a }) +deEQ = lens _deEQ (\ s a -> s{_deEQ = a}); --- | The greater than or equal to operator. The 'Evaluation' results will have 'FilterVariable' values that are greater than or equal to the value specified with 'GE'. +-- | The greater than or equal to operator. The 'Evaluation' results will +-- have 'FilterVariable' values that are greater than or equal to the value +-- specified with 'GE'. deGE :: Lens' DescribeEvaluations (Maybe Text) -deGE = lens _deGE (\s a -> s { _deGE = a }) - --- | The greater than operator. The 'Evaluation' results will have 'FilterVariable' --- values that are greater than the value specified with 'GT'. -deGT :: Lens' DescribeEvaluations (Maybe Text) -deGT = lens _deGT (\s a -> s { _deGT = a }) - --- | The less than or equal to operator. The 'Evaluation' results will have 'FilterVariable' values that are less than or equal to the value specified with 'LE'. -deLE :: Lens' DescribeEvaluations (Maybe Text) -deLE = lens _deLE (\s a -> s { _deLE = a }) +deGE = lens _deGE (\ s a -> s{_deGE = a}); --- | The less than operator. The 'Evaluation' results will have 'FilterVariable' --- values that are less than the value specified with 'LT'. -deLT :: Lens' DescribeEvaluations (Maybe Text) -deLT = lens _deLT (\s a -> s { _deLT = a }) +-- | A string that is found at the beginning of a variable, such as 'Name' or +-- 'Id'. +-- +-- For example, an 'Evaluation' could have the 'Name' +-- '2014-09-09-HolidayGiftMailer'. To search for this 'Evaluation', select +-- 'Name' for the 'FilterVariable' and any of the following strings for the +-- 'Prefix': +-- +-- - 2014-09 +-- +-- - 2014-09-09 +-- +-- - 2014-09-09-Holiday +-- +dePrefix :: Lens' DescribeEvaluations (Maybe Text) +dePrefix = lens _dePrefix (\ s a -> s{_dePrefix = a}); --- | The maximum number of 'Evaluation' to include in the result. -deLimit :: Lens' DescribeEvaluations (Maybe Natural) -deLimit = lens _deLimit (\s a -> s { _deLimit = a }) . mapping _Nat +-- | The greater than operator. The 'Evaluation' results will have +-- 'FilterVariable' values that are greater than the value specified with +-- 'GT'. +deGT :: Lens' DescribeEvaluations (Maybe Text) +deGT = lens _deGT (\ s a -> s{_deGT = a}); --- | The not equal to operator. The 'Evaluation' results will have 'FilterVariable' --- values not equal to the value specified with 'NE'. +-- | The not equal to operator. The 'Evaluation' results will have +-- 'FilterVariable' values not equal to the value specified with 'NE'. deNE :: Lens' DescribeEvaluations (Maybe Text) -deNE = lens _deNE (\s a -> s { _deNE = a }) +deNE = lens _deNE (\ s a -> s{_deNE = a}); -- | The ID of the page in the paginated results. deNextToken :: Lens' DescribeEvaluations (Maybe Text) -deNextToken = lens _deNextToken (\s a -> s { _deNextToken = a }) +deNextToken = lens _deNextToken (\ s a -> s{_deNextToken = a}); --- | A string that is found at the beginning of a variable, such as 'Name' or 'Id'. --- --- For example, an 'Evaluation' could have the 'Name' '2014-09-09-HolidayGiftMailer'. --- To search for this 'Evaluation', select 'Name' for the 'FilterVariable' and any of --- the following strings for the 'Prefix': --- --- 2014-09 --- --- 2014-09-09 --- --- 2014-09-09-Holiday --- +-- | A two-value parameter that determines the sequence of the resulting list +-- of 'Evaluation'. -- -dePrefix :: Lens' DescribeEvaluations (Maybe Text) -dePrefix = lens _dePrefix (\s a -> s { _dePrefix = a }) - --- | A two-value parameter that determines the sequence of the resulting list of 'Evaluation'. +-- - 'asc' - Arranges the list in ascending order (A-Z, 0-9). +-- - 'dsc' - Arranges the list in descending order (Z-A, 9-0). -- --- 'asc' - Arranges the list in ascending order (A-Z, 0-9). 'dsc' - Arranges the --- list in descending order (Z-A, 9-0). Results are sorted by 'FilterVariable'. +-- Results are sorted by 'FilterVariable'. deSortOrder :: Lens' DescribeEvaluations (Maybe SortOrder) -deSortOrder = lens _deSortOrder (\s a -> s { _deSortOrder = a }) +deSortOrder = lens _deSortOrder (\ s a -> s{_deSortOrder = a}); -data DescribeEvaluationsResponse = DescribeEvaluationsResponse - { _derNextToken :: Maybe Text - , _derResults :: List "Results" Evaluation - } deriving (Eq, Read, Show) +-- | The maximum number of 'Evaluation' to include in the result. +deLimit :: Lens' DescribeEvaluations (Maybe Natural) +deLimit = lens _deLimit (\ s a -> s{_deLimit = a}) . mapping _Nat; --- | 'DescribeEvaluationsResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'derNextToken' @::@ 'Maybe' 'Text' --- --- * 'derResults' @::@ ['Evaluation'] +-- | The less than operator. The 'Evaluation' results will have +-- 'FilterVariable' values that are less than the value specified with +-- 'LT'. +deLT :: Lens' DescribeEvaluations (Maybe Text) +deLT = lens _deLT (\ s a -> s{_deLT = a}); + +-- | Use one of the following variable to filter a list of 'Evaluation' +-- objects: -- -describeEvaluationsResponse :: DescribeEvaluationsResponse -describeEvaluationsResponse = DescribeEvaluationsResponse - { _derResults = mempty - , _derNextToken = Nothing - } +-- - 'CreatedAt' - Sets the search criteria to the 'Evaluation' creation +-- date. +-- - 'Status' - Sets the search criteria to the 'Evaluation' status. +-- - 'Name' - Sets the search criteria to the contents of 'Evaluation' +-- ____ 'Name'. +-- - 'IAMUser' - Sets the search criteria to the user account that +-- invoked an 'Evaluation'. +-- - 'MLModelId' - Sets the search criteria to the 'MLModel' that was +-- evaluated. +-- - 'DataSourceId' - Sets the search criteria to the 'DataSource' used +-- in 'Evaluation'. +-- - 'DataUri' - Sets the search criteria to the data file(s) used in +-- 'Evaluation'. The URL can identify either a file or an Amazon Simple +-- Storage Solution (Amazon S3) bucket or directory. +deFilterVariable :: Lens' DescribeEvaluations (Maybe EvaluationFilterVariable) +deFilterVariable = lens _deFilterVariable (\ s a -> s{_deFilterVariable = a}); --- | The ID of the next page in the paginated results that indicates at least one --- more page follows. -derNextToken :: Lens' DescribeEvaluationsResponse (Maybe Text) -derNextToken = lens _derNextToken (\s a -> s { _derNextToken = a }) +-- | The less than or equal to operator. The 'Evaluation' results will have +-- 'FilterVariable' values that are less than or equal to the value +-- specified with 'LE'. +deLE :: Lens' DescribeEvaluations (Maybe Text) +deLE = lens _deLE (\ s a -> s{_deLE = a}); --- | A list of 'Evaluation' that meet the search criteria. -derResults :: Lens' DescribeEvaluationsResponse [Evaluation] -derResults = lens _derResults (\s a -> s { _derResults = a }) . _List +instance AWSPager DescribeEvaluations where + page rq rs + | stop (rs ^. desrsNextToken) = Nothing + | stop (rs ^. desrsResults) = Nothing + | otherwise = + Just $ rq & deNextToken .~ rs ^. desrsNextToken +instance AWSRequest DescribeEvaluations where + type Sv DescribeEvaluations = MachineLearning + type Rs DescribeEvaluations = + DescribeEvaluationsResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + DescribeEvaluationsResponse' <$> + (x .?> "Results" .!@ mempty) <*> (x .?> "NextToken") + <*> (pure (fromEnum s))) + +instance ToHeaders DescribeEvaluations where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.DescribeEvaluations" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) + +instance ToJSON DescribeEvaluations where + toJSON DescribeEvaluations'{..} + = object + ["EQ" .= _deEQ, "GE" .= _deGE, "Prefix" .= _dePrefix, + "GT" .= _deGT, "NE" .= _deNE, + "NextToken" .= _deNextToken, + "SortOrder" .= _deSortOrder, "Limit" .= _deLimit, + "LT" .= _deLT, "FilterVariable" .= _deFilterVariable, + "LE" .= _deLE] + instance ToPath DescribeEvaluations where - toPath = const "/" + toPath = const "/" instance ToQuery DescribeEvaluations where - toQuery = const mempty - -instance ToHeaders DescribeEvaluations + toQuery = const mempty -instance ToJSON DescribeEvaluations where - toJSON DescribeEvaluations{..} = object - [ "FilterVariable" .= _deFilterVariable - , "EQ" .= _deEQ - , "GT" .= _deGT - , "LT" .= _deLT - , "GE" .= _deGE - , "LE" .= _deLE - , "NE" .= _deNE - , "Prefix" .= _dePrefix - , "SortOrder" .= _deSortOrder - , "NextToken" .= _deNextToken - , "Limit" .= _deLimit - ] +-- | Represents the query results from a DescribeEvaluations operation. The +-- content is essentially a list of 'Evaluation'. +-- +-- /See:/ 'describeEvaluationsResponse' smart constructor. +data DescribeEvaluationsResponse = DescribeEvaluationsResponse' + { _desrsResults :: !(Maybe [Evaluation]) + , _desrsNextToken :: !(Maybe Text) + , _desrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest DescribeEvaluations where - type Sv DescribeEvaluations = MachineLearning - type Rs DescribeEvaluations = DescribeEvaluationsResponse +-- | Creates a value of 'DescribeEvaluationsResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'desrsResults' +-- +-- * 'desrsNextToken' +-- +-- * 'desrsStatus' +describeEvaluationsResponse + :: Int -- ^ 'desrsStatus' + -> DescribeEvaluationsResponse +describeEvaluationsResponse pStatus_ = + DescribeEvaluationsResponse' + { _desrsResults = Nothing + , _desrsNextToken = Nothing + , _desrsStatus = pStatus_ + } - request = post "DescribeEvaluations" - response = jsonResponse +-- | A list of Evaluation that meet the search criteria. +desrsResults :: Lens' DescribeEvaluationsResponse [Evaluation] +desrsResults = lens _desrsResults (\ s a -> s{_desrsResults = a}) . _Default . _Coerce; -instance FromJSON DescribeEvaluationsResponse where - parseJSON = withObject "DescribeEvaluationsResponse" $ \o -> DescribeEvaluationsResponse - <$> o .:? "NextToken" - <*> o .:? "Results" .!= mempty +-- | The ID of the next page in the paginated results that indicates at least +-- one more page follows. +desrsNextToken :: Lens' DescribeEvaluationsResponse (Maybe Text) +desrsNextToken = lens _desrsNextToken (\ s a -> s{_desrsNextToken = a}); -instance AWSPager DescribeEvaluations where - page rq rs - | stop (rs ^. derNextToken) = Nothing - | otherwise = (\x -> rq & deNextToken ?~ x) - <$> (rs ^. derNextToken) +-- | The response status code. +desrsStatus :: Lens' DescribeEvaluationsResponse Int +desrsStatus = lens _desrsStatus (\ s a -> s{_desrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/DescribeMLModels.hs b/gen/Network/AWS/MachineLearning/DescribeMLModels.hs --- a/gen/Network/AWS/MachineLearning/DescribeMLModels.hs +++ b/gen/Network/AWS/MachineLearning/DescribeMLModels.hs @@ -1,258 +1,293 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.DescribeMLModels --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Returns a list of 'MLModel' that match the search criteria in the request. +-- Returns a list of 'MLModel' that match the search criteria in the +-- request. -- --- +-- /See:/ for DescribeMLModels. +-- +-- This operation returns paginated results. module Network.AWS.MachineLearning.DescribeMLModels ( - -- * Request - DescribeMLModels - -- ** Request constructor - , describeMLModels - -- ** Request lenses + -- * Creating a Request + describeMLModels + , DescribeMLModels + -- * Request Lenses , dmlmEQ - , dmlmFilterVariable , dmlmGE + , dmlmPrefix , dmlmGT - , dmlmLE - , dmlmLT - , dmlmLimit , dmlmNE , dmlmNextToken - , dmlmPrefix , dmlmSortOrder + , dmlmLimit + , dmlmLT + , dmlmFilterVariable + , dmlmLE - -- * Response - , DescribeMLModelsResponse - -- ** Response constructor + -- * Destructuring the Response , describeMLModelsResponse - -- ** Response lenses - , dmlmrNextToken - , dmlmrResults + , DescribeMLModelsResponse + -- * Response Lenses + , dmlmsrsResults + , dmlmsrsNextToken + , dmlmsrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Pager +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data DescribeMLModels = DescribeMLModels - { _dmlmEQ :: Maybe Text - , _dmlmFilterVariable :: Maybe MLModelFilterVariable - , _dmlmGE :: Maybe Text - , _dmlmGT :: Maybe Text - , _dmlmLE :: Maybe Text - , _dmlmLT :: Maybe Text - , _dmlmLimit :: Maybe Nat - , _dmlmNE :: Maybe Text - , _dmlmNextToken :: Maybe Text - , _dmlmPrefix :: Maybe Text - , _dmlmSortOrder :: Maybe SortOrder - } deriving (Eq, Read, Show) +-- | /See:/ 'describeMLModels' smart constructor. +data DescribeMLModels = DescribeMLModels' + { _dmlmEQ :: !(Maybe Text) + , _dmlmGE :: !(Maybe Text) + , _dmlmPrefix :: !(Maybe Text) + , _dmlmGT :: !(Maybe Text) + , _dmlmNE :: !(Maybe Text) + , _dmlmNextToken :: !(Maybe Text) + , _dmlmSortOrder :: !(Maybe SortOrder) + , _dmlmLimit :: !(Maybe Nat) + , _dmlmLT :: !(Maybe Text) + , _dmlmFilterVariable :: !(Maybe MLModelFilterVariable) + , _dmlmLE :: !(Maybe Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'DescribeMLModels' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'DescribeMLModels' with the minimum fields required to make a request. -- --- * 'dmlmEQ' @::@ 'Maybe' 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'dmlmFilterVariable' @::@ 'Maybe' 'MLModelFilterVariable' +-- * 'dmlmEQ' -- --- * 'dmlmGE' @::@ 'Maybe' 'Text' +-- * 'dmlmGE' -- --- * 'dmlmGT' @::@ 'Maybe' 'Text' +-- * 'dmlmPrefix' -- --- * 'dmlmLE' @::@ 'Maybe' 'Text' +-- * 'dmlmGT' -- --- * 'dmlmLT' @::@ 'Maybe' 'Text' +-- * 'dmlmNE' -- --- * 'dmlmLimit' @::@ 'Maybe' 'Natural' +-- * 'dmlmNextToken' -- --- * 'dmlmNE' @::@ 'Maybe' 'Text' +-- * 'dmlmSortOrder' -- --- * 'dmlmNextToken' @::@ 'Maybe' 'Text' +-- * 'dmlmLimit' -- --- * 'dmlmPrefix' @::@ 'Maybe' 'Text' +-- * 'dmlmLT' -- --- * 'dmlmSortOrder' @::@ 'Maybe' 'SortOrder' +-- * 'dmlmFilterVariable' -- -describeMLModels :: DescribeMLModels -describeMLModels = DescribeMLModels - { _dmlmFilterVariable = Nothing - , _dmlmEQ = Nothing - , _dmlmGT = Nothing - , _dmlmLT = Nothing - , _dmlmGE = Nothing - , _dmlmLE = Nothing - , _dmlmNE = Nothing - , _dmlmPrefix = Nothing - , _dmlmSortOrder = Nothing - , _dmlmNextToken = Nothing - , _dmlmLimit = Nothing +-- * 'dmlmLE' +describeMLModels + :: DescribeMLModels +describeMLModels = + DescribeMLModels' + { _dmlmEQ = Nothing + , _dmlmGE = Nothing + , _dmlmPrefix = Nothing + , _dmlmGT = Nothing + , _dmlmNE = Nothing + , _dmlmNextToken = Nothing + , _dmlmSortOrder = Nothing + , _dmlmLimit = Nothing + , _dmlmLT = Nothing + , _dmlmFilterVariable = Nothing + , _dmlmLE = Nothing } --- | The equal to operator. The 'MLModel' results will have 'FilterVariable' values --- that exactly match the value specified with 'EQ'. +-- | The equal to operator. The 'MLModel' results will have 'FilterVariable' +-- values that exactly match the value specified with 'EQ'. dmlmEQ :: Lens' DescribeMLModels (Maybe Text) -dmlmEQ = lens _dmlmEQ (\s a -> s { _dmlmEQ = a }) - --- | Use one of the following variables to filter a list of 'MLModel': --- --- 'CreatedAt' - Sets the search criteria to 'MLModel' creation date. 'Status' - --- Sets the search criteria to 'MLModel' status. 'Name' - Sets the search criteria --- to the contents of 'MLModel' 'Name'. 'IAMUser' - Sets the search criteria to the --- user account that invoked the 'MLModel' creation. 'TrainingDataSourceId' - Sets --- the search criteria to the 'DataSource' used to train one or more 'MLModel'. 'RealtimeEndpointStatus' - Sets the search criteria to the 'MLModel' real-time endpoint status. 'MLModelType' - Sets the search criteria to 'MLModel' type: binary, regression, or --- multi-class. 'Algorithm' - Sets the search criteria to the algorithm that the 'MLModel' uses. 'TrainingDataURI' - Sets the search criteria to the data file(s) used --- in training a 'MLModel'. The URL can identify either a file or an Amazon Simple --- Storage Service (Amazon S3) bucket or directory. -dmlmFilterVariable :: Lens' DescribeMLModels (Maybe MLModelFilterVariable) -dmlmFilterVariable = - lens _dmlmFilterVariable (\s a -> s { _dmlmFilterVariable = a }) +dmlmEQ = lens _dmlmEQ (\ s a -> s{_dmlmEQ = a}); --- | The greater than or equal to operator. The 'MLModel' results will have 'FilterVariable' values that are greater than or equal to the value specified with 'GE'. +-- | The greater than or equal to operator. The 'MLModel' results will have +-- 'FilterVariable' values that are greater than or equal to the value +-- specified with 'GE'. dmlmGE :: Lens' DescribeMLModels (Maybe Text) -dmlmGE = lens _dmlmGE (\s a -> s { _dmlmGE = a }) - --- | The greater than operator. The 'MLModel' results will have 'FilterVariable' --- values that are greater than the value specified with 'GT'. -dmlmGT :: Lens' DescribeMLModels (Maybe Text) -dmlmGT = lens _dmlmGT (\s a -> s { _dmlmGT = a }) - --- | The less than or equal to operator. The 'MLModel' results will have 'FilterVariable' values that are less than or equal to the value specified with 'LE'. -dmlmLE :: Lens' DescribeMLModels (Maybe Text) -dmlmLE = lens _dmlmLE (\s a -> s { _dmlmLE = a }) +dmlmGE = lens _dmlmGE (\ s a -> s{_dmlmGE = a}); --- | The less than operator. The 'MLModel' results will have 'FilterVariable' values --- that are less than the value specified with 'LT'. -dmlmLT :: Lens' DescribeMLModels (Maybe Text) -dmlmLT = lens _dmlmLT (\s a -> s { _dmlmLT = a }) +-- | A string that is found at the beginning of a variable, such as 'Name' or +-- 'Id'. +-- +-- For example, an 'MLModel' could have the 'Name' +-- '2014-09-09-HolidayGiftMailer'. To search for this 'MLModel', select +-- 'Name' for the 'FilterVariable' and any of the following strings for the +-- 'Prefix': +-- +-- - 2014-09 +-- +-- - 2014-09-09 +-- +-- - 2014-09-09-Holiday +-- +dmlmPrefix :: Lens' DescribeMLModels (Maybe Text) +dmlmPrefix = lens _dmlmPrefix (\ s a -> s{_dmlmPrefix = a}); --- | The number of pages of information to include in the result. The range of --- acceptable values is 1 through 100. The default value is 100. -dmlmLimit :: Lens' DescribeMLModels (Maybe Natural) -dmlmLimit = lens _dmlmLimit (\s a -> s { _dmlmLimit = a }) . mapping _Nat +-- | The greater than operator. The 'MLModel' results will have +-- 'FilterVariable' values that are greater than the value specified with +-- 'GT'. +dmlmGT :: Lens' DescribeMLModels (Maybe Text) +dmlmGT = lens _dmlmGT (\ s a -> s{_dmlmGT = a}); --- | The not equal to operator. The 'MLModel' results will have 'FilterVariable' --- values not equal to the value specified with 'NE'. +-- | The not equal to operator. The 'MLModel' results will have +-- 'FilterVariable' values not equal to the value specified with 'NE'. dmlmNE :: Lens' DescribeMLModels (Maybe Text) -dmlmNE = lens _dmlmNE (\s a -> s { _dmlmNE = a }) +dmlmNE = lens _dmlmNE (\ s a -> s{_dmlmNE = a}); -- | The ID of the page in the paginated results. dmlmNextToken :: Lens' DescribeMLModels (Maybe Text) -dmlmNextToken = lens _dmlmNextToken (\s a -> s { _dmlmNextToken = a }) +dmlmNextToken = lens _dmlmNextToken (\ s a -> s{_dmlmNextToken = a}); --- | A string that is found at the beginning of a variable, such as 'Name' or 'Id'. --- --- For example, an 'MLModel' could have the 'Name' '2014-09-09-HolidayGiftMailer'. To --- search for this 'MLModel', select 'Name' for the 'FilterVariable' and any of the --- following strings for the 'Prefix': --- --- 2014-09 --- --- 2014-09-09 --- --- 2014-09-09-Holiday --- +-- | A two-value parameter that determines the sequence of the resulting list +-- of 'MLModel'. -- -dmlmPrefix :: Lens' DescribeMLModels (Maybe Text) -dmlmPrefix = lens _dmlmPrefix (\s a -> s { _dmlmPrefix = a }) - --- | A two-value parameter that determines the sequence of the resulting list of 'MLModel'. +-- - 'asc' - Arranges the list in ascending order (A-Z, 0-9). +-- - 'dsc' - Arranges the list in descending order (Z-A, 9-0). -- --- 'asc' - Arranges the list in ascending order (A-Z, 0-9). 'dsc' - Arranges the --- list in descending order (Z-A, 9-0). Results are sorted by 'FilterVariable'. +-- Results are sorted by 'FilterVariable'. dmlmSortOrder :: Lens' DescribeMLModels (Maybe SortOrder) -dmlmSortOrder = lens _dmlmSortOrder (\s a -> s { _dmlmSortOrder = a }) +dmlmSortOrder = lens _dmlmSortOrder (\ s a -> s{_dmlmSortOrder = a}); -data DescribeMLModelsResponse = DescribeMLModelsResponse - { _dmlmrNextToken :: Maybe Text - , _dmlmrResults :: List "Results" MLModel - } deriving (Eq, Read, Show) +-- | The number of pages of information to include in the result. The range +-- of acceptable values is 1 through 100. The default value is 100. +dmlmLimit :: Lens' DescribeMLModels (Maybe Natural) +dmlmLimit = lens _dmlmLimit (\ s a -> s{_dmlmLimit = a}) . mapping _Nat; --- | 'DescribeMLModelsResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'dmlmrNextToken' @::@ 'Maybe' 'Text' --- --- * 'dmlmrResults' @::@ ['MLModel'] +-- | The less than operator. The 'MLModel' results will have 'FilterVariable' +-- values that are less than the value specified with 'LT'. +dmlmLT :: Lens' DescribeMLModels (Maybe Text) +dmlmLT = lens _dmlmLT (\ s a -> s{_dmlmLT = a}); + +-- | Use one of the following variables to filter a list of 'MLModel': -- -describeMLModelsResponse :: DescribeMLModelsResponse -describeMLModelsResponse = DescribeMLModelsResponse - { _dmlmrResults = mempty - , _dmlmrNextToken = Nothing - } +-- - 'CreatedAt' - Sets the search criteria to 'MLModel' creation date. +-- - 'Status' - Sets the search criteria to 'MLModel' status. +-- - 'Name' - Sets the search criteria to the contents of 'MLModel' ____ +-- 'Name'. +-- - 'IAMUser' - Sets the search criteria to the user account that +-- invoked the 'MLModel' creation. +-- - 'TrainingDataSourceId' - Sets the search criteria to the +-- 'DataSource' used to train one or more 'MLModel'. +-- - 'RealtimeEndpointStatus' - Sets the search criteria to the 'MLModel' +-- real-time endpoint status. +-- - 'MLModelType' - Sets the search criteria to 'MLModel' type: binary, +-- regression, or multi-class. +-- - 'Algorithm' - Sets the search criteria to the algorithm that the +-- 'MLModel' uses. +-- - 'TrainingDataURI' - Sets the search criteria to the data file(s) +-- used in training a 'MLModel'. The URL can identify either a file or +-- an Amazon Simple Storage Service (Amazon S3) bucket or directory. +dmlmFilterVariable :: Lens' DescribeMLModels (Maybe MLModelFilterVariable) +dmlmFilterVariable = lens _dmlmFilterVariable (\ s a -> s{_dmlmFilterVariable = a}); --- | The ID of the next page in the paginated results that indicates at least one --- more page follows. -dmlmrNextToken :: Lens' DescribeMLModelsResponse (Maybe Text) -dmlmrNextToken = lens _dmlmrNextToken (\s a -> s { _dmlmrNextToken = a }) +-- | The less than or equal to operator. The 'MLModel' results will have +-- 'FilterVariable' values that are less than or equal to the value +-- specified with 'LE'. +dmlmLE :: Lens' DescribeMLModels (Maybe Text) +dmlmLE = lens _dmlmLE (\ s a -> s{_dmlmLE = a}); --- | A list of 'MLModel' that meet the search criteria. -dmlmrResults :: Lens' DescribeMLModelsResponse [MLModel] -dmlmrResults = lens _dmlmrResults (\s a -> s { _dmlmrResults = a }) . _List +instance AWSPager DescribeMLModels where + page rq rs + | stop (rs ^. dmlmsrsNextToken) = Nothing + | stop (rs ^. dmlmsrsResults) = Nothing + | otherwise = + Just $ rq & dmlmNextToken .~ rs ^. dmlmsrsNextToken +instance AWSRequest DescribeMLModels where + type Sv DescribeMLModels = MachineLearning + type Rs DescribeMLModels = DescribeMLModelsResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + DescribeMLModelsResponse' <$> + (x .?> "Results" .!@ mempty) <*> (x .?> "NextToken") + <*> (pure (fromEnum s))) + +instance ToHeaders DescribeMLModels where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.DescribeMLModels" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) + +instance ToJSON DescribeMLModels where + toJSON DescribeMLModels'{..} + = object + ["EQ" .= _dmlmEQ, "GE" .= _dmlmGE, + "Prefix" .= _dmlmPrefix, "GT" .= _dmlmGT, + "NE" .= _dmlmNE, "NextToken" .= _dmlmNextToken, + "SortOrder" .= _dmlmSortOrder, "Limit" .= _dmlmLimit, + "LT" .= _dmlmLT, + "FilterVariable" .= _dmlmFilterVariable, + "LE" .= _dmlmLE] + instance ToPath DescribeMLModels where - toPath = const "/" + toPath = const "/" instance ToQuery DescribeMLModels where - toQuery = const mempty - -instance ToHeaders DescribeMLModels + toQuery = const mempty -instance ToJSON DescribeMLModels where - toJSON DescribeMLModels{..} = object - [ "FilterVariable" .= _dmlmFilterVariable - , "EQ" .= _dmlmEQ - , "GT" .= _dmlmGT - , "LT" .= _dmlmLT - , "GE" .= _dmlmGE - , "LE" .= _dmlmLE - , "NE" .= _dmlmNE - , "Prefix" .= _dmlmPrefix - , "SortOrder" .= _dmlmSortOrder - , "NextToken" .= _dmlmNextToken - , "Limit" .= _dmlmLimit - ] +-- | Represents the output of a DescribeMLModels operation. The content is +-- essentially a list of 'MLModel'. +-- +-- /See:/ 'describeMLModelsResponse' smart constructor. +data DescribeMLModelsResponse = DescribeMLModelsResponse' + { _dmlmsrsResults :: !(Maybe [MLModel]) + , _dmlmsrsNextToken :: !(Maybe Text) + , _dmlmsrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest DescribeMLModels where - type Sv DescribeMLModels = MachineLearning - type Rs DescribeMLModels = DescribeMLModelsResponse +-- | Creates a value of 'DescribeMLModelsResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'dmlmsrsResults' +-- +-- * 'dmlmsrsNextToken' +-- +-- * 'dmlmsrsStatus' +describeMLModelsResponse + :: Int -- ^ 'dmlmsrsStatus' + -> DescribeMLModelsResponse +describeMLModelsResponse pStatus_ = + DescribeMLModelsResponse' + { _dmlmsrsResults = Nothing + , _dmlmsrsNextToken = Nothing + , _dmlmsrsStatus = pStatus_ + } - request = post "DescribeMLModels" - response = jsonResponse +-- | A list of MLModel that meet the search criteria. +dmlmsrsResults :: Lens' DescribeMLModelsResponse [MLModel] +dmlmsrsResults = lens _dmlmsrsResults (\ s a -> s{_dmlmsrsResults = a}) . _Default . _Coerce; -instance FromJSON DescribeMLModelsResponse where - parseJSON = withObject "DescribeMLModelsResponse" $ \o -> DescribeMLModelsResponse - <$> o .:? "NextToken" - <*> o .:? "Results" .!= mempty +-- | The ID of the next page in the paginated results that indicates at least +-- one more page follows. +dmlmsrsNextToken :: Lens' DescribeMLModelsResponse (Maybe Text) +dmlmsrsNextToken = lens _dmlmsrsNextToken (\ s a -> s{_dmlmsrsNextToken = a}); -instance AWSPager DescribeMLModels where - page rq rs - | stop (rs ^. dmlmrNextToken) = Nothing - | otherwise = (\x -> rq & dmlmNextToken ?~ x) - <$> (rs ^. dmlmrNextToken) +-- | The response status code. +dmlmsrsStatus :: Lens' DescribeMLModelsResponse Int +dmlmsrsStatus = lens _dmlmsrsStatus (\ s a -> s{_dmlmsrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/GetBatchPrediction.hs b/gen/Network/AWS/MachineLearning/GetBatchPrediction.hs --- a/gen/Network/AWS/MachineLearning/GetBatchPrediction.hs +++ b/gen/Network/AWS/MachineLearning/GetBatchPrediction.hs @@ -1,247 +1,243 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.GetBatchPrediction --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Returns a 'BatchPrediction' that includes detailed metadata, status, and data --- file information for a 'Batch Prediction' request. +-- Returns a 'BatchPrediction' that includes detailed metadata, status, and +-- data file information for a 'Batch Prediction' request. -- --- +-- /See:/ for GetBatchPrediction. module Network.AWS.MachineLearning.GetBatchPrediction ( - -- * Request - GetBatchPrediction - -- ** Request constructor - , getBatchPrediction - -- ** Request lenses + -- * Creating a Request + getBatchPrediction + , GetBatchPrediction + -- * Request Lenses , gbpBatchPredictionId - -- * Response - , GetBatchPredictionResponse - -- ** Response constructor + -- * Destructuring the Response , getBatchPredictionResponse - -- ** Response lenses - , gbprBatchPredictionDataSourceId - , gbprBatchPredictionId - , gbprCreatedAt - , gbprCreatedByIamUser - , gbprInputDataLocationS3 - , gbprLastUpdatedAt - , gbprLogUri - , gbprMLModelId - , gbprMessage - , gbprName - , gbprOutputUri - , gbprStatus + , GetBatchPredictionResponse + -- * Response Lenses + , gbprsLastUpdatedAt + , gbprsCreatedAt + , gbprsInputDataLocationS3 + , gbprsMLModelId + , gbprsBatchPredictionDataSourceId + , gbprsBatchPredictionId + , gbprsName + , gbprsCreatedByIAMUser + , gbprsLogURI + , gbprsMessage + , gbprsOutputURI + , gbprsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -newtype GetBatchPrediction = GetBatchPrediction +-- | /See:/ 'getBatchPrediction' smart constructor. +newtype GetBatchPrediction = GetBatchPrediction' { _gbpBatchPredictionId :: Text - } deriving (Eq, Ord, Read, Show, Monoid, IsString) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'GetBatchPrediction' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'GetBatchPrediction' with the minimum fields required to make a request. -- --- * 'gbpBatchPredictionId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- -getBatchPrediction :: Text -- ^ 'gbpBatchPredictionId' - -> GetBatchPrediction -getBatchPrediction p1 = GetBatchPrediction - { _gbpBatchPredictionId = p1 +-- * 'gbpBatchPredictionId' +getBatchPrediction + :: Text -- ^ 'gbpBatchPredictionId' + -> GetBatchPrediction +getBatchPrediction pBatchPredictionId_ = + GetBatchPrediction' + { _gbpBatchPredictionId = pBatchPredictionId_ } -- | An ID assigned to the 'BatchPrediction' at creation. gbpBatchPredictionId :: Lens' GetBatchPrediction Text -gbpBatchPredictionId = - lens _gbpBatchPredictionId (\s a -> s { _gbpBatchPredictionId = a }) +gbpBatchPredictionId = lens _gbpBatchPredictionId (\ s a -> s{_gbpBatchPredictionId = a}); -data GetBatchPredictionResponse = GetBatchPredictionResponse - { _gbprBatchPredictionDataSourceId :: Maybe Text - , _gbprBatchPredictionId :: Maybe Text - , _gbprCreatedAt :: Maybe POSIX - , _gbprCreatedByIamUser :: Maybe Text - , _gbprInputDataLocationS3 :: Maybe Text - , _gbprLastUpdatedAt :: Maybe POSIX - , _gbprLogUri :: Maybe Text - , _gbprMLModelId :: Maybe Text - , _gbprMessage :: Maybe Text - , _gbprName :: Maybe Text - , _gbprOutputUri :: Maybe Text - , _gbprStatus :: Maybe EntityStatus - } deriving (Eq, Read, Show) +instance AWSRequest GetBatchPrediction where + type Sv GetBatchPrediction = MachineLearning + type Rs GetBatchPrediction = + GetBatchPredictionResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + GetBatchPredictionResponse' <$> + (x .?> "LastUpdatedAt") <*> (x .?> "CreatedAt") <*> + (x .?> "InputDataLocationS3") + <*> (x .?> "MLModelId") + <*> (x .?> "BatchPredictionDataSourceId") + <*> (x .?> "BatchPredictionId") + <*> (x .?> "Name") + <*> (x .?> "CreatedByIamUser") + <*> (x .?> "LogUri") + <*> (x .?> "Message") + <*> (x .?> "OutputUri") + <*> (pure (fromEnum s))) --- | 'GetBatchPredictionResponse' constructor. +instance ToHeaders GetBatchPrediction where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.GetBatchPrediction" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) + +instance ToJSON GetBatchPrediction where + toJSON GetBatchPrediction'{..} + = object + ["BatchPredictionId" .= _gbpBatchPredictionId] + +instance ToPath GetBatchPrediction where + toPath = const "/" + +instance ToQuery GetBatchPrediction where + toQuery = const mempty + +-- | Represents the output of a GetBatchPrediction operation and describes a +-- 'BatchPrediction'. -- --- The fields accessible through corresponding lenses are: +-- /See:/ 'getBatchPredictionResponse' smart constructor. +data GetBatchPredictionResponse = GetBatchPredictionResponse' + { _gbprsLastUpdatedAt :: !(Maybe POSIX) + , _gbprsCreatedAt :: !(Maybe POSIX) + , _gbprsInputDataLocationS3 :: !(Maybe Text) + , _gbprsMLModelId :: !(Maybe Text) + , _gbprsBatchPredictionDataSourceId :: !(Maybe Text) + , _gbprsBatchPredictionId :: !(Maybe Text) + , _gbprsName :: !(Maybe Text) + , _gbprsCreatedByIAMUser :: !(Maybe Text) + , _gbprsLogURI :: !(Maybe Text) + , _gbprsMessage :: !(Maybe Text) + , _gbprsOutputURI :: !(Maybe Text) + , _gbprsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'GetBatchPredictionResponse' with the minimum fields required to make a request. -- --- * 'gbprBatchPredictionDataSourceId' @::@ 'Maybe' 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'gbprBatchPredictionId' @::@ 'Maybe' 'Text' +-- * 'gbprsLastUpdatedAt' -- --- * 'gbprCreatedAt' @::@ 'Maybe' 'UTCTime' +-- * 'gbprsCreatedAt' -- --- * 'gbprCreatedByIamUser' @::@ 'Maybe' 'Text' +-- * 'gbprsInputDataLocationS3' -- --- * 'gbprInputDataLocationS3' @::@ 'Maybe' 'Text' +-- * 'gbprsMLModelId' -- --- * 'gbprLastUpdatedAt' @::@ 'Maybe' 'UTCTime' +-- * 'gbprsBatchPredictionDataSourceId' -- --- * 'gbprLogUri' @::@ 'Maybe' 'Text' +-- * 'gbprsBatchPredictionId' -- --- * 'gbprMLModelId' @::@ 'Maybe' 'Text' +-- * 'gbprsName' -- --- * 'gbprMessage' @::@ 'Maybe' 'Text' +-- * 'gbprsCreatedByIAMUser' -- --- * 'gbprName' @::@ 'Maybe' 'Text' +-- * 'gbprsLogURI' -- --- * 'gbprOutputUri' @::@ 'Maybe' 'Text' +-- * 'gbprsMessage' -- --- * 'gbprStatus' @::@ 'Maybe' 'EntityStatus' +-- * 'gbprsOutputURI' -- -getBatchPredictionResponse :: GetBatchPredictionResponse -getBatchPredictionResponse = GetBatchPredictionResponse - { _gbprBatchPredictionId = Nothing - , _gbprMLModelId = Nothing - , _gbprBatchPredictionDataSourceId = Nothing - , _gbprInputDataLocationS3 = Nothing - , _gbprCreatedByIamUser = Nothing - , _gbprCreatedAt = Nothing - , _gbprLastUpdatedAt = Nothing - , _gbprName = Nothing - , _gbprStatus = Nothing - , _gbprOutputUri = Nothing - , _gbprLogUri = Nothing - , _gbprMessage = Nothing +-- * 'gbprsStatus' +getBatchPredictionResponse + :: Int -- ^ 'gbprsStatus' + -> GetBatchPredictionResponse +getBatchPredictionResponse pStatus_ = + GetBatchPredictionResponse' + { _gbprsLastUpdatedAt = Nothing + , _gbprsCreatedAt = Nothing + , _gbprsInputDataLocationS3 = Nothing + , _gbprsMLModelId = Nothing + , _gbprsBatchPredictionDataSourceId = Nothing + , _gbprsBatchPredictionId = Nothing + , _gbprsName = Nothing + , _gbprsCreatedByIAMUser = Nothing + , _gbprsLogURI = Nothing + , _gbprsMessage = Nothing + , _gbprsOutputURI = Nothing + , _gbprsStatus = pStatus_ } --- | The ID of the 'DataSource' that was used to create the 'BatchPrediction'. -gbprBatchPredictionDataSourceId :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprBatchPredictionDataSourceId = - lens _gbprBatchPredictionDataSourceId - (\s a -> s { _gbprBatchPredictionDataSourceId = a }) - --- | An ID assigned to the 'BatchPrediction' at creation. This value should be --- identical to the value of the 'BatchPredictionID' in the request. -gbprBatchPredictionId :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprBatchPredictionId = - lens _gbprBatchPredictionId (\s a -> s { _gbprBatchPredictionId = a }) - --- | The time when the 'BatchPrediction' was created. The time is expressed in epoch --- time. -gbprCreatedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) -gbprCreatedAt = lens _gbprCreatedAt (\s a -> s { _gbprCreatedAt = a }) . mapping _Time - --- | The AWS user account that invoked the 'BatchPrediction'. The account type can --- be either an AWS root account or an AWS Identity and Access Management (IAM) --- user account. -gbprCreatedByIamUser :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprCreatedByIamUser = - lens _gbprCreatedByIamUser (\s a -> s { _gbprCreatedByIamUser = a }) +-- | The time of the most recent edit to 'BatchPrediction'. The time is +-- expressed in epoch time. +gbprsLastUpdatedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) +gbprsLastUpdatedAt = lens _gbprsLastUpdatedAt (\ s a -> s{_gbprsLastUpdatedAt = a}) . mapping _Time; --- | The location of the data file or directory in Amazon Simple Storage Service --- (Amazon S3). -gbprInputDataLocationS3 :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprInputDataLocationS3 = - lens _gbprInputDataLocationS3 (\s a -> s { _gbprInputDataLocationS3 = a }) +-- | The time when the 'BatchPrediction' was created. The time is expressed +-- in epoch time. +gbprsCreatedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) +gbprsCreatedAt = lens _gbprsCreatedAt (\ s a -> s{_gbprsCreatedAt = a}) . mapping _Time; --- | The time of the most recent edit to 'BatchPrediction'. The time is expressed in --- epoch time. -gbprLastUpdatedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) -gbprLastUpdatedAt = - lens _gbprLastUpdatedAt (\s a -> s { _gbprLastUpdatedAt = a }) - . mapping _Time +-- | The location of the data file or directory in Amazon Simple Storage +-- Service (Amazon S3). +gbprsInputDataLocationS3 :: Lens' GetBatchPredictionResponse (Maybe Text) +gbprsInputDataLocationS3 = lens _gbprsInputDataLocationS3 (\ s a -> s{_gbprsInputDataLocationS3 = a}); --- | A link to the file that contains logs of the 'CreateBatchPrediction' operation. -gbprLogUri :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprLogUri = lens _gbprLogUri (\s a -> s { _gbprLogUri = a }) +-- | The ID of the 'MLModel' that generated predictions for the +-- 'BatchPrediction' request. +gbprsMLModelId :: Lens' GetBatchPredictionResponse (Maybe Text) +gbprsMLModelId = lens _gbprsMLModelId (\ s a -> s{_gbprsMLModelId = a}); --- | The ID of the 'MLModel' that generated predictions for the 'BatchPrediction' --- request. -gbprMLModelId :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprMLModelId = lens _gbprMLModelId (\s a -> s { _gbprMLModelId = a }) +-- | The ID of the 'DataSource' that was used to create the +-- 'BatchPrediction'. +gbprsBatchPredictionDataSourceId :: Lens' GetBatchPredictionResponse (Maybe Text) +gbprsBatchPredictionDataSourceId = lens _gbprsBatchPredictionDataSourceId (\ s a -> s{_gbprsBatchPredictionDataSourceId = a}); --- | A description of the most recent details about processing the batch --- prediction request. -gbprMessage :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprMessage = lens _gbprMessage (\s a -> s { _gbprMessage = a }) +-- | An ID assigned to the 'BatchPrediction' at creation. This value should +-- be identical to the value of the 'BatchPredictionID' in the request. +gbprsBatchPredictionId :: Lens' GetBatchPredictionResponse (Maybe Text) +gbprsBatchPredictionId = lens _gbprsBatchPredictionId (\ s a -> s{_gbprsBatchPredictionId = a}); -- | A user-supplied name or description of the 'BatchPrediction'. -gbprName :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprName = lens _gbprName (\s a -> s { _gbprName = a }) - --- | The location of an Amazon S3 bucket or directory to receive the operation --- results. -gbprOutputUri :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprOutputUri = lens _gbprOutputUri (\s a -> s { _gbprOutputUri = a }) - --- | The status of the 'BatchPrediction', which can be one of the following values: --- --- 'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request to --- generate batch predictions. 'INPROGRESS' - The batch predictions are in --- progress. 'FAILED' - The request to perform a batch prediction did not run to --- completion. It is not usable. 'COMPLETED' - The batch prediction process --- completed successfully. 'DELETED' - The 'BatchPrediction' is marked as deleted. --- It is not usable. -gbprStatus :: Lens' GetBatchPredictionResponse (Maybe EntityStatus) -gbprStatus = lens _gbprStatus (\s a -> s { _gbprStatus = a }) - -instance ToPath GetBatchPrediction where - toPath = const "/" - -instance ToQuery GetBatchPrediction where - toQuery = const mempty +gbprsName :: Lens' GetBatchPredictionResponse (Maybe Text) +gbprsName = lens _gbprsName (\ s a -> s{_gbprsName = a}); -instance ToHeaders GetBatchPrediction +-- | The AWS user account that invoked the 'BatchPrediction'. The account +-- type can be either an AWS root account or an AWS Identity and Access +-- Management (IAM) user account. +gbprsCreatedByIAMUser :: Lens' GetBatchPredictionResponse (Maybe Text) +gbprsCreatedByIAMUser = lens _gbprsCreatedByIAMUser (\ s a -> s{_gbprsCreatedByIAMUser = a}); -instance ToJSON GetBatchPrediction where - toJSON GetBatchPrediction{..} = object - [ "BatchPredictionId" .= _gbpBatchPredictionId - ] +-- | A link to the file that contains logs of the CreateBatchPrediction +-- operation. +gbprsLogURI :: Lens' GetBatchPredictionResponse (Maybe Text) +gbprsLogURI = lens _gbprsLogURI (\ s a -> s{_gbprsLogURI = a}); -instance AWSRequest GetBatchPrediction where - type Sv GetBatchPrediction = MachineLearning - type Rs GetBatchPrediction = GetBatchPredictionResponse +-- | A description of the most recent details about processing the batch +-- prediction request. +gbprsMessage :: Lens' GetBatchPredictionResponse (Maybe Text) +gbprsMessage = lens _gbprsMessage (\ s a -> s{_gbprsMessage = a}); - request = post "GetBatchPrediction" - response = jsonResponse +-- | The location of an Amazon S3 bucket or directory to receive the +-- operation results. +gbprsOutputURI :: Lens' GetBatchPredictionResponse (Maybe Text) +gbprsOutputURI = lens _gbprsOutputURI (\ s a -> s{_gbprsOutputURI = a}); -instance FromJSON GetBatchPredictionResponse where - parseJSON = withObject "GetBatchPredictionResponse" $ \o -> GetBatchPredictionResponse - <$> o .:? "BatchPredictionDataSourceId" - <*> o .:? "BatchPredictionId" - <*> o .:? "CreatedAt" - <*> o .:? "CreatedByIamUser" - <*> o .:? "InputDataLocationS3" - <*> o .:? "LastUpdatedAt" - <*> o .:? "LogUri" - <*> o .:? "MLModelId" - <*> o .:? "Message" - <*> o .:? "Name" - <*> o .:? "OutputUri" - <*> o .:? "Status" +-- | The response status code. +gbprsStatus :: Lens' GetBatchPredictionResponse Int +gbprsStatus = lens _gbprsStatus (\ s a -> s{_gbprsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/GetDataSource.hs b/gen/Network/AWS/MachineLearning/GetDataSource.hs --- a/gen/Network/AWS/MachineLearning/GetDataSource.hs +++ b/gen/Network/AWS/MachineLearning/GetDataSource.hs @@ -1,314 +1,313 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.GetDataSource --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Returns a 'DataSource' that includes metadata and data file information, as --- well as the current status of the 'DataSource'. +-- Returns a 'DataSource' that includes metadata and data file information, +-- as well as the current status of the 'DataSource'. -- --- 'GetDataSource' provides results in normal or verbose format. The verbose --- format adds the schema description and the list of files pointed to by the --- DataSource to the normal format. +-- 'GetDataSource' provides results in normal or verbose format. The +-- verbose format adds the schema description and the list of files pointed +-- to by the DataSource to the normal format. -- --- +-- /See:/ for GetDataSource. module Network.AWS.MachineLearning.GetDataSource ( - -- * Request - GetDataSource - -- ** Request constructor - , getDataSource - -- ** Request lenses - , gdsDataSourceId + -- * Creating a Request + getDataSource + , GetDataSource + -- * Request Lenses , gdsVerbose + , gdsDataSourceId - -- * Response - , GetDataSourceResponse - -- ** Response constructor + -- * Destructuring the Response , getDataSourceResponse - -- ** Response lenses - , gdsrComputeStatistics - , gdsrCreatedAt - , gdsrCreatedByIamUser - , gdsrDataLocationS3 - , gdsrDataRearrangement - , gdsrDataSizeInBytes - , gdsrDataSourceId - , gdsrDataSourceSchema - , gdsrLastUpdatedAt - , gdsrLogUri - , gdsrMessage - , gdsrName - , gdsrNumberOfFiles - , gdsrRDSMetadata - , gdsrRedshiftMetadata - , gdsrRoleARN - , gdsrStatus + , GetDataSourceResponse + -- * Response Lenses + , gdsrsNumberOfFiles + , gdsrsLastUpdatedAt + , gdsrsCreatedAt + , gdsrsRDSMetadata + , gdsrsDataSourceId + , gdsrsDataSizeInBytes + , gdsrsDataSourceSchema + , gdsrsName + , gdsrsCreatedByIAMUser + , gdsrsLogURI + , gdsrsDataLocationS3 + , gdsrsComputeStatistics + , gdsrsMessage + , gdsrsRedshiftMetadata + , gdsrsRoleARN + , gdsrsDataRearrangement + , gdsrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data GetDataSource = GetDataSource - { _gdsDataSourceId :: Text - , _gdsVerbose :: Maybe Bool - } deriving (Eq, Ord, Read, Show) +-- | /See:/ 'getDataSource' smart constructor. +data GetDataSource = GetDataSource' + { _gdsVerbose :: !(Maybe Bool) + , _gdsDataSourceId :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'GetDataSource' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'GetDataSource' with the minimum fields required to make a request. -- --- * 'gdsDataSourceId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'gdsVerbose' @::@ 'Maybe' 'Bool' +-- * 'gdsVerbose' -- -getDataSource :: Text -- ^ 'gdsDataSourceId' - -> GetDataSource -getDataSource p1 = GetDataSource - { _gdsDataSourceId = p1 - , _gdsVerbose = Nothing +-- * 'gdsDataSourceId' +getDataSource + :: Text -- ^ 'gdsDataSourceId' + -> GetDataSource +getDataSource pDataSourceId_ = + GetDataSource' + { _gdsVerbose = Nothing + , _gdsDataSourceId = pDataSourceId_ } --- | The ID assigned to the 'DataSource' at creation. -gdsDataSourceId :: Lens' GetDataSource Text -gdsDataSourceId = lens _gdsDataSourceId (\s a -> s { _gdsDataSourceId = a }) - --- | Specifies whether the 'GetDataSource' operation should return 'DataSourceSchema'. +-- | Specifies whether the 'GetDataSource' operation should return +-- 'DataSourceSchema'. -- -- If true, 'DataSourceSchema' is returned. -- -- If false, 'DataSourceSchema' is not returned. gdsVerbose :: Lens' GetDataSource (Maybe Bool) -gdsVerbose = lens _gdsVerbose (\s a -> s { _gdsVerbose = a }) +gdsVerbose = lens _gdsVerbose (\ s a -> s{_gdsVerbose = a}); -data GetDataSourceResponse = GetDataSourceResponse - { _gdsrComputeStatistics :: Maybe Bool - , _gdsrCreatedAt :: Maybe POSIX - , _gdsrCreatedByIamUser :: Maybe Text - , _gdsrDataLocationS3 :: Maybe Text - , _gdsrDataRearrangement :: Maybe Text - , _gdsrDataSizeInBytes :: Maybe Integer - , _gdsrDataSourceId :: Maybe Text - , _gdsrDataSourceSchema :: Maybe Text - , _gdsrLastUpdatedAt :: Maybe POSIX - , _gdsrLogUri :: Maybe Text - , _gdsrMessage :: Maybe Text - , _gdsrName :: Maybe Text - , _gdsrNumberOfFiles :: Maybe Integer - , _gdsrRDSMetadata :: Maybe RDSMetadata - , _gdsrRedshiftMetadata :: Maybe RedshiftMetadata - , _gdsrRoleARN :: Maybe Text - , _gdsrStatus :: Maybe EntityStatus - } deriving (Eq, Read, Show) +-- | The ID assigned to the 'DataSource' at creation. +gdsDataSourceId :: Lens' GetDataSource Text +gdsDataSourceId = lens _gdsDataSourceId (\ s a -> s{_gdsDataSourceId = a}); --- | 'GetDataSourceResponse' constructor. +instance AWSRequest GetDataSource where + type Sv GetDataSource = MachineLearning + type Rs GetDataSource = GetDataSourceResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + GetDataSourceResponse' <$> + (x .?> "NumberOfFiles") <*> (x .?> "LastUpdatedAt") + <*> (x .?> "CreatedAt") + <*> (x .?> "RDSMetadata") + <*> (x .?> "DataSourceId") + <*> (x .?> "DataSizeInBytes") + <*> (x .?> "DataSourceSchema") + <*> (x .?> "Name") + <*> (x .?> "CreatedByIamUser") + <*> (x .?> "LogUri") + <*> (x .?> "DataLocationS3") + <*> (x .?> "ComputeStatistics") + <*> (x .?> "Message") + <*> (x .?> "RedshiftMetadata") + <*> (x .?> "RoleARN") + <*> (x .?> "DataRearrangement") + <*> (pure (fromEnum s))) + +instance ToHeaders GetDataSource where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.GetDataSource" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) + +instance ToJSON GetDataSource where + toJSON GetDataSource'{..} + = object + ["Verbose" .= _gdsVerbose, + "DataSourceId" .= _gdsDataSourceId] + +instance ToPath GetDataSource where + toPath = const "/" + +instance ToQuery GetDataSource where + toQuery = const mempty + +-- | Represents the output of a GetDataSource operation and describes a +-- 'DataSource'. -- --- The fields accessible through corresponding lenses are: +-- /See:/ 'getDataSourceResponse' smart constructor. +data GetDataSourceResponse = GetDataSourceResponse' + { _gdsrsNumberOfFiles :: !(Maybe Integer) + , _gdsrsLastUpdatedAt :: !(Maybe POSIX) + , _gdsrsCreatedAt :: !(Maybe POSIX) + , _gdsrsRDSMetadata :: !(Maybe RDSMetadata) + , _gdsrsDataSourceId :: !(Maybe Text) + , _gdsrsDataSizeInBytes :: !(Maybe Integer) + , _gdsrsDataSourceSchema :: !(Maybe Text) + , _gdsrsName :: !(Maybe Text) + , _gdsrsCreatedByIAMUser :: !(Maybe Text) + , _gdsrsLogURI :: !(Maybe Text) + , _gdsrsDataLocationS3 :: !(Maybe Text) + , _gdsrsComputeStatistics :: !(Maybe Bool) + , _gdsrsMessage :: !(Maybe Text) + , _gdsrsRedshiftMetadata :: !(Maybe RedshiftMetadata) + , _gdsrsRoleARN :: !(Maybe Text) + , _gdsrsDataRearrangement :: !(Maybe Text) + , _gdsrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'GetDataSourceResponse' with the minimum fields required to make a request. -- --- * 'gdsrComputeStatistics' @::@ 'Maybe' 'Bool' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'gdsrCreatedAt' @::@ 'Maybe' 'UTCTime' +-- * 'gdsrsNumberOfFiles' -- --- * 'gdsrCreatedByIamUser' @::@ 'Maybe' 'Text' +-- * 'gdsrsLastUpdatedAt' -- --- * 'gdsrDataLocationS3' @::@ 'Maybe' 'Text' +-- * 'gdsrsCreatedAt' -- --- * 'gdsrDataRearrangement' @::@ 'Maybe' 'Text' +-- * 'gdsrsRDSMetadata' -- --- * 'gdsrDataSizeInBytes' @::@ 'Maybe' 'Integer' +-- * 'gdsrsDataSourceId' -- --- * 'gdsrDataSourceId' @::@ 'Maybe' 'Text' +-- * 'gdsrsDataSizeInBytes' -- --- * 'gdsrDataSourceSchema' @::@ 'Maybe' 'Text' +-- * 'gdsrsDataSourceSchema' -- --- * 'gdsrLastUpdatedAt' @::@ 'Maybe' 'UTCTime' +-- * 'gdsrsName' -- --- * 'gdsrLogUri' @::@ 'Maybe' 'Text' +-- * 'gdsrsCreatedByIAMUser' -- --- * 'gdsrMessage' @::@ 'Maybe' 'Text' +-- * 'gdsrsLogURI' -- --- * 'gdsrName' @::@ 'Maybe' 'Text' +-- * 'gdsrsDataLocationS3' -- --- * 'gdsrNumberOfFiles' @::@ 'Maybe' 'Integer' +-- * 'gdsrsComputeStatistics' -- --- * 'gdsrRDSMetadata' @::@ 'Maybe' 'RDSMetadata' +-- * 'gdsrsMessage' -- --- * 'gdsrRedshiftMetadata' @::@ 'Maybe' 'RedshiftMetadata' +-- * 'gdsrsRedshiftMetadata' -- --- * 'gdsrRoleARN' @::@ 'Maybe' 'Text' +-- * 'gdsrsRoleARN' -- --- * 'gdsrStatus' @::@ 'Maybe' 'EntityStatus' +-- * 'gdsrsDataRearrangement' -- -getDataSourceResponse :: GetDataSourceResponse -getDataSourceResponse = GetDataSourceResponse - { _gdsrDataSourceId = Nothing - , _gdsrDataLocationS3 = Nothing - , _gdsrDataRearrangement = Nothing - , _gdsrCreatedByIamUser = Nothing - , _gdsrCreatedAt = Nothing - , _gdsrLastUpdatedAt = Nothing - , _gdsrDataSizeInBytes = Nothing - , _gdsrNumberOfFiles = Nothing - , _gdsrName = Nothing - , _gdsrStatus = Nothing - , _gdsrLogUri = Nothing - , _gdsrMessage = Nothing - , _gdsrRedshiftMetadata = Nothing - , _gdsrRDSMetadata = Nothing - , _gdsrRoleARN = Nothing - , _gdsrComputeStatistics = Nothing - , _gdsrDataSourceSchema = Nothing +-- * 'gdsrsStatus' +getDataSourceResponse + :: Int -- ^ 'gdsrsStatus' + -> GetDataSourceResponse +getDataSourceResponse pStatus_ = + GetDataSourceResponse' + { _gdsrsNumberOfFiles = Nothing + , _gdsrsLastUpdatedAt = Nothing + , _gdsrsCreatedAt = Nothing + , _gdsrsRDSMetadata = Nothing + , _gdsrsDataSourceId = Nothing + , _gdsrsDataSizeInBytes = Nothing + , _gdsrsDataSourceSchema = Nothing + , _gdsrsName = Nothing + , _gdsrsCreatedByIAMUser = Nothing + , _gdsrsLogURI = Nothing + , _gdsrsDataLocationS3 = Nothing + , _gdsrsComputeStatistics = Nothing + , _gdsrsMessage = Nothing + , _gdsrsRedshiftMetadata = Nothing + , _gdsrsRoleARN = Nothing + , _gdsrsDataRearrangement = Nothing + , _gdsrsStatus = pStatus_ } --- | The parameter is 'true' if statistics need to be generated from the --- observation data. -gdsrComputeStatistics :: Lens' GetDataSourceResponse (Maybe Bool) -gdsrComputeStatistics = - lens _gdsrComputeStatistics (\s a -> s { _gdsrComputeStatistics = a }) +-- | The number of data files referenced by the 'DataSource'. +gdsrsNumberOfFiles :: Lens' GetDataSourceResponse (Maybe Integer) +gdsrsNumberOfFiles = lens _gdsrsNumberOfFiles (\ s a -> s{_gdsrsNumberOfFiles = a}); --- | The time that the 'DataSource' was created. The time is expressed in epoch time. -gdsrCreatedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) -gdsrCreatedAt = lens _gdsrCreatedAt (\s a -> s { _gdsrCreatedAt = a }) . mapping _Time +-- | The time of the most recent edit to the 'DataSource'. The time is +-- expressed in epoch time. +gdsrsLastUpdatedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) +gdsrsLastUpdatedAt = lens _gdsrsLastUpdatedAt (\ s a -> s{_gdsrsLastUpdatedAt = a}) . mapping _Time; --- | The AWS user account from which the 'DataSource' was created. The account type --- can be either an AWS root account or an AWS Identity and Access Management --- (IAM) user account. -gdsrCreatedByIamUser :: Lens' GetDataSourceResponse (Maybe Text) -gdsrCreatedByIamUser = - lens _gdsrCreatedByIamUser (\s a -> s { _gdsrCreatedByIamUser = a }) +-- | The time that the 'DataSource' was created. The time is expressed in +-- epoch time. +gdsrsCreatedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) +gdsrsCreatedAt = lens _gdsrsCreatedAt (\ s a -> s{_gdsrsCreatedAt = a}) . mapping _Time; --- | The location of the data file or directory in Amazon Simple Storage Service --- (Amazon S3). -gdsrDataLocationS3 :: Lens' GetDataSourceResponse (Maybe Text) -gdsrDataLocationS3 = - lens _gdsrDataLocationS3 (\s a -> s { _gdsrDataLocationS3 = a }) +-- | Undocumented member. +gdsrsRDSMetadata :: Lens' GetDataSourceResponse (Maybe RDSMetadata) +gdsrsRDSMetadata = lens _gdsrsRDSMetadata (\ s a -> s{_gdsrsRDSMetadata = a}); --- | A JSON string that captures the splitting rearrangement requirement of the 'DataSource'. -gdsrDataRearrangement :: Lens' GetDataSourceResponse (Maybe Text) -gdsrDataRearrangement = - lens _gdsrDataRearrangement (\s a -> s { _gdsrDataRearrangement = a }) +-- | The ID assigned to the 'DataSource' at creation. This value should be +-- identical to the value of the 'DataSourceId' in the request. +gdsrsDataSourceId :: Lens' GetDataSourceResponse (Maybe Text) +gdsrsDataSourceId = lens _gdsrsDataSourceId (\ s a -> s{_gdsrsDataSourceId = a}); -- | The total size of observations in the data files. -gdsrDataSizeInBytes :: Lens' GetDataSourceResponse (Maybe Integer) -gdsrDataSizeInBytes = - lens _gdsrDataSizeInBytes (\s a -> s { _gdsrDataSizeInBytes = a }) - --- | The ID assigned to the 'DataSource' at creation. This value should be identical --- to the value of the 'DataSourceId' in the request. -gdsrDataSourceId :: Lens' GetDataSourceResponse (Maybe Text) -gdsrDataSourceId = lens _gdsrDataSourceId (\s a -> s { _gdsrDataSourceId = a }) +gdsrsDataSizeInBytes :: Lens' GetDataSourceResponse (Maybe Integer) +gdsrsDataSizeInBytes = lens _gdsrsDataSizeInBytes (\ s a -> s{_gdsrsDataSizeInBytes = a}); -- | The schema used by all of the data files of this 'DataSource'. -- --- Note This parameter is provided as part of the verbose format. +-- Note -- -gdsrDataSourceSchema :: Lens' GetDataSourceResponse (Maybe Text) -gdsrDataSourceSchema = - lens _gdsrDataSourceSchema (\s a -> s { _gdsrDataSourceSchema = a }) - --- | The time of the most recent edit to the 'DataSource'. The time is expressed in --- epoch time. -gdsrLastUpdatedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) -gdsrLastUpdatedAt = - lens _gdsrLastUpdatedAt (\s a -> s { _gdsrLastUpdatedAt = a }) - . mapping _Time - --- | A link to the file containining logs of either create 'DataSource' operation. -gdsrLogUri :: Lens' GetDataSourceResponse (Maybe Text) -gdsrLogUri = lens _gdsrLogUri (\s a -> s { _gdsrLogUri = a }) - --- | The description of the most recent details about creating the 'DataSource'. -gdsrMessage :: Lens' GetDataSourceResponse (Maybe Text) -gdsrMessage = lens _gdsrMessage (\s a -> s { _gdsrMessage = a }) +-- This parameter is provided as part of the verbose format. +gdsrsDataSourceSchema :: Lens' GetDataSourceResponse (Maybe Text) +gdsrsDataSourceSchema = lens _gdsrsDataSourceSchema (\ s a -> s{_gdsrsDataSourceSchema = a}); -- | A user-supplied name or description of the 'DataSource'. -gdsrName :: Lens' GetDataSourceResponse (Maybe Text) -gdsrName = lens _gdsrName (\s a -> s { _gdsrName = a }) - --- | The number of data files referenced by the 'DataSource'. -gdsrNumberOfFiles :: Lens' GetDataSourceResponse (Maybe Integer) -gdsrNumberOfFiles = - lens _gdsrNumberOfFiles (\s a -> s { _gdsrNumberOfFiles = a }) - -gdsrRDSMetadata :: Lens' GetDataSourceResponse (Maybe RDSMetadata) -gdsrRDSMetadata = lens _gdsrRDSMetadata (\s a -> s { _gdsrRDSMetadata = a }) - -gdsrRedshiftMetadata :: Lens' GetDataSourceResponse (Maybe RedshiftMetadata) -gdsrRedshiftMetadata = - lens _gdsrRedshiftMetadata (\s a -> s { _gdsrRedshiftMetadata = a }) +gdsrsName :: Lens' GetDataSourceResponse (Maybe Text) +gdsrsName = lens _gdsrsName (\ s a -> s{_gdsrsName = a}); -gdsrRoleARN :: Lens' GetDataSourceResponse (Maybe Text) -gdsrRoleARN = lens _gdsrRoleARN (\s a -> s { _gdsrRoleARN = a }) +-- | The AWS user account from which the 'DataSource' was created. The +-- account type can be either an AWS root account or an AWS Identity and +-- Access Management (IAM) user account. +gdsrsCreatedByIAMUser :: Lens' GetDataSourceResponse (Maybe Text) +gdsrsCreatedByIAMUser = lens _gdsrsCreatedByIAMUser (\ s a -> s{_gdsrsCreatedByIAMUser = a}); --- | The current status of the 'DataSource'. This element can have one of the --- following values: --- --- 'PENDING' - Amazon Machine Language (Amazon ML) submitted a request to --- create a 'DataSource'. 'INPROGRESS' - The creation process is underway. 'FAILED' --- - The request to create a 'DataSource' did not run to completion. It is not --- usable. 'COMPLETED' - The creation process completed successfully. 'DELETED' - --- The 'DataSource' is marked as deleted. It is not usable. -gdsrStatus :: Lens' GetDataSourceResponse (Maybe EntityStatus) -gdsrStatus = lens _gdsrStatus (\s a -> s { _gdsrStatus = a }) +-- | A link to the file containining logs of either create 'DataSource' +-- operation. +gdsrsLogURI :: Lens' GetDataSourceResponse (Maybe Text) +gdsrsLogURI = lens _gdsrsLogURI (\ s a -> s{_gdsrsLogURI = a}); -instance ToPath GetDataSource where - toPath = const "/" +-- | The location of the data file or directory in Amazon Simple Storage +-- Service (Amazon S3). +gdsrsDataLocationS3 :: Lens' GetDataSourceResponse (Maybe Text) +gdsrsDataLocationS3 = lens _gdsrsDataLocationS3 (\ s a -> s{_gdsrsDataLocationS3 = a}); -instance ToQuery GetDataSource where - toQuery = const mempty +-- | The parameter is 'true' if statistics need to be generated from the +-- observation data. +gdsrsComputeStatistics :: Lens' GetDataSourceResponse (Maybe Bool) +gdsrsComputeStatistics = lens _gdsrsComputeStatistics (\ s a -> s{_gdsrsComputeStatistics = a}); -instance ToHeaders GetDataSource +-- | The description of the most recent details about creating the +-- 'DataSource'. +gdsrsMessage :: Lens' GetDataSourceResponse (Maybe Text) +gdsrsMessage = lens _gdsrsMessage (\ s a -> s{_gdsrsMessage = a}); -instance ToJSON GetDataSource where - toJSON GetDataSource{..} = object - [ "DataSourceId" .= _gdsDataSourceId - , "Verbose" .= _gdsVerbose - ] +-- | Undocumented member. +gdsrsRedshiftMetadata :: Lens' GetDataSourceResponse (Maybe RedshiftMetadata) +gdsrsRedshiftMetadata = lens _gdsrsRedshiftMetadata (\ s a -> s{_gdsrsRedshiftMetadata = a}); -instance AWSRequest GetDataSource where - type Sv GetDataSource = MachineLearning - type Rs GetDataSource = GetDataSourceResponse +-- | Undocumented member. +gdsrsRoleARN :: Lens' GetDataSourceResponse (Maybe Text) +gdsrsRoleARN = lens _gdsrsRoleARN (\ s a -> s{_gdsrsRoleARN = a}); - request = post "GetDataSource" - response = jsonResponse +-- | A JSON string that captures the splitting rearrangement requirement of +-- the 'DataSource'. +gdsrsDataRearrangement :: Lens' GetDataSourceResponse (Maybe Text) +gdsrsDataRearrangement = lens _gdsrsDataRearrangement (\ s a -> s{_gdsrsDataRearrangement = a}); -instance FromJSON GetDataSourceResponse where - parseJSON = withObject "GetDataSourceResponse" $ \o -> GetDataSourceResponse - <$> o .:? "ComputeStatistics" - <*> o .:? "CreatedAt" - <*> o .:? "CreatedByIamUser" - <*> o .:? "DataLocationS3" - <*> o .:? "DataRearrangement" - <*> o .:? "DataSizeInBytes" - <*> o .:? "DataSourceId" - <*> o .:? "DataSourceSchema" - <*> o .:? "LastUpdatedAt" - <*> o .:? "LogUri" - <*> o .:? "Message" - <*> o .:? "Name" - <*> o .:? "NumberOfFiles" - <*> o .:? "RDSMetadata" - <*> o .:? "RedshiftMetadata" - <*> o .:? "RoleARN" - <*> o .:? "Status" +-- | The response status code. +gdsrsStatus :: Lens' GetDataSourceResponse Int +gdsrsStatus = lens _gdsrsStatus (\ s a -> s{_gdsrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/GetEvaluation.hs b/gen/Network/AWS/MachineLearning/GetEvaluation.hs --- a/gen/Network/AWS/MachineLearning/GetEvaluation.hs +++ b/gen/Network/AWS/MachineLearning/GetEvaluation.hs @@ -1,253 +1,253 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.GetEvaluation --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Returns an 'Evaluation' that includes metadata as well as the current status of --- the 'Evaluation'. +-- Returns an 'Evaluation' that includes metadata as well as the current +-- status of the 'Evaluation'. -- --- +-- /See:/ for GetEvaluation. module Network.AWS.MachineLearning.GetEvaluation ( - -- * Request - GetEvaluation - -- ** Request constructor - , getEvaluation - -- ** Request lenses + -- * Creating a Request + getEvaluation + , GetEvaluation + -- * Request Lenses , geEvaluationId - -- * Response - , GetEvaluationResponse - -- ** Response constructor + -- * Destructuring the Response , getEvaluationResponse - -- ** Response lenses - , gerCreatedAt - , gerCreatedByIamUser - , gerEvaluationDataSourceId - , gerEvaluationId - , gerInputDataLocationS3 - , gerLastUpdatedAt - , gerLogUri - , gerMLModelId - , gerMessage - , gerName - , gerPerformanceMetrics - , gerStatus + , GetEvaluationResponse + -- * Response Lenses + , gersPerformanceMetrics + , gersLastUpdatedAt + , gersCreatedAt + , gersInputDataLocationS3 + , gersMLModelId + , gersName + , gersCreatedByIAMUser + , gersLogURI + , gersMessage + , gersEvaluationId + , gersEvaluationDataSourceId + , gersStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -newtype GetEvaluation = GetEvaluation +-- | /See:/ 'getEvaluation' smart constructor. +newtype GetEvaluation = GetEvaluation' { _geEvaluationId :: Text - } deriving (Eq, Ord, Read, Show, Monoid, IsString) + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'GetEvaluation' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'GetEvaluation' with the minimum fields required to make a request. -- --- * 'geEvaluationId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- -getEvaluation :: Text -- ^ 'geEvaluationId' - -> GetEvaluation -getEvaluation p1 = GetEvaluation - { _geEvaluationId = p1 +-- * 'geEvaluationId' +getEvaluation + :: Text -- ^ 'geEvaluationId' + -> GetEvaluation +getEvaluation pEvaluationId_ = + GetEvaluation' + { _geEvaluationId = pEvaluationId_ } --- | The ID of the 'Evaluation' to retrieve. The evaluation of each 'MLModel' is --- recorded and cataloged. The ID provides the means to access the information. +-- | The ID of the 'Evaluation' to retrieve. The evaluation of each 'MLModel' +-- is recorded and cataloged. The ID provides the means to access the +-- information. geEvaluationId :: Lens' GetEvaluation Text -geEvaluationId = lens _geEvaluationId (\s a -> s { _geEvaluationId = a }) +geEvaluationId = lens _geEvaluationId (\ s a -> s{_geEvaluationId = a}); -data GetEvaluationResponse = GetEvaluationResponse - { _gerCreatedAt :: Maybe POSIX - , _gerCreatedByIamUser :: Maybe Text - , _gerEvaluationDataSourceId :: Maybe Text - , _gerEvaluationId :: Maybe Text - , _gerInputDataLocationS3 :: Maybe Text - , _gerLastUpdatedAt :: Maybe POSIX - , _gerLogUri :: Maybe Text - , _gerMLModelId :: Maybe Text - , _gerMessage :: Maybe Text - , _gerName :: Maybe Text - , _gerPerformanceMetrics :: Maybe PerformanceMetrics - , _gerStatus :: Maybe EntityStatus - } deriving (Eq, Read, Show) +instance AWSRequest GetEvaluation where + type Sv GetEvaluation = MachineLearning + type Rs GetEvaluation = GetEvaluationResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + GetEvaluationResponse' <$> + (x .?> "PerformanceMetrics") <*> + (x .?> "LastUpdatedAt") + <*> (x .?> "CreatedAt") + <*> (x .?> "InputDataLocationS3") + <*> (x .?> "MLModelId") + <*> (x .?> "Name") + <*> (x .?> "CreatedByIamUser") + <*> (x .?> "LogUri") + <*> (x .?> "Message") + <*> (x .?> "EvaluationId") + <*> (x .?> "EvaluationDataSourceId") + <*> (pure (fromEnum s))) --- | 'GetEvaluationResponse' constructor. +instance ToHeaders GetEvaluation where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.GetEvaluation" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) + +instance ToJSON GetEvaluation where + toJSON GetEvaluation'{..} + = object ["EvaluationId" .= _geEvaluationId] + +instance ToPath GetEvaluation where + toPath = const "/" + +instance ToQuery GetEvaluation where + toQuery = const mempty + +-- | Represents the output of a GetEvaluation operation and describes an +-- 'Evaluation'. -- --- The fields accessible through corresponding lenses are: +-- /See:/ 'getEvaluationResponse' smart constructor. +data GetEvaluationResponse = GetEvaluationResponse' + { _gersPerformanceMetrics :: !(Maybe PerformanceMetrics) + , _gersLastUpdatedAt :: !(Maybe POSIX) + , _gersCreatedAt :: !(Maybe POSIX) + , _gersInputDataLocationS3 :: !(Maybe Text) + , _gersMLModelId :: !(Maybe Text) + , _gersName :: !(Maybe Text) + , _gersCreatedByIAMUser :: !(Maybe Text) + , _gersLogURI :: !(Maybe Text) + , _gersMessage :: !(Maybe Text) + , _gersEvaluationId :: !(Maybe Text) + , _gersEvaluationDataSourceId :: !(Maybe Text) + , _gersStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'GetEvaluationResponse' with the minimum fields required to make a request. -- --- * 'gerCreatedAt' @::@ 'Maybe' 'UTCTime' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'gerCreatedByIamUser' @::@ 'Maybe' 'Text' +-- * 'gersPerformanceMetrics' -- --- * 'gerEvaluationDataSourceId' @::@ 'Maybe' 'Text' +-- * 'gersLastUpdatedAt' -- --- * 'gerEvaluationId' @::@ 'Maybe' 'Text' +-- * 'gersCreatedAt' -- --- * 'gerInputDataLocationS3' @::@ 'Maybe' 'Text' +-- * 'gersInputDataLocationS3' -- --- * 'gerLastUpdatedAt' @::@ 'Maybe' 'UTCTime' +-- * 'gersMLModelId' -- --- * 'gerLogUri' @::@ 'Maybe' 'Text' +-- * 'gersName' -- --- * 'gerMLModelId' @::@ 'Maybe' 'Text' +-- * 'gersCreatedByIAMUser' -- --- * 'gerMessage' @::@ 'Maybe' 'Text' +-- * 'gersLogURI' -- --- * 'gerName' @::@ 'Maybe' 'Text' +-- * 'gersMessage' -- --- * 'gerPerformanceMetrics' @::@ 'Maybe' 'PerformanceMetrics' +-- * 'gersEvaluationId' -- --- * 'gerStatus' @::@ 'Maybe' 'EntityStatus' +-- * 'gersEvaluationDataSourceId' -- -getEvaluationResponse :: GetEvaluationResponse -getEvaluationResponse = GetEvaluationResponse - { _gerEvaluationId = Nothing - , _gerMLModelId = Nothing - , _gerEvaluationDataSourceId = Nothing - , _gerInputDataLocationS3 = Nothing - , _gerCreatedByIamUser = Nothing - , _gerCreatedAt = Nothing - , _gerLastUpdatedAt = Nothing - , _gerName = Nothing - , _gerStatus = Nothing - , _gerPerformanceMetrics = Nothing - , _gerLogUri = Nothing - , _gerMessage = Nothing +-- * 'gersStatus' +getEvaluationResponse + :: Int -- ^ 'gersStatus' + -> GetEvaluationResponse +getEvaluationResponse pStatus_ = + GetEvaluationResponse' + { _gersPerformanceMetrics = Nothing + , _gersLastUpdatedAt = Nothing + , _gersCreatedAt = Nothing + , _gersInputDataLocationS3 = Nothing + , _gersMLModelId = Nothing + , _gersName = Nothing + , _gersCreatedByIAMUser = Nothing + , _gersLogURI = Nothing + , _gersMessage = Nothing + , _gersEvaluationId = Nothing + , _gersEvaluationDataSourceId = Nothing + , _gersStatus = pStatus_ } --- | The time that the 'Evaluation' was created. The time is expressed in epoch time. -gerCreatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) -gerCreatedAt = lens _gerCreatedAt (\s a -> s { _gerCreatedAt = a }) . mapping _Time - --- | The AWS user account that invoked the evaluation. The account type can be --- either an AWS root account or an AWS Identity and Access Management (IAM) --- user account. -gerCreatedByIamUser :: Lens' GetEvaluationResponse (Maybe Text) -gerCreatedByIamUser = - lens _gerCreatedByIamUser (\s a -> s { _gerCreatedByIamUser = a }) - --- | The 'DataSource' used for this evaluation. -gerEvaluationDataSourceId :: Lens' GetEvaluationResponse (Maybe Text) -gerEvaluationDataSourceId = - lens _gerEvaluationDataSourceId - (\s a -> s { _gerEvaluationDataSourceId = a }) - --- | The evaluation ID which is same as the 'EvaluationId' in the request. -gerEvaluationId :: Lens' GetEvaluationResponse (Maybe Text) -gerEvaluationId = lens _gerEvaluationId (\s a -> s { _gerEvaluationId = a }) - --- | The location of the data file or directory in Amazon Simple Storage Service --- (Amazon S3). -gerInputDataLocationS3 :: Lens' GetEvaluationResponse (Maybe Text) -gerInputDataLocationS3 = - lens _gerInputDataLocationS3 (\s a -> s { _gerInputDataLocationS3 = a }) +-- | Measurements of how well the 'MLModel' performed using observations +-- referenced by the 'DataSource'. One of the following metric is returned +-- based on the type of the 'MLModel': +-- +-- - BinaryAUC: A binary 'MLModel' uses the Area Under the Curve (AUC) +-- technique to measure performance. +-- +-- - RegressionRMSE: A regression 'MLModel' uses the Root Mean Square +-- Error (RMSE) technique to measure performance. RMSE measures the +-- difference between predicted and actual values for a single +-- variable. +-- +-- - MulticlassAvgFScore: A multiclass 'MLModel' uses the F1 score +-- technique to measure performance. +-- +-- For more information about performance metrics, please see the +-- . +gersPerformanceMetrics :: Lens' GetEvaluationResponse (Maybe PerformanceMetrics) +gersPerformanceMetrics = lens _gersPerformanceMetrics (\ s a -> s{_gersPerformanceMetrics = a}); -- | The time of the most recent edit to the 'BatchPrediction'. The time is -- expressed in epoch time. -gerLastUpdatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) -gerLastUpdatedAt = lens _gerLastUpdatedAt (\s a -> s { _gerLastUpdatedAt = a }) . mapping _Time +gersLastUpdatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) +gersLastUpdatedAt = lens _gersLastUpdatedAt (\ s a -> s{_gersLastUpdatedAt = a}) . mapping _Time; --- | A link to the file that contains logs of the 'CreateEvaluation' operation. -gerLogUri :: Lens' GetEvaluationResponse (Maybe Text) -gerLogUri = lens _gerLogUri (\s a -> s { _gerLogUri = a }) +-- | The time that the 'Evaluation' was created. The time is expressed in +-- epoch time. +gersCreatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) +gersCreatedAt = lens _gersCreatedAt (\ s a -> s{_gersCreatedAt = a}) . mapping _Time; --- | The ID of the 'MLModel' that was the focus of the evaluation. -gerMLModelId :: Lens' GetEvaluationResponse (Maybe Text) -gerMLModelId = lens _gerMLModelId (\s a -> s { _gerMLModelId = a }) +-- | The location of the data file or directory in Amazon Simple Storage +-- Service (Amazon S3). +gersInputDataLocationS3 :: Lens' GetEvaluationResponse (Maybe Text) +gersInputDataLocationS3 = lens _gersInputDataLocationS3 (\ s a -> s{_gersInputDataLocationS3 = a}); --- | A description of the most recent details about evaluating the 'MLModel'. -gerMessage :: Lens' GetEvaluationResponse (Maybe Text) -gerMessage = lens _gerMessage (\s a -> s { _gerMessage = a }) +-- | The ID of the 'MLModel' that was the focus of the evaluation. +gersMLModelId :: Lens' GetEvaluationResponse (Maybe Text) +gersMLModelId = lens _gersMLModelId (\ s a -> s{_gersMLModelId = a}); -- | A user-supplied name or description of the 'Evaluation'. -gerName :: Lens' GetEvaluationResponse (Maybe Text) -gerName = lens _gerName (\s a -> s { _gerName = a }) - --- | Measurements of how well the 'MLModel' performed using observations referenced --- by the 'DataSource'. One of the following metric is returned based on the type --- of the 'MLModel': --- --- BinaryAUC: A binary 'MLModel' uses the Area Under the Curve (AUC) technique --- to measure performance. --- --- RegressionRMSE: A regression 'MLModel' uses the Root Mean Square Error --- (RMSE) technique to measure performance. RMSE measures the difference between --- predicted and actual values for a single variable. --- --- MulticlassAvgFScore: A multiclass 'MLModel' uses the F1 score technique to --- measure performance. --- --- For more information about performance metrics, please see the . -gerPerformanceMetrics :: Lens' GetEvaluationResponse (Maybe PerformanceMetrics) -gerPerformanceMetrics = - lens _gerPerformanceMetrics (\s a -> s { _gerPerformanceMetrics = a }) - --- | The status of the evaluation. This element can have one of the following --- values: --- --- 'PENDING' - Amazon Machine Language (Amazon ML) submitted a request to --- evaluate an 'MLModel'. 'INPROGRESS' - The evaluation is underway. 'FAILED' - The --- request to evaluate an 'MLModel' did not run to completion. It is not usable. 'COMPLETED' - The evaluation process completed successfully. 'DELETED' - The 'Evaluation' --- is marked as deleted. It is not usable. -gerStatus :: Lens' GetEvaluationResponse (Maybe EntityStatus) -gerStatus = lens _gerStatus (\s a -> s { _gerStatus = a }) - -instance ToPath GetEvaluation where - toPath = const "/" +gersName :: Lens' GetEvaluationResponse (Maybe Text) +gersName = lens _gersName (\ s a -> s{_gersName = a}); -instance ToQuery GetEvaluation where - toQuery = const mempty +-- | The AWS user account that invoked the evaluation. The account type can +-- be either an AWS root account or an AWS Identity and Access Management +-- (IAM) user account. +gersCreatedByIAMUser :: Lens' GetEvaluationResponse (Maybe Text) +gersCreatedByIAMUser = lens _gersCreatedByIAMUser (\ s a -> s{_gersCreatedByIAMUser = a}); -instance ToHeaders GetEvaluation +-- | A link to the file that contains logs of the CreateEvaluation operation. +gersLogURI :: Lens' GetEvaluationResponse (Maybe Text) +gersLogURI = lens _gersLogURI (\ s a -> s{_gersLogURI = a}); -instance ToJSON GetEvaluation where - toJSON GetEvaluation{..} = object - [ "EvaluationId" .= _geEvaluationId - ] +-- | A description of the most recent details about evaluating the 'MLModel'. +gersMessage :: Lens' GetEvaluationResponse (Maybe Text) +gersMessage = lens _gersMessage (\ s a -> s{_gersMessage = a}); -instance AWSRequest GetEvaluation where - type Sv GetEvaluation = MachineLearning - type Rs GetEvaluation = GetEvaluationResponse +-- | The evaluation ID which is same as the 'EvaluationId' in the request. +gersEvaluationId :: Lens' GetEvaluationResponse (Maybe Text) +gersEvaluationId = lens _gersEvaluationId (\ s a -> s{_gersEvaluationId = a}); - request = post "GetEvaluation" - response = jsonResponse +-- | The 'DataSource' used for this evaluation. +gersEvaluationDataSourceId :: Lens' GetEvaluationResponse (Maybe Text) +gersEvaluationDataSourceId = lens _gersEvaluationDataSourceId (\ s a -> s{_gersEvaluationDataSourceId = a}); -instance FromJSON GetEvaluationResponse where - parseJSON = withObject "GetEvaluationResponse" $ \o -> GetEvaluationResponse - <$> o .:? "CreatedAt" - <*> o .:? "CreatedByIamUser" - <*> o .:? "EvaluationDataSourceId" - <*> o .:? "EvaluationId" - <*> o .:? "InputDataLocationS3" - <*> o .:? "LastUpdatedAt" - <*> o .:? "LogUri" - <*> o .:? "MLModelId" - <*> o .:? "Message" - <*> o .:? "Name" - <*> o .:? "PerformanceMetrics" - <*> o .:? "Status" +-- | The response status code. +gersStatus :: Lens' GetEvaluationResponse Int +gersStatus = lens _gersStatus (\ s a -> s{_gersStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/GetMLModel.hs b/gen/Network/AWS/MachineLearning/GetMLModel.hs --- a/gen/Network/AWS/MachineLearning/GetMLModel.hs +++ b/gen/Network/AWS/MachineLearning/GetMLModel.hs @@ -1,376 +1,373 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.GetMLModel --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Returns an 'MLModel' that includes detailed metadata, and data source +-- Returns an 'MLModel' that includes detailed metadata, and data source -- information as well as the current status of the 'MLModel'. -- -- 'GetMLModel' provides results in normal or verbose format. -- --- +-- /See:/ for GetMLModel. module Network.AWS.MachineLearning.GetMLModel ( - -- * Request - GetMLModel - -- ** Request constructor - , getMLModel - -- ** Request lenses - , gmlmMLModelId + -- * Creating a Request + getMLModel + , GetMLModel + -- * Request Lenses , gmlmVerbose + , gmlmMLModelId - -- * Response - , GetMLModelResponse - -- ** Response constructor + -- * Destructuring the Response , getMLModelResponse - -- ** Response lenses - , gmlmrCreatedAt - , gmlmrCreatedByIamUser - , gmlmrEndpointInfo - , gmlmrInputDataLocationS3 - , gmlmrLastUpdatedAt - , gmlmrLogUri - , gmlmrMLModelId - , gmlmrMLModelType - , gmlmrMessage - , gmlmrName - , gmlmrRecipe - , gmlmrSchema - , gmlmrScoreThreshold - , gmlmrScoreThresholdLastUpdatedAt - , gmlmrSizeInBytes - , gmlmrStatus - , gmlmrTrainingDataSourceId - , gmlmrTrainingParameters + , GetMLModelResponse + -- * Response Lenses + , gmlmrsTrainingParameters + , gmlmrsLastUpdatedAt + , gmlmrsCreatedAt + , gmlmrsScoreThresholdLastUpdatedAt + , gmlmrsRecipe + , gmlmrsInputDataLocationS3 + , gmlmrsSizeInBytes + , gmlmrsMLModelId + , gmlmrsSchema + , gmlmrsScoreThreshold + , gmlmrsName + , gmlmrsCreatedByIAMUser + , gmlmrsLogURI + , gmlmrsEndpointInfo + , gmlmrsTrainingDataSourceId + , gmlmrsMessage + , gmlmrsMLModelType + , gmlmrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data GetMLModel = GetMLModel - { _gmlmMLModelId :: Text - , _gmlmVerbose :: Maybe Bool - } deriving (Eq, Ord, Read, Show) +-- | /See:/ 'getMLModel' smart constructor. +data GetMLModel = GetMLModel' + { _gmlmVerbose :: !(Maybe Bool) + , _gmlmMLModelId :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'GetMLModel' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'GetMLModel' with the minimum fields required to make a request. -- --- * 'gmlmMLModelId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'gmlmVerbose' @::@ 'Maybe' 'Bool' +-- * 'gmlmVerbose' -- -getMLModel :: Text -- ^ 'gmlmMLModelId' - -> GetMLModel -getMLModel p1 = GetMLModel - { _gmlmMLModelId = p1 - , _gmlmVerbose = Nothing +-- * 'gmlmMLModelId' +getMLModel + :: Text -- ^ 'gmlmMLModelId' + -> GetMLModel +getMLModel pMLModelId_ = + GetMLModel' + { _gmlmVerbose = Nothing + , _gmlmMLModelId = pMLModelId_ } --- | The ID assigned to the 'MLModel' at creation. -gmlmMLModelId :: Lens' GetMLModel Text -gmlmMLModelId = lens _gmlmMLModelId (\s a -> s { _gmlmMLModelId = a }) - -- | Specifies whether the 'GetMLModel' operation should return 'Recipe'. -- -- If true, 'Recipe' is returned. -- -- If false, 'Recipe' is not returned. gmlmVerbose :: Lens' GetMLModel (Maybe Bool) -gmlmVerbose = lens _gmlmVerbose (\s a -> s { _gmlmVerbose = a }) +gmlmVerbose = lens _gmlmVerbose (\ s a -> s{_gmlmVerbose = a}); -data GetMLModelResponse = GetMLModelResponse - { _gmlmrCreatedAt :: Maybe POSIX - , _gmlmrCreatedByIamUser :: Maybe Text - , _gmlmrEndpointInfo :: Maybe RealtimeEndpointInfo - , _gmlmrInputDataLocationS3 :: Maybe Text - , _gmlmrLastUpdatedAt :: Maybe POSIX - , _gmlmrLogUri :: Maybe Text - , _gmlmrMLModelId :: Maybe Text - , _gmlmrMLModelType :: Maybe MLModelType - , _gmlmrMessage :: Maybe Text - , _gmlmrName :: Maybe Text - , _gmlmrRecipe :: Maybe Text - , _gmlmrSchema :: Maybe Text - , _gmlmrScoreThreshold :: Maybe Double - , _gmlmrScoreThresholdLastUpdatedAt :: Maybe POSIX - , _gmlmrSizeInBytes :: Maybe Integer - , _gmlmrStatus :: Maybe EntityStatus - , _gmlmrTrainingDataSourceId :: Maybe Text - , _gmlmrTrainingParameters :: Map Text Text - } deriving (Eq, Read, Show) +-- | The ID assigned to the 'MLModel' at creation. +gmlmMLModelId :: Lens' GetMLModel Text +gmlmMLModelId = lens _gmlmMLModelId (\ s a -> s{_gmlmMLModelId = a}); --- | 'GetMLModelResponse' constructor. +instance AWSRequest GetMLModel where + type Sv GetMLModel = MachineLearning + type Rs GetMLModel = GetMLModelResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + GetMLModelResponse' <$> + (x .?> "TrainingParameters" .!@ mempty) <*> + (x .?> "LastUpdatedAt") + <*> (x .?> "CreatedAt") + <*> (x .?> "ScoreThresholdLastUpdatedAt") + <*> (x .?> "Recipe") + <*> (x .?> "InputDataLocationS3") + <*> (x .?> "SizeInBytes") + <*> (x .?> "MLModelId") + <*> (x .?> "Schema") + <*> (x .?> "ScoreThreshold") + <*> (x .?> "Name") + <*> (x .?> "CreatedByIamUser") + <*> (x .?> "LogUri") + <*> (x .?> "EndpointInfo") + <*> (x .?> "TrainingDataSourceId") + <*> (x .?> "Message") + <*> (x .?> "MLModelType") + <*> (pure (fromEnum s))) + +instance ToHeaders GetMLModel where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.GetMLModel" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) + +instance ToJSON GetMLModel where + toJSON GetMLModel'{..} + = object + ["Verbose" .= _gmlmVerbose, + "MLModelId" .= _gmlmMLModelId] + +instance ToPath GetMLModel where + toPath = const "/" + +instance ToQuery GetMLModel where + toQuery = const mempty + +-- | Represents the output of a GetMLModel operation, and provides detailed +-- information about a 'MLModel'. -- --- The fields accessible through corresponding lenses are: +-- /See:/ 'getMLModelResponse' smart constructor. +data GetMLModelResponse = GetMLModelResponse' + { _gmlmrsTrainingParameters :: !(Maybe (Map Text Text)) + , _gmlmrsLastUpdatedAt :: !(Maybe POSIX) + , _gmlmrsCreatedAt :: !(Maybe POSIX) + , _gmlmrsScoreThresholdLastUpdatedAt :: !(Maybe POSIX) + , _gmlmrsRecipe :: !(Maybe Text) + , _gmlmrsInputDataLocationS3 :: !(Maybe Text) + , _gmlmrsSizeInBytes :: !(Maybe Integer) + , _gmlmrsMLModelId :: !(Maybe Text) + , _gmlmrsSchema :: !(Maybe Text) + , _gmlmrsScoreThreshold :: !(Maybe Double) + , _gmlmrsName :: !(Maybe Text) + , _gmlmrsCreatedByIAMUser :: !(Maybe Text) + , _gmlmrsLogURI :: !(Maybe Text) + , _gmlmrsEndpointInfo :: !(Maybe RealtimeEndpointInfo) + , _gmlmrsTrainingDataSourceId :: !(Maybe Text) + , _gmlmrsMessage :: !(Maybe Text) + , _gmlmrsMLModelType :: !(Maybe MLModelType) + , _gmlmrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'GetMLModelResponse' with the minimum fields required to make a request. -- --- * 'gmlmrCreatedAt' @::@ 'Maybe' 'UTCTime' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'gmlmrCreatedByIamUser' @::@ 'Maybe' 'Text' +-- * 'gmlmrsTrainingParameters' -- --- * 'gmlmrEndpointInfo' @::@ 'Maybe' 'RealtimeEndpointInfo' +-- * 'gmlmrsLastUpdatedAt' -- --- * 'gmlmrInputDataLocationS3' @::@ 'Maybe' 'Text' +-- * 'gmlmrsCreatedAt' -- --- * 'gmlmrLastUpdatedAt' @::@ 'Maybe' 'UTCTime' +-- * 'gmlmrsScoreThresholdLastUpdatedAt' -- --- * 'gmlmrLogUri' @::@ 'Maybe' 'Text' +-- * 'gmlmrsRecipe' -- --- * 'gmlmrMLModelId' @::@ 'Maybe' 'Text' +-- * 'gmlmrsInputDataLocationS3' -- --- * 'gmlmrMLModelType' @::@ 'Maybe' 'MLModelType' +-- * 'gmlmrsSizeInBytes' -- --- * 'gmlmrMessage' @::@ 'Maybe' 'Text' +-- * 'gmlmrsMLModelId' -- --- * 'gmlmrName' @::@ 'Maybe' 'Text' +-- * 'gmlmrsSchema' -- --- * 'gmlmrRecipe' @::@ 'Maybe' 'Text' +-- * 'gmlmrsScoreThreshold' -- --- * 'gmlmrSchema' @::@ 'Maybe' 'Text' +-- * 'gmlmrsName' -- --- * 'gmlmrScoreThreshold' @::@ 'Maybe' 'Double' +-- * 'gmlmrsCreatedByIAMUser' -- --- * 'gmlmrScoreThresholdLastUpdatedAt' @::@ 'Maybe' 'UTCTime' +-- * 'gmlmrsLogURI' -- --- * 'gmlmrSizeInBytes' @::@ 'Maybe' 'Integer' +-- * 'gmlmrsEndpointInfo' -- --- * 'gmlmrStatus' @::@ 'Maybe' 'EntityStatus' +-- * 'gmlmrsTrainingDataSourceId' -- --- * 'gmlmrTrainingDataSourceId' @::@ 'Maybe' 'Text' +-- * 'gmlmrsMessage' -- --- * 'gmlmrTrainingParameters' @::@ 'HashMap' 'Text' 'Text' +-- * 'gmlmrsMLModelType' -- -getMLModelResponse :: GetMLModelResponse -getMLModelResponse = GetMLModelResponse - { _gmlmrMLModelId = Nothing - , _gmlmrTrainingDataSourceId = Nothing - , _gmlmrCreatedByIamUser = Nothing - , _gmlmrCreatedAt = Nothing - , _gmlmrLastUpdatedAt = Nothing - , _gmlmrName = Nothing - , _gmlmrStatus = Nothing - , _gmlmrSizeInBytes = Nothing - , _gmlmrEndpointInfo = Nothing - , _gmlmrTrainingParameters = mempty - , _gmlmrInputDataLocationS3 = Nothing - , _gmlmrMLModelType = Nothing - , _gmlmrScoreThreshold = Nothing - , _gmlmrScoreThresholdLastUpdatedAt = Nothing - , _gmlmrLogUri = Nothing - , _gmlmrMessage = Nothing - , _gmlmrRecipe = Nothing - , _gmlmrSchema = Nothing +-- * 'gmlmrsStatus' +getMLModelResponse + :: Int -- ^ 'gmlmrsStatus' + -> GetMLModelResponse +getMLModelResponse pStatus_ = + GetMLModelResponse' + { _gmlmrsTrainingParameters = Nothing + , _gmlmrsLastUpdatedAt = Nothing + , _gmlmrsCreatedAt = Nothing + , _gmlmrsScoreThresholdLastUpdatedAt = Nothing + , _gmlmrsRecipe = Nothing + , _gmlmrsInputDataLocationS3 = Nothing + , _gmlmrsSizeInBytes = Nothing + , _gmlmrsMLModelId = Nothing + , _gmlmrsSchema = Nothing + , _gmlmrsScoreThreshold = Nothing + , _gmlmrsName = Nothing + , _gmlmrsCreatedByIAMUser = Nothing + , _gmlmrsLogURI = Nothing + , _gmlmrsEndpointInfo = Nothing + , _gmlmrsTrainingDataSourceId = Nothing + , _gmlmrsMessage = Nothing + , _gmlmrsMLModelType = Nothing + , _gmlmrsStatus = pStatus_ } --- | The time that the 'MLModel' was created. The time is expressed in epoch time. -gmlmrCreatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) -gmlmrCreatedAt = lens _gmlmrCreatedAt (\s a -> s { _gmlmrCreatedAt = a }) . mapping _Time - --- | The AWS user account from which the 'MLModel' was created. The account type can --- be either an AWS root account or an AWS Identity and Access Management (IAM) --- user account. -gmlmrCreatedByIamUser :: Lens' GetMLModelResponse (Maybe Text) -gmlmrCreatedByIamUser = - lens _gmlmrCreatedByIamUser (\s a -> s { _gmlmrCreatedByIamUser = a }) - --- | The current endpoint of the 'MLModel' -gmlmrEndpointInfo :: Lens' GetMLModelResponse (Maybe RealtimeEndpointInfo) -gmlmrEndpointInfo = - lens _gmlmrEndpointInfo (\s a -> s { _gmlmrEndpointInfo = a }) - --- | The location of the data file or directory in Amazon Simple Storage Service --- (Amazon S3). -gmlmrInputDataLocationS3 :: Lens' GetMLModelResponse (Maybe Text) -gmlmrInputDataLocationS3 = - lens _gmlmrInputDataLocationS3 - (\s a -> s { _gmlmrInputDataLocationS3 = a }) - --- | The time of the most recent edit to the 'MLModel'. The time is expressed in --- epoch time. -gmlmrLastUpdatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) -gmlmrLastUpdatedAt = - lens _gmlmrLastUpdatedAt (\s a -> s { _gmlmrLastUpdatedAt = a }) - . mapping _Time - --- | A link to the file that contains logs of the 'CreateMLModel' operation. -gmlmrLogUri :: Lens' GetMLModelResponse (Maybe Text) -gmlmrLogUri = lens _gmlmrLogUri (\s a -> s { _gmlmrLogUri = a }) - --- | The MLModel ID which is same as the 'MLModelId' in the request. -gmlmrMLModelId :: Lens' GetMLModelResponse (Maybe Text) -gmlmrMLModelId = lens _gmlmrMLModelId (\s a -> s { _gmlmrMLModelId = a }) - --- | Identifies the 'MLModel' category. The following are the available types: +-- | A list of the training parameters in the 'MLModel'. The list is +-- implemented as a map of key\/value pairs. -- --- REGRESSION -- Produces a numeric result. For example, "What listing price --- should a house have?" BINARY -- Produces one of two possible results. For --- example, "Is this an e-commerce website?" MULTICLASS -- Produces more than --- two possible results. For example, "Is this a HIGH, LOW or MEDIUM risk trade?" +-- The following is the current set of training parameters: -- -gmlmrMLModelType :: Lens' GetMLModelResponse (Maybe MLModelType) -gmlmrMLModelType = lens _gmlmrMLModelType (\s a -> s { _gmlmrMLModelType = a }) - --- | Description of the most recent details about accessing the 'MLModel'. -gmlmrMessage :: Lens' GetMLModelResponse (Maybe Text) -gmlmrMessage = lens _gmlmrMessage (\s a -> s { _gmlmrMessage = a }) - --- | A user-supplied name or description of the 'MLModel'. -gmlmrName :: Lens' GetMLModelResponse (Maybe Text) -gmlmrName = lens _gmlmrName (\s a -> s { _gmlmrName = a }) - --- | The recipe to use when training the 'MLModel'. The 'Recipe' provides detailed --- information about the observation data to use during training, as well as --- manipulations to perform on the observation data during training. +-- - 'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. +-- It controls overfitting the data by penalizing large coefficients. +-- This tends to drive coefficients to zero, resulting in a sparse +-- feature set. If you use this parameter, specify a small value, such +-- as 1.0E-04 or 1.0E-08. -- --- Note This parameter is provided as part of the verbose format. +-- The value is a double that ranges from 0 to MAX_DOUBLE. The default +-- is not to use L1 normalization. The parameter cannot be used when +-- 'L2' is specified. Use this parameter sparingly. -- -gmlmrRecipe :: Lens' GetMLModelResponse (Maybe Text) -gmlmrRecipe = lens _gmlmrRecipe (\s a -> s { _gmlmrRecipe = a }) - --- | The schema used by all of the data files referenced by the 'DataSource'. +-- - 'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. +-- It controls overfitting the data by penalizing large coefficients. +-- This tends to drive coefficients to small, nonzero values. If you +-- use this parameter, specify a small value, such as 1.0E-04 or +-- 1.0E-08. -- --- Note This parameter is provided as part of the verbose format. +-- The value is a double that ranges from 0 to MAX_DOUBLE. The default +-- is not to use L2 normalization. This parameter cannot be used when +-- 'L1' is specified. Use this parameter sparingly. -- -gmlmrSchema :: Lens' GetMLModelResponse (Maybe Text) -gmlmrSchema = lens _gmlmrSchema (\s a -> s { _gmlmrSchema = a }) - --- | The scoring threshold is used in binary classification 'MLModel's, and marks --- the boundary between a positive prediction and a negative prediction. +-- - 'sgd.maxPasses' - The number of times that the training process +-- traverses the observations to build the 'MLModel'. The value is an +-- integer that ranges from 1 to 10000. The default value is 10. -- --- Output values greater than or equal to the threshold receive a positive --- result from the MLModel, such as 'true'. Output values less than the threshold --- receive a negative response from the MLModel, such as 'false'. -gmlmrScoreThreshold :: Lens' GetMLModelResponse (Maybe Double) -gmlmrScoreThreshold = - lens _gmlmrScoreThreshold (\s a -> s { _gmlmrScoreThreshold = a }) +-- - 'sgd.maxMLModelSizeInBytes' - The maximum allowed size of the model. +-- Depending on the input data, the model size might affect +-- performance. +-- +-- The value is an integer that ranges from 100000 to 2147483648. The +-- default value is 33554432. +-- +gmlmrsTrainingParameters :: Lens' GetMLModelResponse (HashMap Text Text) +gmlmrsTrainingParameters = lens _gmlmrsTrainingParameters (\ s a -> s{_gmlmrsTrainingParameters = a}) . _Default . _Map; --- | The time of the most recent edit to the 'ScoreThreshold'. The time is expressed +-- | The time of the most recent edit to the 'MLModel'. The time is expressed -- in epoch time. -gmlmrScoreThresholdLastUpdatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) -gmlmrScoreThresholdLastUpdatedAt = - lens _gmlmrScoreThresholdLastUpdatedAt - (\s a -> s { _gmlmrScoreThresholdLastUpdatedAt = a }) - . mapping _Time - -gmlmrSizeInBytes :: Lens' GetMLModelResponse (Maybe Integer) -gmlmrSizeInBytes = lens _gmlmrSizeInBytes (\s a -> s { _gmlmrSizeInBytes = a }) +gmlmrsLastUpdatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) +gmlmrsLastUpdatedAt = lens _gmlmrsLastUpdatedAt (\ s a -> s{_gmlmrsLastUpdatedAt = a}) . mapping _Time; --- | The current status of the 'MLModel'. This element can have one of the following --- values: --- --- 'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request to --- describe a 'MLModel'. 'INPROGRESS' - The request is processing. 'FAILED' - The --- request did not run to completion. It is not usable. 'COMPLETED' - The request --- completed successfully. 'DELETED' - The 'MLModel' is marked as deleted. It is --- not usable. -gmlmrStatus :: Lens' GetMLModelResponse (Maybe EntityStatus) -gmlmrStatus = lens _gmlmrStatus (\s a -> s { _gmlmrStatus = a }) +-- | The time that the 'MLModel' was created. The time is expressed in epoch +-- time. +gmlmrsCreatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) +gmlmrsCreatedAt = lens _gmlmrsCreatedAt (\ s a -> s{_gmlmrsCreatedAt = a}) . mapping _Time; --- | The ID of the training 'DataSource'. -gmlmrTrainingDataSourceId :: Lens' GetMLModelResponse (Maybe Text) -gmlmrTrainingDataSourceId = - lens _gmlmrTrainingDataSourceId - (\s a -> s { _gmlmrTrainingDataSourceId = a }) +-- | The time of the most recent edit to the 'ScoreThreshold'. The time is +-- expressed in epoch time. +gmlmrsScoreThresholdLastUpdatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) +gmlmrsScoreThresholdLastUpdatedAt = lens _gmlmrsScoreThresholdLastUpdatedAt (\ s a -> s{_gmlmrsScoreThresholdLastUpdatedAt = a}) . mapping _Time; --- | A list of the training parameters in the 'MLModel'. The list is implemented as --- a map of key/value pairs. --- --- The following is the current set of training parameters: --- --- 'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. It --- controls overfitting the data by penalizing large coefficients. This tends to --- drive coefficients to zero, resulting in a sparse feature set. If you use --- this parameter, specify a small value, such as 1.0E-04 or 1.0E-08. --- --- The value is a double that ranges from 0 to MAX_DOUBLE. The default is not --- to use L1 normalization. The parameter cannot be used when 'L2' is specified. --- Use this parameter sparingly. --- --- 'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. It --- controls overfitting the data by penalizing large coefficients. This tends to --- drive coefficients to small, nonzero values. If you use this parameter, --- specify a small value, such as 1.0E-04 or 1.0E-08. --- --- The value is a double that ranges from 0 to MAX_DOUBLE. The default is not --- to use L2 normalization. This parameter cannot be used when 'L1' is specified. --- Use this parameter sparingly. +-- | The recipe to use when training the 'MLModel'. The 'Recipe' provides +-- detailed information about the observation data to use during training, +-- as well as manipulations to perform on the observation data during +-- training. -- --- 'sgd.maxPasses' - The number of times that the training process traverses the --- observations to build the 'MLModel'. The value is an integer that ranges from 1 --- to 10000. The default value is 10. +-- Note -- --- 'sgd.maxMLModelSizeInBytes' - The maximum allowed size of the model. --- Depending on the input data, the model size might affect performance. +-- This parameter is provided as part of the verbose format. +gmlmrsRecipe :: Lens' GetMLModelResponse (Maybe Text) +gmlmrsRecipe = lens _gmlmrsRecipe (\ s a -> s{_gmlmrsRecipe = a}); + +-- | The location of the data file or directory in Amazon Simple Storage +-- Service (Amazon S3). +gmlmrsInputDataLocationS3 :: Lens' GetMLModelResponse (Maybe Text) +gmlmrsInputDataLocationS3 = lens _gmlmrsInputDataLocationS3 (\ s a -> s{_gmlmrsInputDataLocationS3 = a}); + +-- | Undocumented member. +gmlmrsSizeInBytes :: Lens' GetMLModelResponse (Maybe Integer) +gmlmrsSizeInBytes = lens _gmlmrsSizeInBytes (\ s a -> s{_gmlmrsSizeInBytes = a}); + +-- | The MLModel ID which is same as the 'MLModelId' in the request. +gmlmrsMLModelId :: Lens' GetMLModelResponse (Maybe Text) +gmlmrsMLModelId = lens _gmlmrsMLModelId (\ s a -> s{_gmlmrsMLModelId = a}); + +-- | The schema used by all of the data files referenced by the 'DataSource'. -- --- The value is an integer that ranges from 100000 to 2147483648. The default --- value is 33554432. +-- Note -- +-- This parameter is provided as part of the verbose format. +gmlmrsSchema :: Lens' GetMLModelResponse (Maybe Text) +gmlmrsSchema = lens _gmlmrsSchema (\ s a -> s{_gmlmrsSchema = a}); + +-- | The scoring threshold is used in binary classification 'MLModel's, and +-- marks the boundary between a positive prediction and a negative +-- prediction. -- -gmlmrTrainingParameters :: Lens' GetMLModelResponse (HashMap Text Text) -gmlmrTrainingParameters = - lens _gmlmrTrainingParameters (\s a -> s { _gmlmrTrainingParameters = a }) - . _Map +-- Output values greater than or equal to the threshold receive a positive +-- result from the MLModel, such as 'true'. Output values less than the +-- threshold receive a negative response from the MLModel, such as 'false'. +gmlmrsScoreThreshold :: Lens' GetMLModelResponse (Maybe Double) +gmlmrsScoreThreshold = lens _gmlmrsScoreThreshold (\ s a -> s{_gmlmrsScoreThreshold = a}); -instance ToPath GetMLModel where - toPath = const "/" +-- | A user-supplied name or description of the 'MLModel'. +gmlmrsName :: Lens' GetMLModelResponse (Maybe Text) +gmlmrsName = lens _gmlmrsName (\ s a -> s{_gmlmrsName = a}); -instance ToQuery GetMLModel where - toQuery = const mempty +-- | The AWS user account from which the 'MLModel' was created. The account +-- type can be either an AWS root account or an AWS Identity and Access +-- Management (IAM) user account. +gmlmrsCreatedByIAMUser :: Lens' GetMLModelResponse (Maybe Text) +gmlmrsCreatedByIAMUser = lens _gmlmrsCreatedByIAMUser (\ s a -> s{_gmlmrsCreatedByIAMUser = a}); -instance ToHeaders GetMLModel +-- | A link to the file that contains logs of the 'CreateMLModel' operation. +gmlmrsLogURI :: Lens' GetMLModelResponse (Maybe Text) +gmlmrsLogURI = lens _gmlmrsLogURI (\ s a -> s{_gmlmrsLogURI = a}); -instance ToJSON GetMLModel where - toJSON GetMLModel{..} = object - [ "MLModelId" .= _gmlmMLModelId - , "Verbose" .= _gmlmVerbose - ] +-- | The current endpoint of the 'MLModel' +gmlmrsEndpointInfo :: Lens' GetMLModelResponse (Maybe RealtimeEndpointInfo) +gmlmrsEndpointInfo = lens _gmlmrsEndpointInfo (\ s a -> s{_gmlmrsEndpointInfo = a}); -instance AWSRequest GetMLModel where - type Sv GetMLModel = MachineLearning - type Rs GetMLModel = GetMLModelResponse +-- | The ID of the training 'DataSource'. +gmlmrsTrainingDataSourceId :: Lens' GetMLModelResponse (Maybe Text) +gmlmrsTrainingDataSourceId = lens _gmlmrsTrainingDataSourceId (\ s a -> s{_gmlmrsTrainingDataSourceId = a}); - request = post "GetMLModel" - response = jsonResponse +-- | Description of the most recent details about accessing the 'MLModel'. +gmlmrsMessage :: Lens' GetMLModelResponse (Maybe Text) +gmlmrsMessage = lens _gmlmrsMessage (\ s a -> s{_gmlmrsMessage = a}); -instance FromJSON GetMLModelResponse where - parseJSON = withObject "GetMLModelResponse" $ \o -> GetMLModelResponse - <$> o .:? "CreatedAt" - <*> o .:? "CreatedByIamUser" - <*> o .:? "EndpointInfo" - <*> o .:? "InputDataLocationS3" - <*> o .:? "LastUpdatedAt" - <*> o .:? "LogUri" - <*> o .:? "MLModelId" - <*> o .:? "MLModelType" - <*> o .:? "Message" - <*> o .:? "Name" - <*> o .:? "Recipe" - <*> o .:? "Schema" - <*> o .:? "ScoreThreshold" - <*> o .:? "ScoreThresholdLastUpdatedAt" - <*> o .:? "SizeInBytes" - <*> o .:? "Status" - <*> o .:? "TrainingDataSourceId" - <*> o .:? "TrainingParameters" .!= mempty +-- | Identifies the 'MLModel' category. The following are the available +-- types: +-- +-- - REGRESSION -- Produces a numeric result. For example, \"What listing +-- price should a house have?\" +-- - BINARY -- Produces one of two possible results. For example, \"Is +-- this an e-commerce website?\" +-- - MULTICLASS -- Produces more than two possible results. For example, +-- \"Is this a HIGH, LOW or MEDIUM risk trade?\" +gmlmrsMLModelType :: Lens' GetMLModelResponse (Maybe MLModelType) +gmlmrsMLModelType = lens _gmlmrsMLModelType (\ s a -> s{_gmlmrsMLModelType = a}); + +-- | The response status code. +gmlmrsStatus :: Lens' GetMLModelResponse Int +gmlmrsStatus = lens _gmlmrsStatus (\ s a -> s{_gmlmrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/Predict.hs b/gen/Network/AWS/MachineLearning/Predict.hs --- a/gen/Network/AWS/MachineLearning/Predict.hs +++ b/gen/Network/AWS/MachineLearning/Predict.hs @@ -1,134 +1,152 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.Predict --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Generates a prediction for the observation using the specified 'MLModel'. +-- Generates a prediction for the observation using the specified +-- 'MLModel'. -- --- Note Not all response parameters will be populated because this is dependent --- on the type of requested model. +-- Note -- +-- Not all response parameters will be populated because this is dependent +-- on the type of requested model. -- --- +-- /See:/ for Predict. module Network.AWS.MachineLearning.Predict ( - -- * Request - Predict - -- ** Request constructor - , predict - -- ** Request lenses + -- * Creating a Request + predict + , Predict + -- * Request Lenses , pMLModelId - , pPredictEndpoint , pRecord + , pPredictEndpoint - -- * Response - , PredictResponse - -- ** Response constructor + -- * Destructuring the Response , predictResponse - -- ** Response lenses - , prPrediction + , PredictResponse + -- * Response Lenses + , prsPrediction + , prsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data Predict = Predict - { _pMLModelId :: Text - , _pPredictEndpoint :: Text - , _pRecord :: Map Text Text - } deriving (Eq, Read, Show) +-- | /See:/ 'predict' smart constructor. +data Predict = Predict' + { _pMLModelId :: !Text + , _pRecord :: !(Map Text Text) + , _pPredictEndpoint :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'Predict' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'Predict' with the minimum fields required to make a request. -- --- * 'pMLModelId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'pPredictEndpoint' @::@ 'Text' +-- * 'pMLModelId' -- --- * 'pRecord' @::@ 'HashMap' 'Text' 'Text' +-- * 'pRecord' -- -predict :: Text -- ^ 'pMLModelId' - -> Text -- ^ 'pPredictEndpoint' - -> Predict -predict p1 p2 = Predict - { _pMLModelId = p1 - , _pPredictEndpoint = p2 - , _pRecord = mempty +-- * 'pPredictEndpoint' +predict + :: Text -- ^ 'pMLModelId' + -> Text -- ^ 'pPredictEndpoint' + -> Predict +predict pMLModelId_ pPredictEndpoint_ = + Predict' + { _pMLModelId = pMLModelId_ + , _pRecord = mempty + , _pPredictEndpoint = pPredictEndpoint_ } -- | A unique identifier of the 'MLModel'. pMLModelId :: Lens' Predict Text -pMLModelId = lens _pMLModelId (\s a -> s { _pMLModelId = a }) - -pPredictEndpoint :: Lens' Predict Text -pPredictEndpoint = lens _pPredictEndpoint (\s a -> s { _pPredictEndpoint = a }) +pMLModelId = lens _pMLModelId (\ s a -> s{_pMLModelId = a}); +-- | Undocumented member. pRecord :: Lens' Predict (HashMap Text Text) -pRecord = lens _pRecord (\s a -> s { _pRecord = a }) . _Map +pRecord = lens _pRecord (\ s a -> s{_pRecord = a}) . _Map; -newtype PredictResponse = PredictResponse - { _prPrediction :: Maybe Prediction - } deriving (Eq, Read, Show) +-- | Undocumented member. +pPredictEndpoint :: Lens' Predict Text +pPredictEndpoint = lens _pPredictEndpoint (\ s a -> s{_pPredictEndpoint = a}); --- | 'PredictResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'prPrediction' @::@ 'Maybe' 'Prediction' --- -predictResponse :: PredictResponse -predictResponse = PredictResponse - { _prPrediction = Nothing - } +instance AWSRequest Predict where + type Sv Predict = MachineLearning + type Rs Predict = PredictResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + PredictResponse' <$> + (x .?> "Prediction") <*> (pure (fromEnum s))) -prPrediction :: Lens' PredictResponse (Maybe Prediction) -prPrediction = lens _prPrediction (\s a -> s { _prPrediction = a }) +instance ToHeaders Predict where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.Predict" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) +instance ToJSON Predict where + toJSON Predict'{..} + = object + ["MLModelId" .= _pMLModelId, "Record" .= _pRecord, + "PredictEndpoint" .= _pPredictEndpoint] + instance ToPath Predict where - toPath = const "/" + toPath = const "/" instance ToQuery Predict where - toQuery = const mempty - -instance ToHeaders Predict + toQuery = const mempty -instance ToJSON Predict where - toJSON Predict{..} = object - [ "MLModelId" .= _pMLModelId - , "Record" .= _pRecord - , "PredictEndpoint" .= _pPredictEndpoint - ] +-- | /See:/ 'predictResponse' smart constructor. +data PredictResponse = PredictResponse' + { _prsPrediction :: !(Maybe Prediction) + , _prsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest Predict where - type Sv Predict = MachineLearning - type Rs Predict = PredictResponse +-- | Creates a value of 'PredictResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'prsPrediction' +-- +-- * 'prsStatus' +predictResponse + :: Int -- ^ 'prsStatus' + -> PredictResponse +predictResponse pStatus_ = + PredictResponse' + { _prsPrediction = Nothing + , _prsStatus = pStatus_ + } - request = post "Predict" - response = jsonResponse +-- | Undocumented member. +prsPrediction :: Lens' PredictResponse (Maybe Prediction) +prsPrediction = lens _prsPrediction (\ s a -> s{_prsPrediction = a}); -instance FromJSON PredictResponse where - parseJSON = withObject "PredictResponse" $ \o -> PredictResponse - <$> o .:? "Prediction" +-- | The response status code. +prsStatus :: Lens' PredictResponse Int +prsStatus = lens _prsStatus (\ s a -> s{_prsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/Types.hs b/gen/Network/AWS/MachineLearning/Types.hs --- a/gen/Network/AWS/MachineLearning/Types.hs +++ b/gen/Network/AWS/MachineLearning/Types.hs @@ -1,2148 +1,296 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} -{-# LANGUAGE ViewPatterns #-} - -{-# OPTIONS_GHC -fno-warn-unused-imports #-} - --- Module : Network.AWS.MachineLearning.Types --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. --- Maintainer : Brendan Hay --- Stability : experimental --- Portability : non-portable (GHC extensions) --- --- Derived from AWS service descriptions, licensed under Apache 2.0. - -module Network.AWS.MachineLearning.Types - ( - -- * Service - MachineLearning - -- ** Error - , JSONError - - -- * BatchPredictionFilterVariable - , BatchPredictionFilterVariable (..) - - -- * PerformanceMetrics - , PerformanceMetrics - , performanceMetrics - , pmProperties - - -- * RealtimeEndpointInfo - , RealtimeEndpointInfo - , realtimeEndpointInfo - , reiCreatedAt - , reiEndpointStatus - , reiEndpointUrl - , reiPeakRequestsPerSecond - - -- * Prediction - , Prediction - , prediction - , pDetails - , pPredictedLabel - , pPredictedScores - , pPredictedValue - - -- * S3DataSpec - , S3DataSpec - , s3DataSpec - , sdsDataLocationS3 - , sdsDataRearrangement - , sdsDataSchema - , sdsDataSchemaLocationS3 - - -- * DetailsAttributes - , DetailsAttributes (..) - - -- * EvaluationFilterVariable - , EvaluationFilterVariable (..) - - -- * RealtimeEndpointStatus - , RealtimeEndpointStatus (..) - - -- * RDSDataSpec - , RDSDataSpec - , rdsdataSpec - , rdsdsDataRearrangement - , rdsdsDataSchema - , rdsdsDataSchemaUri - , rdsdsDatabaseCredentials - , rdsdsDatabaseInformation - , rdsdsResourceRole - , rdsdsS3StagingLocation - , rdsdsSecurityGroupIds - , rdsdsSelectSqlQuery - , rdsdsServiceRole - , rdsdsSubnetId - - -- * RDSMetadata - , RDSMetadata - , rdsmetadata - , rdsmDataPipelineId - , rdsmDatabase - , rdsmDatabaseUserName - , rdsmResourceRole - , rdsmSelectSqlQuery - , rdsmServiceRole - - -- * RedshiftDatabase - , RedshiftDatabase - , redshiftDatabase - , rdClusterIdentifier - , rdDatabaseName - - -- * RedshiftDatabaseCredentials - , RedshiftDatabaseCredentials - , redshiftDatabaseCredentials - , rdcPassword - , rdcUsername - - -- * MLModel - , MLModel - , mlmodel - , mlmAlgorithm - , mlmCreatedAt - , mlmCreatedByIamUser - , mlmEndpointInfo - , mlmInputDataLocationS3 - , mlmLastUpdatedAt - , mlmMLModelId - , mlmMLModelType - , mlmMessage - , mlmName - , mlmScoreThreshold - , mlmScoreThresholdLastUpdatedAt - , mlmSizeInBytes - , mlmStatus - , mlmTrainingDataSourceId - , mlmTrainingParameters - - -- * BatchPrediction - , BatchPrediction - , batchPrediction - , bpBatchPredictionDataSourceId - , bpBatchPredictionId - , bpCreatedAt - , bpCreatedByIamUser - , bpInputDataLocationS3 - , bpLastUpdatedAt - , bpMLModelId - , bpMessage - , bpName - , bpOutputUri - , bpStatus - - -- * SortOrder - , SortOrder (..) - - -- * Algorithm - , Algorithm (..) - - -- * EntityStatus - , EntityStatus (..) - - -- * DataSource - , DataSource - , dataSource - , dsComputeStatistics - , dsCreatedAt - , dsCreatedByIamUser - , dsDataLocationS3 - , dsDataRearrangement - , dsDataSizeInBytes - , dsDataSourceId - , dsLastUpdatedAt - , dsMessage - , dsName - , dsNumberOfFiles - , dsRDSMetadata - , dsRedshiftMetadata - , dsRoleARN - , dsStatus - - -- * RDSDatabase - , RDSDatabase - , rdsdatabase - , rdsdDatabaseName - , rdsdInstanceIdentifier - - -- * RDSDatabaseCredentials - , RDSDatabaseCredentials - , rdsdatabaseCredentials - , rdsdcPassword - , rdsdcUsername - - -- * MLModelFilterVariable - , MLModelFilterVariable (..) - - -- * DataSourceFilterVariable - , DataSourceFilterVariable (..) - - -- * RedshiftDataSpec - , RedshiftDataSpec - , redshiftDataSpec - , rdsDataRearrangement - , rdsDataSchema - , rdsDataSchemaUri - , rdsDatabaseCredentials - , rdsDatabaseInformation - , rdsS3StagingLocation - , rdsSelectSqlQuery - - -- * Evaluation - , Evaluation - , evaluation - , eCreatedAt - , eCreatedByIamUser - , eEvaluationDataSourceId - , eEvaluationId - , eInputDataLocationS3 - , eLastUpdatedAt - , eMLModelId - , eMessage - , eName - , ePerformanceMetrics - , eStatus - - -- * RedshiftMetadata - , RedshiftMetadata - , redshiftMetadata - , rmDatabaseUserName - , rmRedshiftDatabase - , rmSelectSqlQuery - - -- * MLModelType - , MLModelType (..) - ) where - -import Network.AWS.Prelude -import Network.AWS.Signing -import qualified GHC.Exts - --- | Version @2014-12-12@ of the Amazon Machine Learning service. -data MachineLearning - -instance AWSService MachineLearning where - type Sg MachineLearning = V4 - type Er MachineLearning = JSONError - - service = service' - where - service' :: Service MachineLearning - service' = Service - { _svcAbbrev = "MachineLearning" - , _svcPrefix = "machinelearning" - , _svcVersion = "2014-12-12" - , _svcTargetPrefix = Just "AmazonML_20141212" - , _svcJSONVersion = Just "1.1" - , _svcHandle = handle - , _svcRetry = retry - } - - handle :: Status - -> Maybe (LazyByteString -> ServiceError JSONError) - handle = jsonError statusSuccess service' - - retry :: Retry MachineLearning - retry = Exponential - { _retryBase = 0.05 - , _retryGrowth = 2 - , _retryAttempts = 5 - , _retryCheck = check - } - - check :: Status - -> JSONError - -> Bool - check (statusCode -> s) (awsErrorCode -> e) - | s == 500 = True -- General Server Error - | s == 509 = True -- Limit Exceeded - | s == 503 = True -- Service Unavailable - | otherwise = False - -data BatchPredictionFilterVariable - = BatchCreatedAt -- ^ CreatedAt - | BatchDataSourceId -- ^ DataSourceId - | BatchDataURI -- ^ DataURI - | BatchIAMUser -- ^ IAMUser - | BatchLastUpdatedAt -- ^ LastUpdatedAt - | BatchMLModelId -- ^ MLModelId - | BatchName -- ^ Name - | BatchStatus -- ^ Status - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable BatchPredictionFilterVariable - -instance FromText BatchPredictionFilterVariable where - parser = takeLowerText >>= \case - "createdat" -> pure BatchCreatedAt - "datasourceid" -> pure BatchDataSourceId - "datauri" -> pure BatchDataURI - "iamuser" -> pure BatchIAMUser - "lastupdatedat" -> pure BatchLastUpdatedAt - "mlmodelid" -> pure BatchMLModelId - "name" -> pure BatchName - "status" -> pure BatchStatus - e -> fail $ - "Failure parsing BatchPredictionFilterVariable from " ++ show e - -instance ToText BatchPredictionFilterVariable where - toText = \case - BatchCreatedAt -> "CreatedAt" - BatchDataSourceId -> "DataSourceId" - BatchDataURI -> "DataURI" - BatchIAMUser -> "IAMUser" - BatchLastUpdatedAt -> "LastUpdatedAt" - BatchMLModelId -> "MLModelId" - BatchName -> "Name" - BatchStatus -> "Status" - -instance ToByteString BatchPredictionFilterVariable -instance ToHeader BatchPredictionFilterVariable -instance ToQuery BatchPredictionFilterVariable - -instance FromJSON BatchPredictionFilterVariable where - parseJSON = parseJSONText "BatchPredictionFilterVariable" - -instance ToJSON BatchPredictionFilterVariable where - toJSON = toJSONText - -newtype PerformanceMetrics = PerformanceMetrics - { _pmProperties :: Map Text Text - } deriving (Eq, Read, Show, Monoid, Semigroup) - --- | 'PerformanceMetrics' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'pmProperties' @::@ 'HashMap' 'Text' 'Text' --- -performanceMetrics :: PerformanceMetrics -performanceMetrics = PerformanceMetrics - { _pmProperties = mempty - } - -pmProperties :: Lens' PerformanceMetrics (HashMap Text Text) -pmProperties = lens _pmProperties (\s a -> s { _pmProperties = a }) . _Map - -instance FromJSON PerformanceMetrics where - parseJSON = withObject "PerformanceMetrics" $ \o -> PerformanceMetrics - <$> o .:? "Properties" .!= mempty - -instance ToJSON PerformanceMetrics where - toJSON PerformanceMetrics{..} = object - [ "Properties" .= _pmProperties - ] - -data RealtimeEndpointInfo = RealtimeEndpointInfo - { _reiCreatedAt :: Maybe POSIX - , _reiEndpointStatus :: Maybe RealtimeEndpointStatus - , _reiEndpointUrl :: Maybe Text - , _reiPeakRequestsPerSecond :: Maybe Int - } deriving (Eq, Read, Show) - --- | 'RealtimeEndpointInfo' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'reiCreatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'reiEndpointStatus' @::@ 'Maybe' 'RealtimeEndpointStatus' --- --- * 'reiEndpointUrl' @::@ 'Maybe' 'Text' --- --- * 'reiPeakRequestsPerSecond' @::@ 'Maybe' 'Int' --- -realtimeEndpointInfo :: RealtimeEndpointInfo -realtimeEndpointInfo = RealtimeEndpointInfo - { _reiPeakRequestsPerSecond = Nothing - , _reiCreatedAt = Nothing - , _reiEndpointUrl = Nothing - , _reiEndpointStatus = Nothing - } - --- | The time that the request to create the real-time endpoint for the 'MLModel' --- was received. The time is expressed in epoch time. -reiCreatedAt :: Lens' RealtimeEndpointInfo (Maybe UTCTime) -reiCreatedAt = lens _reiCreatedAt (\s a -> s { _reiCreatedAt = a }) . mapping _Time - --- | The current status of the real-time endpoint for the 'MLModel'. This element --- can have one of the following values: --- --- NONE - Endpoint does not exist or was previously deleted. READY - Endpoint --- is ready to be used for real-time predictions. UPDATING - Updating/creating --- the endpoint. -reiEndpointStatus :: Lens' RealtimeEndpointInfo (Maybe RealtimeEndpointStatus) -reiEndpointStatus = - lens _reiEndpointStatus (\s a -> s { _reiEndpointStatus = a }) - --- | The URI that specifies where to send real-time prediction requests for the 'MLModel'. --- --- Note The application must wait until the real-time endpoint is ready before --- using this URI. --- --- -reiEndpointUrl :: Lens' RealtimeEndpointInfo (Maybe Text) -reiEndpointUrl = lens _reiEndpointUrl (\s a -> s { _reiEndpointUrl = a }) - --- | The maximum processing rate for the real-time endpoint for 'MLModel', measured --- in incoming requests per second. -reiPeakRequestsPerSecond :: Lens' RealtimeEndpointInfo (Maybe Int) -reiPeakRequestsPerSecond = - lens _reiPeakRequestsPerSecond - (\s a -> s { _reiPeakRequestsPerSecond = a }) - -instance FromJSON RealtimeEndpointInfo where - parseJSON = withObject "RealtimeEndpointInfo" $ \o -> RealtimeEndpointInfo - <$> o .:? "CreatedAt" - <*> o .:? "EndpointStatus" - <*> o .:? "EndpointUrl" - <*> o .:? "PeakRequestsPerSecond" - -instance ToJSON RealtimeEndpointInfo where - toJSON RealtimeEndpointInfo{..} = object - [ "PeakRequestsPerSecond" .= _reiPeakRequestsPerSecond - , "CreatedAt" .= _reiCreatedAt - , "EndpointUrl" .= _reiEndpointUrl - , "EndpointStatus" .= _reiEndpointStatus - ] - -data Prediction = Prediction - { _pDetails :: Map DetailsAttributes Text - , _pPredictedLabel :: Maybe Text - , _pPredictedScores :: Map Text Double - , _pPredictedValue :: Maybe Double - } deriving (Eq, Read, Show) - --- | 'Prediction' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'pDetails' @::@ 'HashMap' 'DetailsAttributes' 'Text' --- --- * 'pPredictedLabel' @::@ 'Maybe' 'Text' --- --- * 'pPredictedScores' @::@ 'HashMap' 'Text' 'Double' --- --- * 'pPredictedValue' @::@ 'Maybe' 'Double' --- -prediction :: Prediction -prediction = Prediction - { _pPredictedLabel = Nothing - , _pPredictedValue = Nothing - , _pPredictedScores = mempty - , _pDetails = mempty - } - -pDetails :: Lens' Prediction (HashMap DetailsAttributes Text) -pDetails = lens _pDetails (\s a -> s { _pDetails = a }) . _Map - --- | The prediction label for either a BINARY or MULTICLASS 'MLModel'. -pPredictedLabel :: Lens' Prediction (Maybe Text) -pPredictedLabel = lens _pPredictedLabel (\s a -> s { _pPredictedLabel = a }) - -pPredictedScores :: Lens' Prediction (HashMap Text Double) -pPredictedScores = lens _pPredictedScores (\s a -> s { _pPredictedScores = a }) . _Map - --- | The prediction value for REGRESSION 'MLModel'. -pPredictedValue :: Lens' Prediction (Maybe Double) -pPredictedValue = lens _pPredictedValue (\s a -> s { _pPredictedValue = a }) - -instance FromJSON Prediction where - parseJSON = withObject "Prediction" $ \o -> Prediction - <$> o .:? "details" .!= mempty - <*> o .:? "predictedLabel" - <*> o .:? "predictedScores" .!= mempty - <*> o .:? "predictedValue" - -instance ToJSON Prediction where - toJSON Prediction{..} = object - [ "predictedLabel" .= _pPredictedLabel - , "predictedValue" .= _pPredictedValue - , "predictedScores" .= _pPredictedScores - , "details" .= _pDetails - ] - -data S3DataSpec = S3DataSpec - { _sdsDataLocationS3 :: Text - , _sdsDataRearrangement :: Maybe Text - , _sdsDataSchema :: Maybe Text - , _sdsDataSchemaLocationS3 :: Maybe Text - } deriving (Eq, Ord, Read, Show) - --- | 'S3DataSpec' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'sdsDataLocationS3' @::@ 'Text' --- --- * 'sdsDataRearrangement' @::@ 'Maybe' 'Text' --- --- * 'sdsDataSchema' @::@ 'Maybe' 'Text' --- --- * 'sdsDataSchemaLocationS3' @::@ 'Maybe' 'Text' --- -s3DataSpec :: Text -- ^ 'sdsDataLocationS3' - -> S3DataSpec -s3DataSpec p1 = S3DataSpec - { _sdsDataLocationS3 = p1 - , _sdsDataRearrangement = Nothing - , _sdsDataSchema = Nothing - , _sdsDataSchemaLocationS3 = Nothing - } - --- | The location of the data file(s) used by a 'DataSource'. The URI specifies a --- data file or an Amazon Simple Storage Service (Amazon S3) directory or bucket --- containing data files. -sdsDataLocationS3 :: Lens' S3DataSpec Text -sdsDataLocationS3 = - lens _sdsDataLocationS3 (\s a -> s { _sdsDataLocationS3 = a }) - --- | Describes the splitting requirement of a 'Datasource'. -sdsDataRearrangement :: Lens' S3DataSpec (Maybe Text) -sdsDataRearrangement = - lens _sdsDataRearrangement (\s a -> s { _sdsDataRearrangement = a }) - --- | Describes the schema for an Amazon S3 'DataSource'. -sdsDataSchema :: Lens' S3DataSpec (Maybe Text) -sdsDataSchema = lens _sdsDataSchema (\s a -> s { _sdsDataSchema = a }) - --- | Describes the schema Location in Amazon S3. -sdsDataSchemaLocationS3 :: Lens' S3DataSpec (Maybe Text) -sdsDataSchemaLocationS3 = - lens _sdsDataSchemaLocationS3 (\s a -> s { _sdsDataSchemaLocationS3 = a }) - -instance FromJSON S3DataSpec where - parseJSON = withObject "S3DataSpec" $ \o -> S3DataSpec - <$> o .: "DataLocationS3" - <*> o .:? "DataRearrangement" - <*> o .:? "DataSchema" - <*> o .:? "DataSchemaLocationS3" - -instance ToJSON S3DataSpec where - toJSON S3DataSpec{..} = object - [ "DataLocationS3" .= _sdsDataLocationS3 - , "DataRearrangement" .= _sdsDataRearrangement - , "DataSchema" .= _sdsDataSchema - , "DataSchemaLocationS3" .= _sdsDataSchemaLocationS3 - ] - -data DetailsAttributes - = DAAlgorithm -- ^ Algorithm - | DAPredictiveModelType -- ^ PredictiveModelType - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable DetailsAttributes - -instance FromText DetailsAttributes where - parser = takeLowerText >>= \case - "algorithm" -> pure DAAlgorithm - "predictivemodeltype" -> pure DAPredictiveModelType - e -> fail $ - "Failure parsing DetailsAttributes from " ++ show e - -instance ToText DetailsAttributes where - toText = \case - DAAlgorithm -> "Algorithm" - DAPredictiveModelType -> "PredictiveModelType" - -instance ToByteString DetailsAttributes -instance ToHeader DetailsAttributes -instance ToQuery DetailsAttributes - -instance FromJSON DetailsAttributes where - parseJSON = parseJSONText "DetailsAttributes" - -instance ToJSON DetailsAttributes where - toJSON = toJSONText - -data EvaluationFilterVariable - = EvalCreatedAt -- ^ CreatedAt - | EvalDataSourceId -- ^ DataSourceId - | EvalDataURI -- ^ DataURI - | EvalIAMUser -- ^ IAMUser - | EvalLastUpdatedAt -- ^ LastUpdatedAt - | EvalMLModelId -- ^ MLModelId - | EvalName -- ^ Name - | EvalStatus -- ^ Status - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable EvaluationFilterVariable - -instance FromText EvaluationFilterVariable where - parser = takeLowerText >>= \case - "createdat" -> pure EvalCreatedAt - "datasourceid" -> pure EvalDataSourceId - "datauri" -> pure EvalDataURI - "iamuser" -> pure EvalIAMUser - "lastupdatedat" -> pure EvalLastUpdatedAt - "mlmodelid" -> pure EvalMLModelId - "name" -> pure EvalName - "status" -> pure EvalStatus - e -> fail $ - "Failure parsing EvaluationFilterVariable from " ++ show e - -instance ToText EvaluationFilterVariable where - toText = \case - EvalCreatedAt -> "CreatedAt" - EvalDataSourceId -> "DataSourceId" - EvalDataURI -> "DataURI" - EvalIAMUser -> "IAMUser" - EvalLastUpdatedAt -> "LastUpdatedAt" - EvalMLModelId -> "MLModelId" - EvalName -> "Name" - EvalStatus -> "Status" - -instance ToByteString EvaluationFilterVariable -instance ToHeader EvaluationFilterVariable -instance ToQuery EvaluationFilterVariable - -instance FromJSON EvaluationFilterVariable where - parseJSON = parseJSONText "EvaluationFilterVariable" - -instance ToJSON EvaluationFilterVariable where - toJSON = toJSONText - -data RealtimeEndpointStatus - = Failed -- ^ FAILED - | None -- ^ NONE - | Ready -- ^ READY - | Updating -- ^ UPDATING - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable RealtimeEndpointStatus - -instance FromText RealtimeEndpointStatus where - parser = takeLowerText >>= \case - "failed" -> pure Failed - "none" -> pure None - "ready" -> pure Ready - "updating" -> pure Updating - e -> fail $ - "Failure parsing RealtimeEndpointStatus from " ++ show e - -instance ToText RealtimeEndpointStatus where - toText = \case - Failed -> "FAILED" - None -> "NONE" - Ready -> "READY" - Updating -> "UPDATING" - -instance ToByteString RealtimeEndpointStatus -instance ToHeader RealtimeEndpointStatus -instance ToQuery RealtimeEndpointStatus - -instance FromJSON RealtimeEndpointStatus where - parseJSON = parseJSONText "RealtimeEndpointStatus" - -instance ToJSON RealtimeEndpointStatus where - toJSON = toJSONText - -data RDSDataSpec = RDSDataSpec - { _rdsdsDataRearrangement :: Maybe Text - , _rdsdsDataSchema :: Maybe Text - , _rdsdsDataSchemaUri :: Maybe Text - , _rdsdsDatabaseCredentials :: RDSDatabaseCredentials - , _rdsdsDatabaseInformation :: RDSDatabase - , _rdsdsResourceRole :: Text - , _rdsdsS3StagingLocation :: Text - , _rdsdsSecurityGroupIds :: List "SecurityGroupIds" Text - , _rdsdsSelectSqlQuery :: Text - , _rdsdsServiceRole :: Text - , _rdsdsSubnetId :: Text - } deriving (Eq, Read, Show) - --- | 'RDSDataSpec' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'rdsdsDataRearrangement' @::@ 'Maybe' 'Text' --- --- * 'rdsdsDataSchema' @::@ 'Maybe' 'Text' --- --- * 'rdsdsDataSchemaUri' @::@ 'Maybe' 'Text' --- --- * 'rdsdsDatabaseCredentials' @::@ 'RDSDatabaseCredentials' --- --- * 'rdsdsDatabaseInformation' @::@ 'RDSDatabase' --- --- * 'rdsdsResourceRole' @::@ 'Text' --- --- * 'rdsdsS3StagingLocation' @::@ 'Text' --- --- * 'rdsdsSecurityGroupIds' @::@ ['Text'] --- --- * 'rdsdsSelectSqlQuery' @::@ 'Text' --- --- * 'rdsdsServiceRole' @::@ 'Text' --- --- * 'rdsdsSubnetId' @::@ 'Text' --- -rdsdataSpec :: RDSDatabase -- ^ 'rdsdsDatabaseInformation' - -> Text -- ^ 'rdsdsSelectSqlQuery' - -> RDSDatabaseCredentials -- ^ 'rdsdsDatabaseCredentials' - -> Text -- ^ 'rdsdsS3StagingLocation' - -> Text -- ^ 'rdsdsResourceRole' - -> Text -- ^ 'rdsdsServiceRole' - -> Text -- ^ 'rdsdsSubnetId' - -> RDSDataSpec -rdsdataSpec p1 p2 p3 p4 p5 p6 p7 = RDSDataSpec - { _rdsdsDatabaseInformation = p1 - , _rdsdsSelectSqlQuery = p2 - , _rdsdsDatabaseCredentials = p3 - , _rdsdsS3StagingLocation = p4 - , _rdsdsResourceRole = p5 - , _rdsdsServiceRole = p6 - , _rdsdsSubnetId = p7 - , _rdsdsDataRearrangement = Nothing - , _rdsdsDataSchema = Nothing - , _rdsdsDataSchemaUri = Nothing - , _rdsdsSecurityGroupIds = mempty - } - --- | DataRearrangement - A JSON string that represents the splitting requirement --- of a 'DataSource'. --- --- --- Sample - ' "{\"randomSeed\":\"some-random-seed\",\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"' -rdsdsDataRearrangement :: Lens' RDSDataSpec (Maybe Text) -rdsdsDataRearrangement = - lens _rdsdsDataRearrangement (\s a -> s { _rdsdsDataRearrangement = a }) - --- | A JSON string that represents the schema. This is not required if 'DataSchemaUri' is specified. -rdsdsDataSchema :: Lens' RDSDataSpec (Maybe Text) -rdsdsDataSchema = lens _rdsdsDataSchema (\s a -> s { _rdsdsDataSchema = a }) - --- | The Amazon S3 location of the 'DataSchema'. -rdsdsDataSchemaUri :: Lens' RDSDataSpec (Maybe Text) -rdsdsDataSchemaUri = - lens _rdsdsDataSchemaUri (\s a -> s { _rdsdsDataSchemaUri = a }) - --- | The AWS Identity and Access Management (IAM) credentials that are used --- connect to the Amazon RDS database. -rdsdsDatabaseCredentials :: Lens' RDSDataSpec RDSDatabaseCredentials -rdsdsDatabaseCredentials = - lens _rdsdsDatabaseCredentials - (\s a -> s { _rdsdsDatabaseCredentials = a }) - --- | Describes the 'DatabaseName' and 'InstanceIdentifier' of an an Amazon RDS --- database. -rdsdsDatabaseInformation :: Lens' RDSDataSpec RDSDatabase -rdsdsDatabaseInformation = - lens _rdsdsDatabaseInformation - (\s a -> s { _rdsdsDatabaseInformation = a }) - --- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon Elastic --- Compute Cloud (Amazon EC2) instance to carry out the copy operation from --- Amazon RDS to an Amazon S3 task. For more information, see for --- data pipelines. -rdsdsResourceRole :: Lens' RDSDataSpec Text -rdsdsResourceRole = - lens _rdsdsResourceRole (\s a -> s { _rdsdsResourceRole = a }) - --- | The Amazon S3 location for staging Amazon RDS data. The data retrieved from --- Amazon RDS using 'SelectSqlQuery' is stored in this location. -rdsdsS3StagingLocation :: Lens' RDSDataSpec Text -rdsdsS3StagingLocation = - lens _rdsdsS3StagingLocation (\s a -> s { _rdsdsS3StagingLocation = a }) - --- | The security group IDs to be used to access a VPC-based RDS DB instance. --- Ensure that there are appropriate ingress rules set up to allow access to the --- RDS DB instance. This attribute is used by Data Pipeline to carry out the --- copy operation from Amazon RDS to an Amazon S3 task. -rdsdsSecurityGroupIds :: Lens' RDSDataSpec [Text] -rdsdsSecurityGroupIds = - lens _rdsdsSecurityGroupIds (\s a -> s { _rdsdsSecurityGroupIds = a }) - . _List - --- | The query that is used to retrieve the observation data for the 'DataSource'. -rdsdsSelectSqlQuery :: Lens' RDSDataSpec Text -rdsdsSelectSqlQuery = - lens _rdsdsSelectSqlQuery (\s a -> s { _rdsdsSelectSqlQuery = a }) - --- | The role (DataPipelineDefaultRole) assumed by AWS Data Pipeline service to --- monitor the progress of the copy task from Amazon RDS to Amazon S3. For more --- information, see for data pipelines. -rdsdsServiceRole :: Lens' RDSDataSpec Text -rdsdsServiceRole = lens _rdsdsServiceRole (\s a -> s { _rdsdsServiceRole = a }) - --- | The subnet ID to be used to access a VPC-based RDS DB instance. This --- attribute is used by Data Pipeline to carry out the copy task from Amazon RDS --- to Amazon S3. -rdsdsSubnetId :: Lens' RDSDataSpec Text -rdsdsSubnetId = lens _rdsdsSubnetId (\s a -> s { _rdsdsSubnetId = a }) - -instance FromJSON RDSDataSpec where - parseJSON = withObject "RDSDataSpec" $ \o -> RDSDataSpec - <$> o .:? "DataRearrangement" - <*> o .:? "DataSchema" - <*> o .:? "DataSchemaUri" - <*> o .: "DatabaseCredentials" - <*> o .: "DatabaseInformation" - <*> o .: "ResourceRole" - <*> o .: "S3StagingLocation" - <*> o .:? "SecurityGroupIds" .!= mempty - <*> o .: "SelectSqlQuery" - <*> o .: "ServiceRole" - <*> o .: "SubnetId" - -instance ToJSON RDSDataSpec where - toJSON RDSDataSpec{..} = object - [ "DatabaseInformation" .= _rdsdsDatabaseInformation - , "SelectSqlQuery" .= _rdsdsSelectSqlQuery - , "DatabaseCredentials" .= _rdsdsDatabaseCredentials - , "S3StagingLocation" .= _rdsdsS3StagingLocation - , "DataRearrangement" .= _rdsdsDataRearrangement - , "DataSchema" .= _rdsdsDataSchema - , "DataSchemaUri" .= _rdsdsDataSchemaUri - , "ResourceRole" .= _rdsdsResourceRole - , "ServiceRole" .= _rdsdsServiceRole - , "SubnetId" .= _rdsdsSubnetId - , "SecurityGroupIds" .= _rdsdsSecurityGroupIds - ] - -data RDSMetadata = RDSMetadata - { _rdsmDataPipelineId :: Maybe Text - , _rdsmDatabase :: Maybe RDSDatabase - , _rdsmDatabaseUserName :: Maybe Text - , _rdsmResourceRole :: Maybe Text - , _rdsmSelectSqlQuery :: Maybe Text - , _rdsmServiceRole :: Maybe Text - } deriving (Eq, Read, Show) - --- | 'RDSMetadata' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'rdsmDataPipelineId' @::@ 'Maybe' 'Text' --- --- * 'rdsmDatabase' @::@ 'Maybe' 'RDSDatabase' --- --- * 'rdsmDatabaseUserName' @::@ 'Maybe' 'Text' --- --- * 'rdsmResourceRole' @::@ 'Maybe' 'Text' --- --- * 'rdsmSelectSqlQuery' @::@ 'Maybe' 'Text' --- --- * 'rdsmServiceRole' @::@ 'Maybe' 'Text' --- -rdsmetadata :: RDSMetadata -rdsmetadata = RDSMetadata - { _rdsmDatabase = Nothing - , _rdsmDatabaseUserName = Nothing - , _rdsmSelectSqlQuery = Nothing - , _rdsmResourceRole = Nothing - , _rdsmServiceRole = Nothing - , _rdsmDataPipelineId = Nothing - } - --- | The ID of the Data Pipeline instance that is used to carry to copy data from --- Amazon RDS to Amazon S3. You can use the ID to find details about the --- instance in the Data Pipeline console. -rdsmDataPipelineId :: Lens' RDSMetadata (Maybe Text) -rdsmDataPipelineId = - lens _rdsmDataPipelineId (\s a -> s { _rdsmDataPipelineId = a }) - --- | The database details required to connect to an Amazon RDS. -rdsmDatabase :: Lens' RDSMetadata (Maybe RDSDatabase) -rdsmDatabase = lens _rdsmDatabase (\s a -> s { _rdsmDatabase = a }) - -rdsmDatabaseUserName :: Lens' RDSMetadata (Maybe Text) -rdsmDatabaseUserName = - lens _rdsmDatabaseUserName (\s a -> s { _rdsmDatabaseUserName = a }) - --- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon EC2 instance --- to carry out the copy task from Amazon RDS to Amazon S3. For more --- information, see for data pipelines. -rdsmResourceRole :: Lens' RDSMetadata (Maybe Text) -rdsmResourceRole = lens _rdsmResourceRole (\s a -> s { _rdsmResourceRole = a }) - --- | The SQL query that is supplied during 'CreateDataSourceFromRDS'. Returns only --- if 'Verbose' is true in 'GetDataSourceInput'. -rdsmSelectSqlQuery :: Lens' RDSMetadata (Maybe Text) -rdsmSelectSqlQuery = - lens _rdsmSelectSqlQuery (\s a -> s { _rdsmSelectSqlQuery = a }) - --- | The role (DataPipelineDefaultRole) assumed by the Data Pipeline service to --- monitor the progress of the copy task from Amazon RDS to Amazon S3. For more --- information, see for data pipelines. -rdsmServiceRole :: Lens' RDSMetadata (Maybe Text) -rdsmServiceRole = lens _rdsmServiceRole (\s a -> s { _rdsmServiceRole = a }) - -instance FromJSON RDSMetadata where - parseJSON = withObject "RDSMetadata" $ \o -> RDSMetadata - <$> o .:? "DataPipelineId" - <*> o .:? "Database" - <*> o .:? "DatabaseUserName" - <*> o .:? "ResourceRole" - <*> o .:? "SelectSqlQuery" - <*> o .:? "ServiceRole" - -instance ToJSON RDSMetadata where - toJSON RDSMetadata{..} = object - [ "Database" .= _rdsmDatabase - , "DatabaseUserName" .= _rdsmDatabaseUserName - , "SelectSqlQuery" .= _rdsmSelectSqlQuery - , "ResourceRole" .= _rdsmResourceRole - , "ServiceRole" .= _rdsmServiceRole - , "DataPipelineId" .= _rdsmDataPipelineId - ] - -data RedshiftDatabase = RedshiftDatabase - { _rdClusterIdentifier :: Text - , _rdDatabaseName :: Text - } deriving (Eq, Ord, Read, Show) - --- | 'RedshiftDatabase' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'rdClusterIdentifier' @::@ 'Text' --- --- * 'rdDatabaseName' @::@ 'Text' --- -redshiftDatabase :: Text -- ^ 'rdDatabaseName' - -> Text -- ^ 'rdClusterIdentifier' - -> RedshiftDatabase -redshiftDatabase p1 p2 = RedshiftDatabase - { _rdDatabaseName = p1 - , _rdClusterIdentifier = p2 - } - -rdClusterIdentifier :: Lens' RedshiftDatabase Text -rdClusterIdentifier = - lens _rdClusterIdentifier (\s a -> s { _rdClusterIdentifier = a }) - -rdDatabaseName :: Lens' RedshiftDatabase Text -rdDatabaseName = lens _rdDatabaseName (\s a -> s { _rdDatabaseName = a }) - -instance FromJSON RedshiftDatabase where - parseJSON = withObject "RedshiftDatabase" $ \o -> RedshiftDatabase - <$> o .: "ClusterIdentifier" - <*> o .: "DatabaseName" - -instance ToJSON RedshiftDatabase where - toJSON RedshiftDatabase{..} = object - [ "DatabaseName" .= _rdDatabaseName - , "ClusterIdentifier" .= _rdClusterIdentifier - ] - -data RedshiftDatabaseCredentials = RedshiftDatabaseCredentials - { _rdcPassword :: Text - , _rdcUsername :: Text - } deriving (Eq, Ord, Read, Show) - --- | 'RedshiftDatabaseCredentials' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'rdcPassword' @::@ 'Text' --- --- * 'rdcUsername' @::@ 'Text' --- -redshiftDatabaseCredentials :: Text -- ^ 'rdcUsername' - -> Text -- ^ 'rdcPassword' - -> RedshiftDatabaseCredentials -redshiftDatabaseCredentials p1 p2 = RedshiftDatabaseCredentials - { _rdcUsername = p1 - , _rdcPassword = p2 - } - -rdcPassword :: Lens' RedshiftDatabaseCredentials Text -rdcPassword = lens _rdcPassword (\s a -> s { _rdcPassword = a }) - -rdcUsername :: Lens' RedshiftDatabaseCredentials Text -rdcUsername = lens _rdcUsername (\s a -> s { _rdcUsername = a }) - -instance FromJSON RedshiftDatabaseCredentials where - parseJSON = withObject "RedshiftDatabaseCredentials" $ \o -> RedshiftDatabaseCredentials - <$> o .: "Password" - <*> o .: "Username" - -instance ToJSON RedshiftDatabaseCredentials where - toJSON RedshiftDatabaseCredentials{..} = object - [ "Username" .= _rdcUsername - , "Password" .= _rdcPassword - ] - -data MLModel = MLModel - { _mlmAlgorithm :: Maybe Algorithm - , _mlmCreatedAt :: Maybe POSIX - , _mlmCreatedByIamUser :: Maybe Text - , _mlmEndpointInfo :: Maybe RealtimeEndpointInfo - , _mlmInputDataLocationS3 :: Maybe Text - , _mlmLastUpdatedAt :: Maybe POSIX - , _mlmMLModelId :: Maybe Text - , _mlmMLModelType :: Maybe MLModelType - , _mlmMessage :: Maybe Text - , _mlmName :: Maybe Text - , _mlmScoreThreshold :: Maybe Double - , _mlmScoreThresholdLastUpdatedAt :: Maybe POSIX - , _mlmSizeInBytes :: Maybe Integer - , _mlmStatus :: Maybe EntityStatus - , _mlmTrainingDataSourceId :: Maybe Text - , _mlmTrainingParameters :: Map Text Text - } deriving (Eq, Read, Show) - --- | 'MLModel' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'mlmAlgorithm' @::@ 'Maybe' 'Algorithm' --- --- * 'mlmCreatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'mlmCreatedByIamUser' @::@ 'Maybe' 'Text' --- --- * 'mlmEndpointInfo' @::@ 'Maybe' 'RealtimeEndpointInfo' --- --- * 'mlmInputDataLocationS3' @::@ 'Maybe' 'Text' --- --- * 'mlmLastUpdatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'mlmMLModelId' @::@ 'Maybe' 'Text' --- --- * 'mlmMLModelType' @::@ 'Maybe' 'MLModelType' --- --- * 'mlmMessage' @::@ 'Maybe' 'Text' --- --- * 'mlmName' @::@ 'Maybe' 'Text' --- --- * 'mlmScoreThreshold' @::@ 'Maybe' 'Double' --- --- * 'mlmScoreThresholdLastUpdatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'mlmSizeInBytes' @::@ 'Maybe' 'Integer' --- --- * 'mlmStatus' @::@ 'Maybe' 'EntityStatus' --- --- * 'mlmTrainingDataSourceId' @::@ 'Maybe' 'Text' --- --- * 'mlmTrainingParameters' @::@ 'HashMap' 'Text' 'Text' --- -mlmodel :: MLModel -mlmodel = MLModel - { _mlmMLModelId = Nothing - , _mlmTrainingDataSourceId = Nothing - , _mlmCreatedByIamUser = Nothing - , _mlmCreatedAt = Nothing - , _mlmLastUpdatedAt = Nothing - , _mlmName = Nothing - , _mlmStatus = Nothing - , _mlmSizeInBytes = Nothing - , _mlmEndpointInfo = Nothing - , _mlmTrainingParameters = mempty - , _mlmInputDataLocationS3 = Nothing - , _mlmAlgorithm = Nothing - , _mlmMLModelType = Nothing - , _mlmScoreThreshold = Nothing - , _mlmScoreThresholdLastUpdatedAt = Nothing - , _mlmMessage = Nothing - } - --- | The algorithm used to train the 'MLModel'. The following algorithm is supported: --- --- SGD -- Stochastic gradient descent. The goal of SGD is to minimize the --- gradient of the loss function. -mlmAlgorithm :: Lens' MLModel (Maybe Algorithm) -mlmAlgorithm = lens _mlmAlgorithm (\s a -> s { _mlmAlgorithm = a }) - --- | The time that the 'MLModel' was created. The time is expressed in epoch time. -mlmCreatedAt :: Lens' MLModel (Maybe UTCTime) -mlmCreatedAt = lens _mlmCreatedAt (\s a -> s { _mlmCreatedAt = a }) . mapping _Time - --- | The AWS user account from which the 'MLModel' was created. The account type can --- be either an AWS root account or an AWS Identity and Access Management (IAM) --- user account. -mlmCreatedByIamUser :: Lens' MLModel (Maybe Text) -mlmCreatedByIamUser = - lens _mlmCreatedByIamUser (\s a -> s { _mlmCreatedByIamUser = a }) - --- | The current endpoint of the 'MLModel'. -mlmEndpointInfo :: Lens' MLModel (Maybe RealtimeEndpointInfo) -mlmEndpointInfo = lens _mlmEndpointInfo (\s a -> s { _mlmEndpointInfo = a }) - --- | The location of the data file or directory in Amazon Simple Storage Service --- (Amazon S3). -mlmInputDataLocationS3 :: Lens' MLModel (Maybe Text) -mlmInputDataLocationS3 = - lens _mlmInputDataLocationS3 (\s a -> s { _mlmInputDataLocationS3 = a }) - --- | The time of the most recent edit to the 'MLModel'. The time is expressed in --- epoch time. -mlmLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) -mlmLastUpdatedAt = lens _mlmLastUpdatedAt (\s a -> s { _mlmLastUpdatedAt = a }) . mapping _Time - --- | The ID assigned to the 'MLModel' at creation. -mlmMLModelId :: Lens' MLModel (Maybe Text) -mlmMLModelId = lens _mlmMLModelId (\s a -> s { _mlmMLModelId = a }) - --- | Identifies the 'MLModel' category. The following are the available types: --- --- REGRESSION - Produces a numeric result. For example, "What listing price --- should a house have?". BINARY - Produces one of two possible results. For --- example, "Is this a child-friendly web site?". MULTICLASS - Produces more --- than two possible results. For example, "Is this a HIGH, LOW or MEDIUM risk --- trade?". -mlmMLModelType :: Lens' MLModel (Maybe MLModelType) -mlmMLModelType = lens _mlmMLModelType (\s a -> s { _mlmMLModelType = a }) - --- | A description of the most recent details about accessing the 'MLModel'. -mlmMessage :: Lens' MLModel (Maybe Text) -mlmMessage = lens _mlmMessage (\s a -> s { _mlmMessage = a }) - --- | A user-supplied name or description of the 'MLModel'. -mlmName :: Lens' MLModel (Maybe Text) -mlmName = lens _mlmName (\s a -> s { _mlmName = a }) - -mlmScoreThreshold :: Lens' MLModel (Maybe Double) -mlmScoreThreshold = - lens _mlmScoreThreshold (\s a -> s { _mlmScoreThreshold = a }) - --- | The time of the most recent edit to the 'ScoreThreshold'. The time is expressed --- in epoch time. -mlmScoreThresholdLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) -mlmScoreThresholdLastUpdatedAt = - lens _mlmScoreThresholdLastUpdatedAt - (\s a -> s { _mlmScoreThresholdLastUpdatedAt = a }) - . mapping _Time - -mlmSizeInBytes :: Lens' MLModel (Maybe Integer) -mlmSizeInBytes = lens _mlmSizeInBytes (\s a -> s { _mlmSizeInBytes = a }) - --- | The current status of an 'MLModel'. This element can have one of the following --- values: --- --- PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create --- an 'MLModel'. INPROGRESS - The creation process is underway. FAILED - The --- request to create an 'MLModel' did not run to completion. It is not usable. COMPLETED - The creation process completed successfully. --- DELETED - The 'MLModel' is marked as deleted. It is not usable. -mlmStatus :: Lens' MLModel (Maybe EntityStatus) -mlmStatus = lens _mlmStatus (\s a -> s { _mlmStatus = a }) - --- | The ID of the training 'DataSource'. The 'CreateMLModel' operation uses the 'TrainingDataSourceId'. -mlmTrainingDataSourceId :: Lens' MLModel (Maybe Text) -mlmTrainingDataSourceId = - lens _mlmTrainingDataSourceId (\s a -> s { _mlmTrainingDataSourceId = a }) - --- | A list of the training parameters in the 'MLModel'. The list is implemented as --- a map of key/value pairs. --- --- The following is the current set of training parameters: --- --- 'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. It --- controls overfitting the data by penalizing large coefficients. This tends to --- drive coefficients to zero, resulting in a sparse feature set. If you use --- this parameter, specify a small value, such as 1.0E-04 or 1.0E-08. --- --- The value is a double that ranges from 0 to MAX_DOUBLE. The default is not --- to use L1 normalization. The parameter cannot be used when 'L2' is specified. --- Use this parameter sparingly. --- --- 'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. It --- controls overfitting the data by penalizing large coefficients. This tends to --- drive coefficients to small, nonzero values. If you use this parameter, --- specify a small value, such as 1.0E-04 or 1.0E-08. --- --- The valus is a double that ranges from 0 to MAX_DOUBLE. The default is not --- to use L2 normalization. This cannot be used when 'L1' is specified. Use this --- parameter sparingly. --- --- 'sgd.maxPasses' - Number of times that the training process traverses the --- observations to build the 'MLModel'. The value is an integer that ranges from 1 --- to 10000. The default value is 10. --- --- 'sgd.maxMLModelSizeInBytes' - Maximum allowed size of the model. Depending on --- the input data, the model size might affect performance. --- --- The value is an integer that ranges from 100000 to 2147483648. The default --- value is 33554432. --- --- -mlmTrainingParameters :: Lens' MLModel (HashMap Text Text) -mlmTrainingParameters = - lens _mlmTrainingParameters (\s a -> s { _mlmTrainingParameters = a }) - . _Map - -instance FromJSON MLModel where - parseJSON = withObject "MLModel" $ \o -> MLModel - <$> o .:? "Algorithm" - <*> o .:? "CreatedAt" - <*> o .:? "CreatedByIamUser" - <*> o .:? "EndpointInfo" - <*> o .:? "InputDataLocationS3" - <*> o .:? "LastUpdatedAt" - <*> o .:? "MLModelId" - <*> o .:? "MLModelType" - <*> o .:? "Message" - <*> o .:? "Name" - <*> o .:? "ScoreThreshold" - <*> o .:? "ScoreThresholdLastUpdatedAt" - <*> o .:? "SizeInBytes" - <*> o .:? "Status" - <*> o .:? "TrainingDataSourceId" - <*> o .:? "TrainingParameters" .!= mempty - -instance ToJSON MLModel where - toJSON MLModel{..} = object - [ "MLModelId" .= _mlmMLModelId - , "TrainingDataSourceId" .= _mlmTrainingDataSourceId - , "CreatedByIamUser" .= _mlmCreatedByIamUser - , "CreatedAt" .= _mlmCreatedAt - , "LastUpdatedAt" .= _mlmLastUpdatedAt - , "Name" .= _mlmName - , "Status" .= _mlmStatus - , "SizeInBytes" .= _mlmSizeInBytes - , "EndpointInfo" .= _mlmEndpointInfo - , "TrainingParameters" .= _mlmTrainingParameters - , "InputDataLocationS3" .= _mlmInputDataLocationS3 - , "Algorithm" .= _mlmAlgorithm - , "MLModelType" .= _mlmMLModelType - , "ScoreThreshold" .= _mlmScoreThreshold - , "ScoreThresholdLastUpdatedAt" .= _mlmScoreThresholdLastUpdatedAt - , "Message" .= _mlmMessage - ] - -data BatchPrediction = BatchPrediction - { _bpBatchPredictionDataSourceId :: Maybe Text - , _bpBatchPredictionId :: Maybe Text - , _bpCreatedAt :: Maybe POSIX - , _bpCreatedByIamUser :: Maybe Text - , _bpInputDataLocationS3 :: Maybe Text - , _bpLastUpdatedAt :: Maybe POSIX - , _bpMLModelId :: Maybe Text - , _bpMessage :: Maybe Text - , _bpName :: Maybe Text - , _bpOutputUri :: Maybe Text - , _bpStatus :: Maybe EntityStatus - } deriving (Eq, Read, Show) - --- | 'BatchPrediction' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'bpBatchPredictionDataSourceId' @::@ 'Maybe' 'Text' --- --- * 'bpBatchPredictionId' @::@ 'Maybe' 'Text' --- --- * 'bpCreatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'bpCreatedByIamUser' @::@ 'Maybe' 'Text' --- --- * 'bpInputDataLocationS3' @::@ 'Maybe' 'Text' --- --- * 'bpLastUpdatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'bpMLModelId' @::@ 'Maybe' 'Text' --- --- * 'bpMessage' @::@ 'Maybe' 'Text' --- --- * 'bpName' @::@ 'Maybe' 'Text' --- --- * 'bpOutputUri' @::@ 'Maybe' 'Text' --- --- * 'bpStatus' @::@ 'Maybe' 'EntityStatus' --- -batchPrediction :: BatchPrediction -batchPrediction = BatchPrediction - { _bpBatchPredictionId = Nothing - , _bpMLModelId = Nothing - , _bpBatchPredictionDataSourceId = Nothing - , _bpInputDataLocationS3 = Nothing - , _bpCreatedByIamUser = Nothing - , _bpCreatedAt = Nothing - , _bpLastUpdatedAt = Nothing - , _bpName = Nothing - , _bpStatus = Nothing - , _bpOutputUri = Nothing - , _bpMessage = Nothing - } - --- | The ID of the 'DataSource' that points to the group of observations to predict. -bpBatchPredictionDataSourceId :: Lens' BatchPrediction (Maybe Text) -bpBatchPredictionDataSourceId = - lens _bpBatchPredictionDataSourceId - (\s a -> s { _bpBatchPredictionDataSourceId = a }) - --- | The ID assigned to the 'BatchPrediction' at creation. This value should be --- identical to the value of the 'BatchPredictionID' in the request. -bpBatchPredictionId :: Lens' BatchPrediction (Maybe Text) -bpBatchPredictionId = - lens _bpBatchPredictionId (\s a -> s { _bpBatchPredictionId = a }) - --- | The time that the 'BatchPrediction' was created. The time is expressed in epoch --- time. -bpCreatedAt :: Lens' BatchPrediction (Maybe UTCTime) -bpCreatedAt = lens _bpCreatedAt (\s a -> s { _bpCreatedAt = a }) . mapping _Time - --- | The AWS user account that invoked the 'BatchPrediction'. The account type can --- be either an AWS root account or an AWS Identity and Access Management (IAM) --- user account. -bpCreatedByIamUser :: Lens' BatchPrediction (Maybe Text) -bpCreatedByIamUser = - lens _bpCreatedByIamUser (\s a -> s { _bpCreatedByIamUser = a }) - --- | The location of the data file or directory in Amazon Simple Storage Service --- (Amazon S3). -bpInputDataLocationS3 :: Lens' BatchPrediction (Maybe Text) -bpInputDataLocationS3 = - lens _bpInputDataLocationS3 (\s a -> s { _bpInputDataLocationS3 = a }) - --- | The time of the most recent edit to the 'BatchPrediction'. The time is --- expressed in epoch time. -bpLastUpdatedAt :: Lens' BatchPrediction (Maybe UTCTime) -bpLastUpdatedAt = lens _bpLastUpdatedAt (\s a -> s { _bpLastUpdatedAt = a }) . mapping _Time - --- | The ID of the 'MLModel' that generated predictions for the 'BatchPrediction' --- request. -bpMLModelId :: Lens' BatchPrediction (Maybe Text) -bpMLModelId = lens _bpMLModelId (\s a -> s { _bpMLModelId = a }) - --- | A description of the most recent details about processing the batch --- prediction request. -bpMessage :: Lens' BatchPrediction (Maybe Text) -bpMessage = lens _bpMessage (\s a -> s { _bpMessage = a }) - --- | A user-supplied name or description of the 'BatchPrediction'. -bpName :: Lens' BatchPrediction (Maybe Text) -bpName = lens _bpName (\s a -> s { _bpName = a }) - --- | The location of an Amazon S3 bucket or directory to receive the operation --- results. The following substrings are not allowed in the s3 key portion of --- the "outputURI" field: ':', '//', '/./', '/../'. -bpOutputUri :: Lens' BatchPrediction (Maybe Text) -bpOutputUri = lens _bpOutputUri (\s a -> s { _bpOutputUri = a }) - --- | The status of the 'BatchPrediction'. This element can have one of the following --- values: --- --- 'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request to --- generate predictions for a batch of observations. 'INPROGRESS' - The process --- is underway. 'FAILED' - The request to peform a batch prediction did not run --- to completion. It is not usable. 'COMPLETED' - The batch prediction process --- completed successfully. 'DELETED' - The 'BatchPrediction' is marked as deleted. --- It is not usable. -bpStatus :: Lens' BatchPrediction (Maybe EntityStatus) -bpStatus = lens _bpStatus (\s a -> s { _bpStatus = a }) - -instance FromJSON BatchPrediction where - parseJSON = withObject "BatchPrediction" $ \o -> BatchPrediction - <$> o .:? "BatchPredictionDataSourceId" - <*> o .:? "BatchPredictionId" - <*> o .:? "CreatedAt" - <*> o .:? "CreatedByIamUser" - <*> o .:? "InputDataLocationS3" - <*> o .:? "LastUpdatedAt" - <*> o .:? "MLModelId" - <*> o .:? "Message" - <*> o .:? "Name" - <*> o .:? "OutputUri" - <*> o .:? "Status" - -instance ToJSON BatchPrediction where - toJSON BatchPrediction{..} = object - [ "BatchPredictionId" .= _bpBatchPredictionId - , "MLModelId" .= _bpMLModelId - , "BatchPredictionDataSourceId" .= _bpBatchPredictionDataSourceId - , "InputDataLocationS3" .= _bpInputDataLocationS3 - , "CreatedByIamUser" .= _bpCreatedByIamUser - , "CreatedAt" .= _bpCreatedAt - , "LastUpdatedAt" .= _bpLastUpdatedAt - , "Name" .= _bpName - , "Status" .= _bpStatus - , "OutputUri" .= _bpOutputUri - , "Message" .= _bpMessage - ] - -data SortOrder - = Asc -- ^ asc - | Dsc -- ^ dsc - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable SortOrder - -instance FromText SortOrder where - parser = takeLowerText >>= \case - "asc" -> pure Asc - "dsc" -> pure Dsc - e -> fail $ - "Failure parsing SortOrder from " ++ show e - -instance ToText SortOrder where - toText = \case - Asc -> "asc" - Dsc -> "dsc" - -instance ToByteString SortOrder -instance ToHeader SortOrder -instance ToQuery SortOrder - -instance FromJSON SortOrder where - parseJSON = parseJSONText "SortOrder" - -instance ToJSON SortOrder where - toJSON = toJSONText - -data Algorithm - = Sgd -- ^ sgd - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable Algorithm - -instance FromText Algorithm where - parser = takeLowerText >>= \case - "sgd" -> pure Sgd - e -> fail $ - "Failure parsing Algorithm from " ++ show e - -instance ToText Algorithm where - toText Sgd = "sgd" - -instance ToByteString Algorithm -instance ToHeader Algorithm -instance ToQuery Algorithm - -instance FromJSON Algorithm where - parseJSON = parseJSONText "Algorithm" - -instance ToJSON Algorithm where - toJSON = toJSONText - -data EntityStatus - = ESCompleted -- ^ COMPLETED - | ESDeleted -- ^ DELETED - | ESFailed -- ^ FAILED - | ESInprogress -- ^ INPROGRESS - | ESPending -- ^ PENDING - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable EntityStatus - -instance FromText EntityStatus where - parser = takeLowerText >>= \case - "completed" -> pure ESCompleted - "deleted" -> pure ESDeleted - "failed" -> pure ESFailed - "inprogress" -> pure ESInprogress - "pending" -> pure ESPending - e -> fail $ - "Failure parsing EntityStatus from " ++ show e - -instance ToText EntityStatus where - toText = \case - ESCompleted -> "COMPLETED" - ESDeleted -> "DELETED" - ESFailed -> "FAILED" - ESInprogress -> "INPROGRESS" - ESPending -> "PENDING" - -instance ToByteString EntityStatus -instance ToHeader EntityStatus -instance ToQuery EntityStatus - -instance FromJSON EntityStatus where - parseJSON = parseJSONText "EntityStatus" - -instance ToJSON EntityStatus where - toJSON = toJSONText - -data DataSource = DataSource - { _dsComputeStatistics :: Maybe Bool - , _dsCreatedAt :: Maybe POSIX - , _dsCreatedByIamUser :: Maybe Text - , _dsDataLocationS3 :: Maybe Text - , _dsDataRearrangement :: Maybe Text - , _dsDataSizeInBytes :: Maybe Integer - , _dsDataSourceId :: Maybe Text - , _dsLastUpdatedAt :: Maybe POSIX - , _dsMessage :: Maybe Text - , _dsName :: Maybe Text - , _dsNumberOfFiles :: Maybe Integer - , _dsRDSMetadata :: Maybe RDSMetadata - , _dsRedshiftMetadata :: Maybe RedshiftMetadata - , _dsRoleARN :: Maybe Text - , _dsStatus :: Maybe EntityStatus - } deriving (Eq, Read, Show) - --- | 'DataSource' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'dsComputeStatistics' @::@ 'Maybe' 'Bool' --- --- * 'dsCreatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'dsCreatedByIamUser' @::@ 'Maybe' 'Text' --- --- * 'dsDataLocationS3' @::@ 'Maybe' 'Text' --- --- * 'dsDataRearrangement' @::@ 'Maybe' 'Text' --- --- * 'dsDataSizeInBytes' @::@ 'Maybe' 'Integer' --- --- * 'dsDataSourceId' @::@ 'Maybe' 'Text' --- --- * 'dsLastUpdatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'dsMessage' @::@ 'Maybe' 'Text' --- --- * 'dsName' @::@ 'Maybe' 'Text' --- --- * 'dsNumberOfFiles' @::@ 'Maybe' 'Integer' --- --- * 'dsRDSMetadata' @::@ 'Maybe' 'RDSMetadata' --- --- * 'dsRedshiftMetadata' @::@ 'Maybe' 'RedshiftMetadata' --- --- * 'dsRoleARN' @::@ 'Maybe' 'Text' --- --- * 'dsStatus' @::@ 'Maybe' 'EntityStatus' --- -dataSource :: DataSource -dataSource = DataSource - { _dsDataSourceId = Nothing - , _dsDataLocationS3 = Nothing - , _dsDataRearrangement = Nothing - , _dsCreatedByIamUser = Nothing - , _dsCreatedAt = Nothing - , _dsLastUpdatedAt = Nothing - , _dsDataSizeInBytes = Nothing - , _dsNumberOfFiles = Nothing - , _dsName = Nothing - , _dsStatus = Nothing - , _dsMessage = Nothing - , _dsRedshiftMetadata = Nothing - , _dsRDSMetadata = Nothing - , _dsRoleARN = Nothing - , _dsComputeStatistics = Nothing - } - --- | The parameter is 'true' if statistics need to be generated from the --- observation data. -dsComputeStatistics :: Lens' DataSource (Maybe Bool) -dsComputeStatistics = - lens _dsComputeStatistics (\s a -> s { _dsComputeStatistics = a }) - --- | The time that the 'DataSource' was created. The time is expressed in epoch time. -dsCreatedAt :: Lens' DataSource (Maybe UTCTime) -dsCreatedAt = lens _dsCreatedAt (\s a -> s { _dsCreatedAt = a }) . mapping _Time - --- | The AWS user account from which the 'DataSource' was created. The account type --- can be either an AWS root account or an AWS Identity and Access Management --- (IAM) user account. -dsCreatedByIamUser :: Lens' DataSource (Maybe Text) -dsCreatedByIamUser = - lens _dsCreatedByIamUser (\s a -> s { _dsCreatedByIamUser = a }) - --- | The location and name of the data in Amazon Simple Storage Service (Amazon --- S3) that is used by a 'DataSource'. -dsDataLocationS3 :: Lens' DataSource (Maybe Text) -dsDataLocationS3 = lens _dsDataLocationS3 (\s a -> s { _dsDataLocationS3 = a }) - --- | A JSON string that represents the splitting requirement of a 'Datasource'. -dsDataRearrangement :: Lens' DataSource (Maybe Text) -dsDataRearrangement = - lens _dsDataRearrangement (\s a -> s { _dsDataRearrangement = a }) - --- | The total number of observations contained in the data files that the 'DataSource' references. -dsDataSizeInBytes :: Lens' DataSource (Maybe Integer) -dsDataSizeInBytes = - lens _dsDataSizeInBytes (\s a -> s { _dsDataSizeInBytes = a }) - --- | The ID that is assigned to the 'DataSource' during creation. -dsDataSourceId :: Lens' DataSource (Maybe Text) -dsDataSourceId = lens _dsDataSourceId (\s a -> s { _dsDataSourceId = a }) - --- | The time of the most recent edit to the 'BatchPrediction'. The time is --- expressed in epoch time. -dsLastUpdatedAt :: Lens' DataSource (Maybe UTCTime) -dsLastUpdatedAt = lens _dsLastUpdatedAt (\s a -> s { _dsLastUpdatedAt = a }) . mapping _Time - --- | A description of the most recent details about creating the 'DataSource'. -dsMessage :: Lens' DataSource (Maybe Text) -dsMessage = lens _dsMessage (\s a -> s { _dsMessage = a }) - --- | A user-supplied name or description of the 'DataSource'. -dsName :: Lens' DataSource (Maybe Text) -dsName = lens _dsName (\s a -> s { _dsName = a }) - --- | The number of data files referenced by the 'DataSource'. -dsNumberOfFiles :: Lens' DataSource (Maybe Integer) -dsNumberOfFiles = lens _dsNumberOfFiles (\s a -> s { _dsNumberOfFiles = a }) - -dsRDSMetadata :: Lens' DataSource (Maybe RDSMetadata) -dsRDSMetadata = lens _dsRDSMetadata (\s a -> s { _dsRDSMetadata = a }) - -dsRedshiftMetadata :: Lens' DataSource (Maybe RedshiftMetadata) -dsRedshiftMetadata = - lens _dsRedshiftMetadata (\s a -> s { _dsRedshiftMetadata = a }) - -dsRoleARN :: Lens' DataSource (Maybe Text) -dsRoleARN = lens _dsRoleARN (\s a -> s { _dsRoleARN = a }) - --- | The current status of the 'DataSource'. This element can have one of the --- following values: --- --- PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create --- a 'DataSource'. INPROGRESS - The creation process is underway. FAILED - The --- request to create a 'DataSource' did not run to completion. It is not usable. COMPLETED - The creation process completed successfully. --- DELETED - The 'DataSource' is marked as deleted. It is not usable. -dsStatus :: Lens' DataSource (Maybe EntityStatus) -dsStatus = lens _dsStatus (\s a -> s { _dsStatus = a }) - -instance FromJSON DataSource where - parseJSON = withObject "DataSource" $ \o -> DataSource - <$> o .:? "ComputeStatistics" - <*> o .:? "CreatedAt" - <*> o .:? "CreatedByIamUser" - <*> o .:? "DataLocationS3" - <*> o .:? "DataRearrangement" - <*> o .:? "DataSizeInBytes" - <*> o .:? "DataSourceId" - <*> o .:? "LastUpdatedAt" - <*> o .:? "Message" - <*> o .:? "Name" - <*> o .:? "NumberOfFiles" - <*> o .:? "RDSMetadata" - <*> o .:? "RedshiftMetadata" - <*> o .:? "RoleARN" - <*> o .:? "Status" - -instance ToJSON DataSource where - toJSON DataSource{..} = object - [ "DataSourceId" .= _dsDataSourceId - , "DataLocationS3" .= _dsDataLocationS3 - , "DataRearrangement" .= _dsDataRearrangement - , "CreatedByIamUser" .= _dsCreatedByIamUser - , "CreatedAt" .= _dsCreatedAt - , "LastUpdatedAt" .= _dsLastUpdatedAt - , "DataSizeInBytes" .= _dsDataSizeInBytes - , "NumberOfFiles" .= _dsNumberOfFiles - , "Name" .= _dsName - , "Status" .= _dsStatus - , "Message" .= _dsMessage - , "RedshiftMetadata" .= _dsRedshiftMetadata - , "RDSMetadata" .= _dsRDSMetadata - , "RoleARN" .= _dsRoleARN - , "ComputeStatistics" .= _dsComputeStatistics - ] - -data RDSDatabase = RDSDatabase - { _rdsdDatabaseName :: Text - , _rdsdInstanceIdentifier :: Text - } deriving (Eq, Ord, Read, Show) - --- | 'RDSDatabase' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'rdsdDatabaseName' @::@ 'Text' --- --- * 'rdsdInstanceIdentifier' @::@ 'Text' --- -rdsdatabase :: Text -- ^ 'rdsdInstanceIdentifier' - -> Text -- ^ 'rdsdDatabaseName' - -> RDSDatabase -rdsdatabase p1 p2 = RDSDatabase - { _rdsdInstanceIdentifier = p1 - , _rdsdDatabaseName = p2 - } - -rdsdDatabaseName :: Lens' RDSDatabase Text -rdsdDatabaseName = lens _rdsdDatabaseName (\s a -> s { _rdsdDatabaseName = a }) - --- | The ID of an RDS DB instance. -rdsdInstanceIdentifier :: Lens' RDSDatabase Text -rdsdInstanceIdentifier = - lens _rdsdInstanceIdentifier (\s a -> s { _rdsdInstanceIdentifier = a }) - -instance FromJSON RDSDatabase where - parseJSON = withObject "RDSDatabase" $ \o -> RDSDatabase - <$> o .: "DatabaseName" - <*> o .: "InstanceIdentifier" - -instance ToJSON RDSDatabase where - toJSON RDSDatabase{..} = object - [ "InstanceIdentifier" .= _rdsdInstanceIdentifier - , "DatabaseName" .= _rdsdDatabaseName - ] - -data RDSDatabaseCredentials = RDSDatabaseCredentials - { _rdsdcPassword :: Text - , _rdsdcUsername :: Text - } deriving (Eq, Ord, Read, Show) - --- | 'RDSDatabaseCredentials' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'rdsdcPassword' @::@ 'Text' --- --- * 'rdsdcUsername' @::@ 'Text' --- -rdsdatabaseCredentials :: Text -- ^ 'rdsdcUsername' - -> Text -- ^ 'rdsdcPassword' - -> RDSDatabaseCredentials -rdsdatabaseCredentials p1 p2 = RDSDatabaseCredentials - { _rdsdcUsername = p1 - , _rdsdcPassword = p2 - } - -rdsdcPassword :: Lens' RDSDatabaseCredentials Text -rdsdcPassword = lens _rdsdcPassword (\s a -> s { _rdsdcPassword = a }) - -rdsdcUsername :: Lens' RDSDatabaseCredentials Text -rdsdcUsername = lens _rdsdcUsername (\s a -> s { _rdsdcUsername = a }) - -instance FromJSON RDSDatabaseCredentials where - parseJSON = withObject "RDSDatabaseCredentials" $ \o -> RDSDatabaseCredentials - <$> o .: "Password" - <*> o .: "Username" - -instance ToJSON RDSDatabaseCredentials where - toJSON RDSDatabaseCredentials{..} = object - [ "Username" .= _rdsdcUsername - , "Password" .= _rdsdcPassword - ] - -data MLModelFilterVariable - = MLMFVAlgorithm -- ^ Algorithm - | MLMFVCreatedAt -- ^ CreatedAt - | MLMFVIAMUser -- ^ IAMUser - | MLMFVLastUpdatedAt -- ^ LastUpdatedAt - | MLMFVMLModelType -- ^ MLModelType - | MLMFVName -- ^ Name - | MLMFVRealtimeEndpointStatus -- ^ RealtimeEndpointStatus - | MLMFVStatus -- ^ Status - | MLMFVTrainingDataSourceId -- ^ TrainingDataSourceId - | MLMFVTrainingDataURI -- ^ TrainingDataURI - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable MLModelFilterVariable - -instance FromText MLModelFilterVariable where - parser = takeLowerText >>= \case - "algorithm" -> pure MLMFVAlgorithm - "createdat" -> pure MLMFVCreatedAt - "iamuser" -> pure MLMFVIAMUser - "lastupdatedat" -> pure MLMFVLastUpdatedAt - "mlmodeltype" -> pure MLMFVMLModelType - "name" -> pure MLMFVName - "realtimeendpointstatus" -> pure MLMFVRealtimeEndpointStatus - "status" -> pure MLMFVStatus - "trainingdatasourceid" -> pure MLMFVTrainingDataSourceId - "trainingdatauri" -> pure MLMFVTrainingDataURI - e -> fail $ - "Failure parsing MLModelFilterVariable from " ++ show e - -instance ToText MLModelFilterVariable where - toText = \case - MLMFVAlgorithm -> "Algorithm" - MLMFVCreatedAt -> "CreatedAt" - MLMFVIAMUser -> "IAMUser" - MLMFVLastUpdatedAt -> "LastUpdatedAt" - MLMFVMLModelType -> "MLModelType" - MLMFVName -> "Name" - MLMFVRealtimeEndpointStatus -> "RealtimeEndpointStatus" - MLMFVStatus -> "Status" - MLMFVTrainingDataSourceId -> "TrainingDataSourceId" - MLMFVTrainingDataURI -> "TrainingDataURI" - -instance ToByteString MLModelFilterVariable -instance ToHeader MLModelFilterVariable -instance ToQuery MLModelFilterVariable - -instance FromJSON MLModelFilterVariable where - parseJSON = parseJSONText "MLModelFilterVariable" - -instance ToJSON MLModelFilterVariable where - toJSON = toJSONText - -data DataSourceFilterVariable - = DataCreatedAt -- ^ CreatedAt - | DataDataLocationS3 -- ^ DataLocationS3 - | DataIAMUser -- ^ IAMUser - | DataLastUpdatedAt -- ^ LastUpdatedAt - | DataName -- ^ Name - | DataStatus -- ^ Status - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable DataSourceFilterVariable - -instance FromText DataSourceFilterVariable where - parser = takeLowerText >>= \case - "createdat" -> pure DataCreatedAt - "datalocations3" -> pure DataDataLocationS3 - "iamuser" -> pure DataIAMUser - "lastupdatedat" -> pure DataLastUpdatedAt - "name" -> pure DataName - "status" -> pure DataStatus - e -> fail $ - "Failure parsing DataSourceFilterVariable from " ++ show e - -instance ToText DataSourceFilterVariable where - toText = \case - DataCreatedAt -> "CreatedAt" - DataDataLocationS3 -> "DataLocationS3" - DataIAMUser -> "IAMUser" - DataLastUpdatedAt -> "LastUpdatedAt" - DataName -> "Name" - DataStatus -> "Status" - -instance ToByteString DataSourceFilterVariable -instance ToHeader DataSourceFilterVariable -instance ToQuery DataSourceFilterVariable - -instance FromJSON DataSourceFilterVariable where - parseJSON = parseJSONText "DataSourceFilterVariable" - -instance ToJSON DataSourceFilterVariable where - toJSON = toJSONText - -data RedshiftDataSpec = RedshiftDataSpec - { _rdsDataRearrangement :: Maybe Text - , _rdsDataSchema :: Maybe Text - , _rdsDataSchemaUri :: Maybe Text - , _rdsDatabaseCredentials :: RedshiftDatabaseCredentials - , _rdsDatabaseInformation :: RedshiftDatabase - , _rdsS3StagingLocation :: Text - , _rdsSelectSqlQuery :: Text - } deriving (Eq, Read, Show) - --- | 'RedshiftDataSpec' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'rdsDataRearrangement' @::@ 'Maybe' 'Text' --- --- * 'rdsDataSchema' @::@ 'Maybe' 'Text' --- --- * 'rdsDataSchemaUri' @::@ 'Maybe' 'Text' --- --- * 'rdsDatabaseCredentials' @::@ 'RedshiftDatabaseCredentials' --- --- * 'rdsDatabaseInformation' @::@ 'RedshiftDatabase' --- --- * 'rdsS3StagingLocation' @::@ 'Text' --- --- * 'rdsSelectSqlQuery' @::@ 'Text' --- -redshiftDataSpec :: RedshiftDatabase -- ^ 'rdsDatabaseInformation' - -> Text -- ^ 'rdsSelectSqlQuery' - -> RedshiftDatabaseCredentials -- ^ 'rdsDatabaseCredentials' - -> Text -- ^ 'rdsS3StagingLocation' - -> RedshiftDataSpec -redshiftDataSpec p1 p2 p3 p4 = RedshiftDataSpec - { _rdsDatabaseInformation = p1 - , _rdsSelectSqlQuery = p2 - , _rdsDatabaseCredentials = p3 - , _rdsS3StagingLocation = p4 - , _rdsDataRearrangement = Nothing - , _rdsDataSchema = Nothing - , _rdsDataSchemaUri = Nothing - } - --- | Describes the splitting specifications for a 'DataSource'. -rdsDataRearrangement :: Lens' RedshiftDataSpec (Maybe Text) -rdsDataRearrangement = - lens _rdsDataRearrangement (\s a -> s { _rdsDataRearrangement = a }) - --- | Describes the schema for an Amazon Redshift 'DataSource'. -rdsDataSchema :: Lens' RedshiftDataSpec (Maybe Text) -rdsDataSchema = lens _rdsDataSchema (\s a -> s { _rdsDataSchema = a }) - --- | Describes the schema location for an Amazon Redshift 'DataSource'. -rdsDataSchemaUri :: Lens' RedshiftDataSpec (Maybe Text) -rdsDataSchemaUri = lens _rdsDataSchemaUri (\s a -> s { _rdsDataSchemaUri = a }) - --- | Describes AWS Identity and Access Management (IAM) credentials that are used --- connect to the Amazon Redshift database. -rdsDatabaseCredentials :: Lens' RedshiftDataSpec RedshiftDatabaseCredentials -rdsDatabaseCredentials = - lens _rdsDatabaseCredentials (\s a -> s { _rdsDatabaseCredentials = a }) - --- | Describes the 'DatabaseName' and 'ClusterIdentifier' for an Amazon Redshift 'DataSource'. -rdsDatabaseInformation :: Lens' RedshiftDataSpec RedshiftDatabase -rdsDatabaseInformation = - lens _rdsDatabaseInformation (\s a -> s { _rdsDatabaseInformation = a }) - --- | Describes an Amazon S3 location to store the result set of the 'SelectSqlQuery' --- query. -rdsS3StagingLocation :: Lens' RedshiftDataSpec Text -rdsS3StagingLocation = - lens _rdsS3StagingLocation (\s a -> s { _rdsS3StagingLocation = a }) - --- | Describes the SQL Query to execute on an Amazon Redshift database for an --- Amazon Redshift 'DataSource'. -rdsSelectSqlQuery :: Lens' RedshiftDataSpec Text -rdsSelectSqlQuery = - lens _rdsSelectSqlQuery (\s a -> s { _rdsSelectSqlQuery = a }) - -instance FromJSON RedshiftDataSpec where - parseJSON = withObject "RedshiftDataSpec" $ \o -> RedshiftDataSpec - <$> o .:? "DataRearrangement" - <*> o .:? "DataSchema" - <*> o .:? "DataSchemaUri" - <*> o .: "DatabaseCredentials" - <*> o .: "DatabaseInformation" - <*> o .: "S3StagingLocation" - <*> o .: "SelectSqlQuery" - -instance ToJSON RedshiftDataSpec where - toJSON RedshiftDataSpec{..} = object - [ "DatabaseInformation" .= _rdsDatabaseInformation - , "SelectSqlQuery" .= _rdsSelectSqlQuery - , "DatabaseCredentials" .= _rdsDatabaseCredentials - , "S3StagingLocation" .= _rdsS3StagingLocation - , "DataRearrangement" .= _rdsDataRearrangement - , "DataSchema" .= _rdsDataSchema - , "DataSchemaUri" .= _rdsDataSchemaUri - ] - -data Evaluation = Evaluation - { _eCreatedAt :: Maybe POSIX - , _eCreatedByIamUser :: Maybe Text - , _eEvaluationDataSourceId :: Maybe Text - , _eEvaluationId :: Maybe Text - , _eInputDataLocationS3 :: Maybe Text - , _eLastUpdatedAt :: Maybe POSIX - , _eMLModelId :: Maybe Text - , _eMessage :: Maybe Text - , _eName :: Maybe Text - , _ePerformanceMetrics :: Maybe PerformanceMetrics - , _eStatus :: Maybe EntityStatus - } deriving (Eq, Read, Show) - --- | 'Evaluation' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'eCreatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'eCreatedByIamUser' @::@ 'Maybe' 'Text' --- --- * 'eEvaluationDataSourceId' @::@ 'Maybe' 'Text' --- --- * 'eEvaluationId' @::@ 'Maybe' 'Text' --- --- * 'eInputDataLocationS3' @::@ 'Maybe' 'Text' --- --- * 'eLastUpdatedAt' @::@ 'Maybe' 'UTCTime' --- --- * 'eMLModelId' @::@ 'Maybe' 'Text' --- --- * 'eMessage' @::@ 'Maybe' 'Text' --- --- * 'eName' @::@ 'Maybe' 'Text' --- --- * 'ePerformanceMetrics' @::@ 'Maybe' 'PerformanceMetrics' --- --- * 'eStatus' @::@ 'Maybe' 'EntityStatus' --- -evaluation :: Evaluation -evaluation = Evaluation - { _eEvaluationId = Nothing - , _eMLModelId = Nothing - , _eEvaluationDataSourceId = Nothing - , _eInputDataLocationS3 = Nothing - , _eCreatedByIamUser = Nothing - , _eCreatedAt = Nothing - , _eLastUpdatedAt = Nothing - , _eName = Nothing - , _eStatus = Nothing - , _ePerformanceMetrics = Nothing - , _eMessage = Nothing - } - --- | The time that the 'Evaluation' was created. The time is expressed in epoch time. -eCreatedAt :: Lens' Evaluation (Maybe UTCTime) -eCreatedAt = lens _eCreatedAt (\s a -> s { _eCreatedAt = a }) . mapping _Time - --- | The AWS user account that invoked the evaluation. The account type can be --- either an AWS root account or an AWS Identity and Access Management (IAM) --- user account. -eCreatedByIamUser :: Lens' Evaluation (Maybe Text) -eCreatedByIamUser = - lens _eCreatedByIamUser (\s a -> s { _eCreatedByIamUser = a }) - --- | The ID of the 'DataSource' that is used to evaluate the 'MLModel'. -eEvaluationDataSourceId :: Lens' Evaluation (Maybe Text) -eEvaluationDataSourceId = - lens _eEvaluationDataSourceId (\s a -> s { _eEvaluationDataSourceId = a }) - --- | The ID that is assigned to the 'Evaluation' at creation. -eEvaluationId :: Lens' Evaluation (Maybe Text) -eEvaluationId = lens _eEvaluationId (\s a -> s { _eEvaluationId = a }) - --- | The location and name of the data in Amazon Simple Storage Server (Amazon S3) --- that is used in the evaluation. -eInputDataLocationS3 :: Lens' Evaluation (Maybe Text) -eInputDataLocationS3 = - lens _eInputDataLocationS3 (\s a -> s { _eInputDataLocationS3 = a }) - --- | The time of the most recent edit to the 'Evaluation'. The time is expressed in --- epoch time. -eLastUpdatedAt :: Lens' Evaluation (Maybe UTCTime) -eLastUpdatedAt = lens _eLastUpdatedAt (\s a -> s { _eLastUpdatedAt = a }) . mapping _Time - --- | The ID of the 'MLModel' that is the focus of the evaluation. -eMLModelId :: Lens' Evaluation (Maybe Text) -eMLModelId = lens _eMLModelId (\s a -> s { _eMLModelId = a }) - --- | A description of the most recent details about evaluating the 'MLModel'. -eMessage :: Lens' Evaluation (Maybe Text) -eMessage = lens _eMessage (\s a -> s { _eMessage = a }) - --- | A user-supplied name or description of the 'Evaluation'. -eName :: Lens' Evaluation (Maybe Text) -eName = lens _eName (\s a -> s { _eName = a }) - --- | Measurements of how well the 'MLModel' performed, using observations referenced --- by the 'DataSource'. One of the following metrics is returned, based on the --- type of the MLModel: --- --- BinaryAUC: A binary 'MLModel' uses the Area Under the Curve (AUC) technique --- to measure performance. --- --- RegressionRMSE: A regression 'MLModel' uses the Root Mean Square Error --- (RMSE) technique to measure performance. RMSE measures the difference between --- predicted and actual values for a single variable. --- --- MulticlassAvgFScore: A multiclass 'MLModel' uses the F1 score technique to --- measure performance. --- --- For more information about performance metrics, please see the . -ePerformanceMetrics :: Lens' Evaluation (Maybe PerformanceMetrics) -ePerformanceMetrics = - lens _ePerformanceMetrics (\s a -> s { _ePerformanceMetrics = a }) - --- | The status of the evaluation. This element can have one of the following --- values: --- --- 'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request to --- evaluate an 'MLModel'. 'INPROGRESS' - The evaluation is underway. 'FAILED' - The --- request to evaluate an 'MLModel' did not run to completion. It is not usable. 'COMPLETED' - The evaluation process completed successfully. 'DELETED' - The 'Evaluation' --- is marked as deleted. It is not usable. -eStatus :: Lens' Evaluation (Maybe EntityStatus) -eStatus = lens _eStatus (\s a -> s { _eStatus = a }) - -instance FromJSON Evaluation where - parseJSON = withObject "Evaluation" $ \o -> Evaluation - <$> o .:? "CreatedAt" - <*> o .:? "CreatedByIamUser" - <*> o .:? "EvaluationDataSourceId" - <*> o .:? "EvaluationId" - <*> o .:? "InputDataLocationS3" - <*> o .:? "LastUpdatedAt" - <*> o .:? "MLModelId" - <*> o .:? "Message" - <*> o .:? "Name" - <*> o .:? "PerformanceMetrics" - <*> o .:? "Status" - -instance ToJSON Evaluation where - toJSON Evaluation{..} = object - [ "EvaluationId" .= _eEvaluationId - , "MLModelId" .= _eMLModelId - , "EvaluationDataSourceId" .= _eEvaluationDataSourceId - , "InputDataLocationS3" .= _eInputDataLocationS3 - , "CreatedByIamUser" .= _eCreatedByIamUser - , "CreatedAt" .= _eCreatedAt - , "LastUpdatedAt" .= _eLastUpdatedAt - , "Name" .= _eName - , "Status" .= _eStatus - , "PerformanceMetrics" .= _ePerformanceMetrics - , "Message" .= _eMessage - ] - -data RedshiftMetadata = RedshiftMetadata - { _rmDatabaseUserName :: Maybe Text - , _rmRedshiftDatabase :: Maybe RedshiftDatabase - , _rmSelectSqlQuery :: Maybe Text - } deriving (Eq, Read, Show) - --- | 'RedshiftMetadata' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'rmDatabaseUserName' @::@ 'Maybe' 'Text' --- --- * 'rmRedshiftDatabase' @::@ 'Maybe' 'RedshiftDatabase' --- --- * 'rmSelectSqlQuery' @::@ 'Maybe' 'Text' --- -redshiftMetadata :: RedshiftMetadata -redshiftMetadata = RedshiftMetadata - { _rmRedshiftDatabase = Nothing - , _rmDatabaseUserName = Nothing - , _rmSelectSqlQuery = Nothing - } - -rmDatabaseUserName :: Lens' RedshiftMetadata (Maybe Text) -rmDatabaseUserName = - lens _rmDatabaseUserName (\s a -> s { _rmDatabaseUserName = a }) - -rmRedshiftDatabase :: Lens' RedshiftMetadata (Maybe RedshiftDatabase) -rmRedshiftDatabase = - lens _rmRedshiftDatabase (\s a -> s { _rmRedshiftDatabase = a }) - --- | The SQL query that is specified during 'CreateDataSourceFromRedshift'. Returns --- only if 'Verbose' is true in GetDataSourceInput. -rmSelectSqlQuery :: Lens' RedshiftMetadata (Maybe Text) -rmSelectSqlQuery = lens _rmSelectSqlQuery (\s a -> s { _rmSelectSqlQuery = a }) - -instance FromJSON RedshiftMetadata where - parseJSON = withObject "RedshiftMetadata" $ \o -> RedshiftMetadata - <$> o .:? "DatabaseUserName" - <*> o .:? "RedshiftDatabase" - <*> o .:? "SelectSqlQuery" - -instance ToJSON RedshiftMetadata where - toJSON RedshiftMetadata{..} = object - [ "RedshiftDatabase" .= _rmRedshiftDatabase - , "DatabaseUserName" .= _rmDatabaseUserName - , "SelectSqlQuery" .= _rmSelectSqlQuery - ] - -data MLModelType - = Binary -- ^ BINARY - | Multiclass -- ^ MULTICLASS - | Regression -- ^ REGRESSION - deriving (Eq, Ord, Read, Show, Generic, Enum) - -instance Hashable MLModelType - -instance FromText MLModelType where - parser = takeLowerText >>= \case - "binary" -> pure Binary - "multiclass" -> pure Multiclass - "regression" -> pure Regression - e -> fail $ - "Failure parsing MLModelType from " ++ show e - -instance ToText MLModelType where - toText = \case - Binary -> "BINARY" - Multiclass -> "MULTICLASS" - Regression -> "REGRESSION" - -instance ToByteString MLModelType -instance ToHeader MLModelType -instance ToQuery MLModelType - -instance FromJSON MLModelType where - parseJSON = parseJSONText "MLModelType" - -instance ToJSON MLModelType where - toJSON = toJSONText +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE TypeFamilies #-} + +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | +-- Module : Network.AWS.MachineLearning.Types +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. +-- Maintainer : Brendan Hay +-- Stability : auto-generated +-- Portability : non-portable (GHC extensions) +-- +module Network.AWS.MachineLearning.Types + ( + -- * Service + MachineLearning + + -- * Errors + , _InternalServerException + , _InvalidInputException + , _IdempotentParameterMismatchException + , _PredictorNotMountedException + , _ResourceNotFoundException + , _LimitExceededException + + -- * Algorithm + , Algorithm (..) + + -- * BatchPredictionFilterVariable + , BatchPredictionFilterVariable (..) + + -- * DataSourceFilterVariable + , DataSourceFilterVariable (..) + + -- * DetailsAttributes + , DetailsAttributes (..) + + -- * EntityStatus + , EntityStatus (..) + + -- * EvaluationFilterVariable + , EvaluationFilterVariable (..) + + -- * MLModelFilterVariable + , MLModelFilterVariable (..) + + -- * MLModelType + , MLModelType (..) + + -- * RealtimeEndpointStatus + , RealtimeEndpointStatus (..) + + -- * SortOrder + , SortOrder (..) + + -- * BatchPrediction + , BatchPrediction + , batchPrediction + , bpStatus + , bpLastUpdatedAt + , bpCreatedAt + , bpInputDataLocationS3 + , bpMLModelId + , bpBatchPredictionDataSourceId + , bpBatchPredictionId + , bpName + , bpCreatedByIAMUser + , bpMessage + , bpOutputURI + + -- * DataSource + , DataSource + , dataSource + , dsStatus + , dsNumberOfFiles + , dsLastUpdatedAt + , dsCreatedAt + , dsRDSMetadata + , dsDataSourceId + , dsDataSizeInBytes + , dsName + , dsCreatedByIAMUser + , dsDataLocationS3 + , dsComputeStatistics + , dsMessage + , dsRedshiftMetadata + , dsRoleARN + , dsDataRearrangement + + -- * Evaluation + , Evaluation + , evaluation + , eStatus + , ePerformanceMetrics + , eLastUpdatedAt + , eCreatedAt + , eInputDataLocationS3 + , eMLModelId + , eName + , eCreatedByIAMUser + , eMessage + , eEvaluationId + , eEvaluationDataSourceId + + -- * MLModel + , MLModel + , mLModel + , mlmStatus + , mlmTrainingParameters + , mlmLastUpdatedAt + , mlmCreatedAt + , mlmScoreThresholdLastUpdatedAt + , mlmInputDataLocationS3 + , mlmSizeInBytes + , mlmMLModelId + , mlmScoreThreshold + , mlmName + , mlmAlgorithm + , mlmCreatedByIAMUser + , mlmEndpointInfo + , mlmTrainingDataSourceId + , mlmMessage + , mlmMLModelType + + -- * PerformanceMetrics + , PerformanceMetrics + , performanceMetrics + , pmProperties + + -- * Prediction + , Prediction + , prediction + , pPredictedValue + , pPredictedLabel + , pPredictedScores + , pDetails + + -- * RDSDataSpec + , RDSDataSpec + , rdsDataSpec + , rdsdsDataSchemaURI + , rdsdsDataSchema + , rdsdsDataRearrangement + , rdsdsDatabaseInformation + , rdsdsSelectSqlQuery + , rdsdsDatabaseCredentials + , rdsdsS3StagingLocation + , rdsdsResourceRole + , rdsdsServiceRole + , rdsdsSubnetId + , rdsdsSecurityGroupIds + + -- * RDSDatabase + , RDSDatabase + , rdsDatabase + , rdsdInstanceIdentifier + , rdsdDatabaseName + + -- * RDSDatabaseCredentials + , RDSDatabaseCredentials + , rdsDatabaseCredentials + , rdsdcUsername + , rdsdcPassword + + -- * RDSMetadata + , RDSMetadata + , rdsMetadata + , rmSelectSqlQuery + , rmDataPipelineId + , rmDatabase + , rmDatabaseUserName + , rmResourceRole + , rmServiceRole + + -- * RealtimeEndpointInfo + , RealtimeEndpointInfo + , realtimeEndpointInfo + , reiCreatedAt + , reiEndpointURL + , reiEndpointStatus + , reiPeakRequestsPerSecond + + -- * RedshiftDataSpec + , RedshiftDataSpec + , redshiftDataSpec + , rDataSchemaURI + , rDataSchema + , rDataRearrangement + , rDatabaseInformation + , rSelectSqlQuery + , rDatabaseCredentials + , rS3StagingLocation + + -- * RedshiftDatabase + , RedshiftDatabase + , redshiftDatabase + , rdDatabaseName + , rdClusterIdentifier + + -- * RedshiftDatabaseCredentials + , RedshiftDatabaseCredentials + , redshiftDatabaseCredentials + , rdcUsername + , rdcPassword + + -- * RedshiftMetadata + , RedshiftMetadata + , redshiftMetadata + , redSelectSqlQuery + , redRedshiftDatabase + , redDatabaseUserName + + -- * S3DataSpec + , S3DataSpec + , s3DataSpec + , sdsDataSchema + , sdsDataSchemaLocationS3 + , sdsDataRearrangement + , sdsDataLocationS3 + ) where + +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.MachineLearning.Types.Sum +import Network.AWS.Prelude +import Network.AWS.Sign.V4 + +-- | Version @2014-12-12@ of the Amazon Machine Learning SDK. +data MachineLearning + +instance AWSService MachineLearning where + type Sg MachineLearning = V4 + service = const svc + where + svc = + Service + { _svcAbbrev = "MachineLearning" + , _svcPrefix = "machinelearning" + , _svcVersion = "2014-12-12" + , _svcEndpoint = defaultEndpoint svc + , _svcTimeout = Just 70 + , _svcStatus = statusSuccess + , _svcError = parseJSONError + , _svcRetry = retry + } + retry = + Exponential + { _retryBase = 5.0e-2 + , _retryGrowth = 2 + , _retryAttempts = 5 + , _retryCheck = check + } + check e + | has (hasCode "ThrottlingException" . hasStatus 400) e = + Just "throttling_exception" + | has (hasCode "Throttling" . hasStatus 400) e = Just "throttling" + | has (hasStatus 503) e = Just "service_unavailable" + | has (hasStatus 500) e = Just "general_server_error" + | has (hasStatus 509) e = Just "limit_exceeded" + | otherwise = Nothing + +-- | An error on the server occurred when trying to process a request. +_InternalServerException :: AsError a => Getting (First ServiceError) a ServiceError +_InternalServerException = + _ServiceError . hasStatus 500 . hasCode "InternalServerException" + +-- | An error on the client occurred. Typically, the cause is an invalid +-- input value. +_InvalidInputException :: AsError a => Getting (First ServiceError) a ServiceError +_InvalidInputException = + _ServiceError . hasStatus 400 . hasCode "InvalidInputException" + +-- | A second request to use or change an object was not allowed. This can +-- result from retrying a request using a parameter that was not present in +-- the original request. +_IdempotentParameterMismatchException :: AsError a => Getting (First ServiceError) a ServiceError +_IdempotentParameterMismatchException = + _ServiceError . + hasStatus 400 . hasCode "IdempotentParameterMismatchException" + +-- | The exception is thrown when a predict request is made to an unmounted +-- 'MLModel'. +_PredictorNotMountedException :: AsError a => Getting (First ServiceError) a ServiceError +_PredictorNotMountedException = + _ServiceError . hasStatus 400 . hasCode "PredictorNotMountedException" + +-- | A specified resource cannot be located. +_ResourceNotFoundException :: AsError a => Getting (First ServiceError) a ServiceError +_ResourceNotFoundException = + _ServiceError . hasStatus 404 . hasCode "ResourceNotFoundException" + +-- | The subscriber exceeded the maximum number of operations. This exception +-- can occur when listing objects such as 'DataSource'. +_LimitExceededException :: AsError a => Getting (First ServiceError) a ServiceError +_LimitExceededException = + _ServiceError . hasStatus 417 . hasCode "LimitExceededException" diff --git a/gen/Network/AWS/MachineLearning/Types/Product.hs b/gen/Network/AWS/MachineLearning/Types/Product.hs new file mode 100644 --- /dev/null +++ b/gen/Network/AWS/MachineLearning/Types/Product.hs @@ -0,0 +1,1512 @@ +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} + +{-# OPTIONS_GHC -fno-warn-unused-imports #-} + +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | +-- Module : Network.AWS.MachineLearning.Types.Product +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. +-- Maintainer : Brendan Hay +-- Stability : auto-generated +-- Portability : non-portable (GHC extensions) +-- +module Network.AWS.MachineLearning.Types.Product where + +import Network.AWS.MachineLearning.Types.Sum +import Network.AWS.Prelude + +-- | Represents the output of GetBatchPrediction operation. +-- +-- The content consists of the detailed metadata, the status, and the data +-- file information of a /Batch Prediction/. +-- +-- /See:/ 'batchPrediction' smart constructor. +data BatchPrediction = BatchPrediction' + { _bpStatus :: !(Maybe EntityStatus) + , _bpLastUpdatedAt :: !(Maybe POSIX) + , _bpCreatedAt :: !(Maybe POSIX) + , _bpInputDataLocationS3 :: !(Maybe Text) + , _bpMLModelId :: !(Maybe Text) + , _bpBatchPredictionDataSourceId :: !(Maybe Text) + , _bpBatchPredictionId :: !(Maybe Text) + , _bpName :: !(Maybe Text) + , _bpCreatedByIAMUser :: !(Maybe Text) + , _bpMessage :: !(Maybe Text) + , _bpOutputURI :: !(Maybe Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'BatchPrediction' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'bpStatus' +-- +-- * 'bpLastUpdatedAt' +-- +-- * 'bpCreatedAt' +-- +-- * 'bpInputDataLocationS3' +-- +-- * 'bpMLModelId' +-- +-- * 'bpBatchPredictionDataSourceId' +-- +-- * 'bpBatchPredictionId' +-- +-- * 'bpName' +-- +-- * 'bpCreatedByIAMUser' +-- +-- * 'bpMessage' +-- +-- * 'bpOutputURI' +batchPrediction + :: BatchPrediction +batchPrediction = + BatchPrediction' + { _bpStatus = Nothing + , _bpLastUpdatedAt = Nothing + , _bpCreatedAt = Nothing + , _bpInputDataLocationS3 = Nothing + , _bpMLModelId = Nothing + , _bpBatchPredictionDataSourceId = Nothing + , _bpBatchPredictionId = Nothing + , _bpName = Nothing + , _bpCreatedByIAMUser = Nothing + , _bpMessage = Nothing + , _bpOutputURI = Nothing + } + +-- | The status of the 'BatchPrediction'. This element can have one of the +-- following values: +-- +-- - 'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request +-- to generate predictions for a batch of observations. +-- - 'INPROGRESS' - The process is underway. +-- - 'FAILED' - The request to peform a batch prediction did not run to +-- completion. It is not usable. +-- - 'COMPLETED' - The batch prediction process completed successfully. +-- - 'DELETED' - The 'BatchPrediction' is marked as deleted. It is not +-- usable. +bpStatus :: Lens' BatchPrediction (Maybe EntityStatus) +bpStatus = lens _bpStatus (\ s a -> s{_bpStatus = a}); + +-- | The time of the most recent edit to the 'BatchPrediction'. The time is +-- expressed in epoch time. +bpLastUpdatedAt :: Lens' BatchPrediction (Maybe UTCTime) +bpLastUpdatedAt = lens _bpLastUpdatedAt (\ s a -> s{_bpLastUpdatedAt = a}) . mapping _Time; + +-- | The time that the 'BatchPrediction' was created. The time is expressed +-- in epoch time. +bpCreatedAt :: Lens' BatchPrediction (Maybe UTCTime) +bpCreatedAt = lens _bpCreatedAt (\ s a -> s{_bpCreatedAt = a}) . mapping _Time; + +-- | The location of the data file or directory in Amazon Simple Storage +-- Service (Amazon S3). +bpInputDataLocationS3 :: Lens' BatchPrediction (Maybe Text) +bpInputDataLocationS3 = lens _bpInputDataLocationS3 (\ s a -> s{_bpInputDataLocationS3 = a}); + +-- | The ID of the 'MLModel' that generated predictions for the +-- 'BatchPrediction' request. +bpMLModelId :: Lens' BatchPrediction (Maybe Text) +bpMLModelId = lens _bpMLModelId (\ s a -> s{_bpMLModelId = a}); + +-- | The ID of the 'DataSource' that points to the group of observations to +-- predict. +bpBatchPredictionDataSourceId :: Lens' BatchPrediction (Maybe Text) +bpBatchPredictionDataSourceId = lens _bpBatchPredictionDataSourceId (\ s a -> s{_bpBatchPredictionDataSourceId = a}); + +-- | The ID assigned to the 'BatchPrediction' at creation. This value should +-- be identical to the value of the 'BatchPredictionID' in the request. +bpBatchPredictionId :: Lens' BatchPrediction (Maybe Text) +bpBatchPredictionId = lens _bpBatchPredictionId (\ s a -> s{_bpBatchPredictionId = a}); + +-- | A user-supplied name or description of the 'BatchPrediction'. +bpName :: Lens' BatchPrediction (Maybe Text) +bpName = lens _bpName (\ s a -> s{_bpName = a}); + +-- | The AWS user account that invoked the 'BatchPrediction'. The account +-- type can be either an AWS root account or an AWS Identity and Access +-- Management (IAM) user account. +bpCreatedByIAMUser :: Lens' BatchPrediction (Maybe Text) +bpCreatedByIAMUser = lens _bpCreatedByIAMUser (\ s a -> s{_bpCreatedByIAMUser = a}); + +-- | A description of the most recent details about processing the batch +-- prediction request. +bpMessage :: Lens' BatchPrediction (Maybe Text) +bpMessage = lens _bpMessage (\ s a -> s{_bpMessage = a}); + +-- | The location of an Amazon S3 bucket or directory to receive the +-- operation results. The following substrings are not allowed in the s3 +-- key portion of the \"outputURI\" field: \':\', \'\/\/\', \'\/.\/\', +-- \'\/..\/\'. +bpOutputURI :: Lens' BatchPrediction (Maybe Text) +bpOutputURI = lens _bpOutputURI (\ s a -> s{_bpOutputURI = a}); + +instance FromJSON BatchPrediction where + parseJSON + = withObject "BatchPrediction" + (\ x -> + BatchPrediction' <$> + (x .:? "Status") <*> (x .:? "LastUpdatedAt") <*> + (x .:? "CreatedAt") + <*> (x .:? "InputDataLocationS3") + <*> (x .:? "MLModelId") + <*> (x .:? "BatchPredictionDataSourceId") + <*> (x .:? "BatchPredictionId") + <*> (x .:? "Name") + <*> (x .:? "CreatedByIamUser") + <*> (x .:? "Message") + <*> (x .:? "OutputUri")) + +-- | Represents the output of the GetDataSource operation. +-- +-- The content consists of the detailed metadata and data file information +-- and the current status of the 'DataSource'. +-- +-- /See:/ 'dataSource' smart constructor. +data DataSource = DataSource' + { _dsStatus :: !(Maybe EntityStatus) + , _dsNumberOfFiles :: !(Maybe Integer) + , _dsLastUpdatedAt :: !(Maybe POSIX) + , _dsCreatedAt :: !(Maybe POSIX) + , _dsRDSMetadata :: !(Maybe RDSMetadata) + , _dsDataSourceId :: !(Maybe Text) + , _dsDataSizeInBytes :: !(Maybe Integer) + , _dsName :: !(Maybe Text) + , _dsCreatedByIAMUser :: !(Maybe Text) + , _dsDataLocationS3 :: !(Maybe Text) + , _dsComputeStatistics :: !(Maybe Bool) + , _dsMessage :: !(Maybe Text) + , _dsRedshiftMetadata :: !(Maybe RedshiftMetadata) + , _dsRoleARN :: !(Maybe Text) + , _dsDataRearrangement :: !(Maybe Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'DataSource' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'dsStatus' +-- +-- * 'dsNumberOfFiles' +-- +-- * 'dsLastUpdatedAt' +-- +-- * 'dsCreatedAt' +-- +-- * 'dsRDSMetadata' +-- +-- * 'dsDataSourceId' +-- +-- * 'dsDataSizeInBytes' +-- +-- * 'dsName' +-- +-- * 'dsCreatedByIAMUser' +-- +-- * 'dsDataLocationS3' +-- +-- * 'dsComputeStatistics' +-- +-- * 'dsMessage' +-- +-- * 'dsRedshiftMetadata' +-- +-- * 'dsRoleARN' +-- +-- * 'dsDataRearrangement' +dataSource + :: DataSource +dataSource = + DataSource' + { _dsStatus = Nothing + , _dsNumberOfFiles = Nothing + , _dsLastUpdatedAt = Nothing + , _dsCreatedAt = Nothing + , _dsRDSMetadata = Nothing + , _dsDataSourceId = Nothing + , _dsDataSizeInBytes = Nothing + , _dsName = Nothing + , _dsCreatedByIAMUser = Nothing + , _dsDataLocationS3 = Nothing + , _dsComputeStatistics = Nothing + , _dsMessage = Nothing + , _dsRedshiftMetadata = Nothing + , _dsRoleARN = Nothing + , _dsDataRearrangement = Nothing + } + +-- | The current status of the 'DataSource'. This element can have one of the +-- following values: +-- +-- - PENDING - Amazon Machine Learning (Amazon ML) submitted a request to +-- create a 'DataSource'. +-- - INPROGRESS - The creation process is underway. +-- - FAILED - The request to create a 'DataSource' did not run to +-- completion. It is not usable. +-- - COMPLETED - The creation process completed successfully. +-- - DELETED - The 'DataSource' is marked as deleted. It is not usable. +dsStatus :: Lens' DataSource (Maybe EntityStatus) +dsStatus = lens _dsStatus (\ s a -> s{_dsStatus = a}); + +-- | The number of data files referenced by the 'DataSource'. +dsNumberOfFiles :: Lens' DataSource (Maybe Integer) +dsNumberOfFiles = lens _dsNumberOfFiles (\ s a -> s{_dsNumberOfFiles = a}); + +-- | The time of the most recent edit to the 'BatchPrediction'. The time is +-- expressed in epoch time. +dsLastUpdatedAt :: Lens' DataSource (Maybe UTCTime) +dsLastUpdatedAt = lens _dsLastUpdatedAt (\ s a -> s{_dsLastUpdatedAt = a}) . mapping _Time; + +-- | The time that the 'DataSource' was created. The time is expressed in +-- epoch time. +dsCreatedAt :: Lens' DataSource (Maybe UTCTime) +dsCreatedAt = lens _dsCreatedAt (\ s a -> s{_dsCreatedAt = a}) . mapping _Time; + +-- | Undocumented member. +dsRDSMetadata :: Lens' DataSource (Maybe RDSMetadata) +dsRDSMetadata = lens _dsRDSMetadata (\ s a -> s{_dsRDSMetadata = a}); + +-- | The ID that is assigned to the 'DataSource' during creation. +dsDataSourceId :: Lens' DataSource (Maybe Text) +dsDataSourceId = lens _dsDataSourceId (\ s a -> s{_dsDataSourceId = a}); + +-- | The total number of observations contained in the data files that the +-- 'DataSource' references. +dsDataSizeInBytes :: Lens' DataSource (Maybe Integer) +dsDataSizeInBytes = lens _dsDataSizeInBytes (\ s a -> s{_dsDataSizeInBytes = a}); + +-- | A user-supplied name or description of the 'DataSource'. +dsName :: Lens' DataSource (Maybe Text) +dsName = lens _dsName (\ s a -> s{_dsName = a}); + +-- | The AWS user account from which the 'DataSource' was created. The +-- account type can be either an AWS root account or an AWS Identity and +-- Access Management (IAM) user account. +dsCreatedByIAMUser :: Lens' DataSource (Maybe Text) +dsCreatedByIAMUser = lens _dsCreatedByIAMUser (\ s a -> s{_dsCreatedByIAMUser = a}); + +-- | The location and name of the data in Amazon Simple Storage Service +-- (Amazon S3) that is used by a 'DataSource'. +dsDataLocationS3 :: Lens' DataSource (Maybe Text) +dsDataLocationS3 = lens _dsDataLocationS3 (\ s a -> s{_dsDataLocationS3 = a}); + +-- | The parameter is 'true' if statistics need to be generated from the +-- observation data. +dsComputeStatistics :: Lens' DataSource (Maybe Bool) +dsComputeStatistics = lens _dsComputeStatistics (\ s a -> s{_dsComputeStatistics = a}); + +-- | A description of the most recent details about creating the +-- 'DataSource'. +dsMessage :: Lens' DataSource (Maybe Text) +dsMessage = lens _dsMessage (\ s a -> s{_dsMessage = a}); + +-- | Undocumented member. +dsRedshiftMetadata :: Lens' DataSource (Maybe RedshiftMetadata) +dsRedshiftMetadata = lens _dsRedshiftMetadata (\ s a -> s{_dsRedshiftMetadata = a}); + +-- | Undocumented member. +dsRoleARN :: Lens' DataSource (Maybe Text) +dsRoleARN = lens _dsRoleARN (\ s a -> s{_dsRoleARN = a}); + +-- | A JSON string that represents the splitting requirement of a +-- 'Datasource'. +dsDataRearrangement :: Lens' DataSource (Maybe Text) +dsDataRearrangement = lens _dsDataRearrangement (\ s a -> s{_dsDataRearrangement = a}); + +instance FromJSON DataSource where + parseJSON + = withObject "DataSource" + (\ x -> + DataSource' <$> + (x .:? "Status") <*> (x .:? "NumberOfFiles") <*> + (x .:? "LastUpdatedAt") + <*> (x .:? "CreatedAt") + <*> (x .:? "RDSMetadata") + <*> (x .:? "DataSourceId") + <*> (x .:? "DataSizeInBytes") + <*> (x .:? "Name") + <*> (x .:? "CreatedByIamUser") + <*> (x .:? "DataLocationS3") + <*> (x .:? "ComputeStatistics") + <*> (x .:? "Message") + <*> (x .:? "RedshiftMetadata") + <*> (x .:? "RoleARN") + <*> (x .:? "DataRearrangement")) + +-- | Represents the output of GetEvaluation operation. +-- +-- The content consists of the detailed metadata and data file information +-- and the current status of the 'Evaluation'. +-- +-- /See:/ 'evaluation' smart constructor. +data Evaluation = Evaluation' + { _eStatus :: !(Maybe EntityStatus) + , _ePerformanceMetrics :: !(Maybe PerformanceMetrics) + , _eLastUpdatedAt :: !(Maybe POSIX) + , _eCreatedAt :: !(Maybe POSIX) + , _eInputDataLocationS3 :: !(Maybe Text) + , _eMLModelId :: !(Maybe Text) + , _eName :: !(Maybe Text) + , _eCreatedByIAMUser :: !(Maybe Text) + , _eMessage :: !(Maybe Text) + , _eEvaluationId :: !(Maybe Text) + , _eEvaluationDataSourceId :: !(Maybe Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'Evaluation' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'eStatus' +-- +-- * 'ePerformanceMetrics' +-- +-- * 'eLastUpdatedAt' +-- +-- * 'eCreatedAt' +-- +-- * 'eInputDataLocationS3' +-- +-- * 'eMLModelId' +-- +-- * 'eName' +-- +-- * 'eCreatedByIAMUser' +-- +-- * 'eMessage' +-- +-- * 'eEvaluationId' +-- +-- * 'eEvaluationDataSourceId' +evaluation + :: Evaluation +evaluation = + Evaluation' + { _eStatus = Nothing + , _ePerformanceMetrics = Nothing + , _eLastUpdatedAt = Nothing + , _eCreatedAt = Nothing + , _eInputDataLocationS3 = Nothing + , _eMLModelId = Nothing + , _eName = Nothing + , _eCreatedByIAMUser = Nothing + , _eMessage = Nothing + , _eEvaluationId = Nothing + , _eEvaluationDataSourceId = Nothing + } + +-- | The status of the evaluation. This element can have one of the following +-- values: +-- +-- - 'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request +-- to evaluate an 'MLModel'. +-- - 'INPROGRESS' - The evaluation is underway. +-- - 'FAILED' - The request to evaluate an 'MLModel' did not run to +-- completion. It is not usable. +-- - 'COMPLETED' - The evaluation process completed successfully. +-- - 'DELETED' - The 'Evaluation' is marked as deleted. It is not usable. +eStatus :: Lens' Evaluation (Maybe EntityStatus) +eStatus = lens _eStatus (\ s a -> s{_eStatus = a}); + +-- | Measurements of how well the 'MLModel' performed, using observations +-- referenced by the 'DataSource'. One of the following metrics is +-- returned, based on the type of the MLModel: +-- +-- - BinaryAUC: A binary 'MLModel' uses the Area Under the Curve (AUC) +-- technique to measure performance. +-- +-- - RegressionRMSE: A regression 'MLModel' uses the Root Mean Square +-- Error (RMSE) technique to measure performance. RMSE measures the +-- difference between predicted and actual values for a single +-- variable. +-- +-- - MulticlassAvgFScore: A multiclass 'MLModel' uses the F1 score +-- technique to measure performance. +-- +-- For more information about performance metrics, please see the +-- . +ePerformanceMetrics :: Lens' Evaluation (Maybe PerformanceMetrics) +ePerformanceMetrics = lens _ePerformanceMetrics (\ s a -> s{_ePerformanceMetrics = a}); + +-- | The time of the most recent edit to the 'Evaluation'. The time is +-- expressed in epoch time. +eLastUpdatedAt :: Lens' Evaluation (Maybe UTCTime) +eLastUpdatedAt = lens _eLastUpdatedAt (\ s a -> s{_eLastUpdatedAt = a}) . mapping _Time; + +-- | The time that the 'Evaluation' was created. The time is expressed in +-- epoch time. +eCreatedAt :: Lens' Evaluation (Maybe UTCTime) +eCreatedAt = lens _eCreatedAt (\ s a -> s{_eCreatedAt = a}) . mapping _Time; + +-- | The location and name of the data in Amazon Simple Storage Server +-- (Amazon S3) that is used in the evaluation. +eInputDataLocationS3 :: Lens' Evaluation (Maybe Text) +eInputDataLocationS3 = lens _eInputDataLocationS3 (\ s a -> s{_eInputDataLocationS3 = a}); + +-- | The ID of the 'MLModel' that is the focus of the evaluation. +eMLModelId :: Lens' Evaluation (Maybe Text) +eMLModelId = lens _eMLModelId (\ s a -> s{_eMLModelId = a}); + +-- | A user-supplied name or description of the 'Evaluation'. +eName :: Lens' Evaluation (Maybe Text) +eName = lens _eName (\ s a -> s{_eName = a}); + +-- | The AWS user account that invoked the evaluation. The account type can +-- be either an AWS root account or an AWS Identity and Access Management +-- (IAM) user account. +eCreatedByIAMUser :: Lens' Evaluation (Maybe Text) +eCreatedByIAMUser = lens _eCreatedByIAMUser (\ s a -> s{_eCreatedByIAMUser = a}); + +-- | A description of the most recent details about evaluating the 'MLModel'. +eMessage :: Lens' Evaluation (Maybe Text) +eMessage = lens _eMessage (\ s a -> s{_eMessage = a}); + +-- | The ID that is assigned to the 'Evaluation' at creation. +eEvaluationId :: Lens' Evaluation (Maybe Text) +eEvaluationId = lens _eEvaluationId (\ s a -> s{_eEvaluationId = a}); + +-- | The ID of the 'DataSource' that is used to evaluate the 'MLModel'. +eEvaluationDataSourceId :: Lens' Evaluation (Maybe Text) +eEvaluationDataSourceId = lens _eEvaluationDataSourceId (\ s a -> s{_eEvaluationDataSourceId = a}); + +instance FromJSON Evaluation where + parseJSON + = withObject "Evaluation" + (\ x -> + Evaluation' <$> + (x .:? "Status") <*> (x .:? "PerformanceMetrics") <*> + (x .:? "LastUpdatedAt") + <*> (x .:? "CreatedAt") + <*> (x .:? "InputDataLocationS3") + <*> (x .:? "MLModelId") + <*> (x .:? "Name") + <*> (x .:? "CreatedByIamUser") + <*> (x .:? "Message") + <*> (x .:? "EvaluationId") + <*> (x .:? "EvaluationDataSourceId")) + +-- | Represents the output of a GetMLModel operation. +-- +-- The content consists of the detailed metadata and the current status of +-- the 'MLModel'. +-- +-- /See:/ 'mLModel' smart constructor. +data MLModel = MLModel' + { _mlmStatus :: !(Maybe EntityStatus) + , _mlmTrainingParameters :: !(Maybe (Map Text Text)) + , _mlmLastUpdatedAt :: !(Maybe POSIX) + , _mlmCreatedAt :: !(Maybe POSIX) + , _mlmScoreThresholdLastUpdatedAt :: !(Maybe POSIX) + , _mlmInputDataLocationS3 :: !(Maybe Text) + , _mlmSizeInBytes :: !(Maybe Integer) + , _mlmMLModelId :: !(Maybe Text) + , _mlmScoreThreshold :: !(Maybe Double) + , _mlmName :: !(Maybe Text) + , _mlmAlgorithm :: !(Maybe Algorithm) + , _mlmCreatedByIAMUser :: !(Maybe Text) + , _mlmEndpointInfo :: !(Maybe RealtimeEndpointInfo) + , _mlmTrainingDataSourceId :: !(Maybe Text) + , _mlmMessage :: !(Maybe Text) + , _mlmMLModelType :: !(Maybe MLModelType) + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'MLModel' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'mlmStatus' +-- +-- * 'mlmTrainingParameters' +-- +-- * 'mlmLastUpdatedAt' +-- +-- * 'mlmCreatedAt' +-- +-- * 'mlmScoreThresholdLastUpdatedAt' +-- +-- * 'mlmInputDataLocationS3' +-- +-- * 'mlmSizeInBytes' +-- +-- * 'mlmMLModelId' +-- +-- * 'mlmScoreThreshold' +-- +-- * 'mlmName' +-- +-- * 'mlmAlgorithm' +-- +-- * 'mlmCreatedByIAMUser' +-- +-- * 'mlmEndpointInfo' +-- +-- * 'mlmTrainingDataSourceId' +-- +-- * 'mlmMessage' +-- +-- * 'mlmMLModelType' +mLModel + :: MLModel +mLModel = + MLModel' + { _mlmStatus = Nothing + , _mlmTrainingParameters = Nothing + , _mlmLastUpdatedAt = Nothing + , _mlmCreatedAt = Nothing + , _mlmScoreThresholdLastUpdatedAt = Nothing + , _mlmInputDataLocationS3 = Nothing + , _mlmSizeInBytes = Nothing + , _mlmMLModelId = Nothing + , _mlmScoreThreshold = Nothing + , _mlmName = Nothing + , _mlmAlgorithm = Nothing + , _mlmCreatedByIAMUser = Nothing + , _mlmEndpointInfo = Nothing + , _mlmTrainingDataSourceId = Nothing + , _mlmMessage = Nothing + , _mlmMLModelType = Nothing + } + +-- | The current status of an 'MLModel'. This element can have one of the +-- following values: +-- +-- - PENDING - Amazon Machine Learning (Amazon ML) submitted a request to +-- create an 'MLModel'. +-- - INPROGRESS - The creation process is underway. +-- - FAILED - The request to create an 'MLModel' did not run to +-- completion. It is not usable. +-- - COMPLETED - The creation process completed successfully. +-- - DELETED - The 'MLModel' is marked as deleted. It is not usable. +mlmStatus :: Lens' MLModel (Maybe EntityStatus) +mlmStatus = lens _mlmStatus (\ s a -> s{_mlmStatus = a}); + +-- | A list of the training parameters in the 'MLModel'. The list is +-- implemented as a map of key\/value pairs. +-- +-- The following is the current set of training parameters: +-- +-- - 'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. +-- It controls overfitting the data by penalizing large coefficients. +-- This tends to drive coefficients to zero, resulting in a sparse +-- feature set. If you use this parameter, specify a small value, such +-- as 1.0E-04 or 1.0E-08. +-- +-- The value is a double that ranges from 0 to MAX_DOUBLE. The default +-- is not to use L1 normalization. The parameter cannot be used when +-- 'L2' is specified. Use this parameter sparingly. +-- +-- - 'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. +-- It controls overfitting the data by penalizing large coefficients. +-- This tends to drive coefficients to small, nonzero values. If you +-- use this parameter, specify a small value, such as 1.0E-04 or +-- 1.0E-08. +-- +-- The valus is a double that ranges from 0 to MAX_DOUBLE. The default +-- is not to use L2 normalization. This cannot be used when 'L1' is +-- specified. Use this parameter sparingly. +-- +-- - 'sgd.maxPasses' - Number of times that the training process +-- traverses the observations to build the 'MLModel'. The value is an +-- integer that ranges from 1 to 10000. The default value is 10. +-- +-- - 'sgd.maxMLModelSizeInBytes' - Maximum allowed size of the model. +-- Depending on the input data, the model size might affect +-- performance. +-- +-- The value is an integer that ranges from 100000 to 2147483648. The +-- default value is 33554432. +-- +mlmTrainingParameters :: Lens' MLModel (HashMap Text Text) +mlmTrainingParameters = lens _mlmTrainingParameters (\ s a -> s{_mlmTrainingParameters = a}) . _Default . _Map; + +-- | The time of the most recent edit to the 'MLModel'. The time is expressed +-- in epoch time. +mlmLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) +mlmLastUpdatedAt = lens _mlmLastUpdatedAt (\ s a -> s{_mlmLastUpdatedAt = a}) . mapping _Time; + +-- | The time that the 'MLModel' was created. The time is expressed in epoch +-- time. +mlmCreatedAt :: Lens' MLModel (Maybe UTCTime) +mlmCreatedAt = lens _mlmCreatedAt (\ s a -> s{_mlmCreatedAt = a}) . mapping _Time; + +-- | The time of the most recent edit to the 'ScoreThreshold'. The time is +-- expressed in epoch time. +mlmScoreThresholdLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) +mlmScoreThresholdLastUpdatedAt = lens _mlmScoreThresholdLastUpdatedAt (\ s a -> s{_mlmScoreThresholdLastUpdatedAt = a}) . mapping _Time; + +-- | The location of the data file or directory in Amazon Simple Storage +-- Service (Amazon S3). +mlmInputDataLocationS3 :: Lens' MLModel (Maybe Text) +mlmInputDataLocationS3 = lens _mlmInputDataLocationS3 (\ s a -> s{_mlmInputDataLocationS3 = a}); + +-- | Undocumented member. +mlmSizeInBytes :: Lens' MLModel (Maybe Integer) +mlmSizeInBytes = lens _mlmSizeInBytes (\ s a -> s{_mlmSizeInBytes = a}); + +-- | The ID assigned to the 'MLModel' at creation. +mlmMLModelId :: Lens' MLModel (Maybe Text) +mlmMLModelId = lens _mlmMLModelId (\ s a -> s{_mlmMLModelId = a}); + +-- | Undocumented member. +mlmScoreThreshold :: Lens' MLModel (Maybe Double) +mlmScoreThreshold = lens _mlmScoreThreshold (\ s a -> s{_mlmScoreThreshold = a}); + +-- | A user-supplied name or description of the 'MLModel'. +mlmName :: Lens' MLModel (Maybe Text) +mlmName = lens _mlmName (\ s a -> s{_mlmName = a}); + +-- | The algorithm used to train the 'MLModel'. The following algorithm is +-- supported: +-- +-- - SGD -- Stochastic gradient descent. The goal of SGD is to minimize +-- the gradient of the loss function. +mlmAlgorithm :: Lens' MLModel (Maybe Algorithm) +mlmAlgorithm = lens _mlmAlgorithm (\ s a -> s{_mlmAlgorithm = a}); + +-- | The AWS user account from which the 'MLModel' was created. The account +-- type can be either an AWS root account or an AWS Identity and Access +-- Management (IAM) user account. +mlmCreatedByIAMUser :: Lens' MLModel (Maybe Text) +mlmCreatedByIAMUser = lens _mlmCreatedByIAMUser (\ s a -> s{_mlmCreatedByIAMUser = a}); + +-- | The current endpoint of the 'MLModel'. +mlmEndpointInfo :: Lens' MLModel (Maybe RealtimeEndpointInfo) +mlmEndpointInfo = lens _mlmEndpointInfo (\ s a -> s{_mlmEndpointInfo = a}); + +-- | The ID of the training 'DataSource'. The CreateMLModel operation uses +-- the 'TrainingDataSourceId'. +mlmTrainingDataSourceId :: Lens' MLModel (Maybe Text) +mlmTrainingDataSourceId = lens _mlmTrainingDataSourceId (\ s a -> s{_mlmTrainingDataSourceId = a}); + +-- | A description of the most recent details about accessing the 'MLModel'. +mlmMessage :: Lens' MLModel (Maybe Text) +mlmMessage = lens _mlmMessage (\ s a -> s{_mlmMessage = a}); + +-- | Identifies the 'MLModel' category. The following are the available +-- types: +-- +-- - REGRESSION - Produces a numeric result. For example, \"What listing +-- price should a house have?\". +-- - BINARY - Produces one of two possible results. For example, \"Is +-- this a child-friendly web site?\". +-- - MULTICLASS - Produces more than two possible results. For example, +-- \"Is this a HIGH, LOW or MEDIUM risk trade?\". +mlmMLModelType :: Lens' MLModel (Maybe MLModelType) +mlmMLModelType = lens _mlmMLModelType (\ s a -> s{_mlmMLModelType = a}); + +instance FromJSON MLModel where + parseJSON + = withObject "MLModel" + (\ x -> + MLModel' <$> + (x .:? "Status") <*> + (x .:? "TrainingParameters" .!= mempty) + <*> (x .:? "LastUpdatedAt") + <*> (x .:? "CreatedAt") + <*> (x .:? "ScoreThresholdLastUpdatedAt") + <*> (x .:? "InputDataLocationS3") + <*> (x .:? "SizeInBytes") + <*> (x .:? "MLModelId") + <*> (x .:? "ScoreThreshold") + <*> (x .:? "Name") + <*> (x .:? "Algorithm") + <*> (x .:? "CreatedByIamUser") + <*> (x .:? "EndpointInfo") + <*> (x .:? "TrainingDataSourceId") + <*> (x .:? "Message") + <*> (x .:? "MLModelType")) + +-- | Measurements of how well the 'MLModel' performed on known observations. +-- One of the following metrics is returned, based on the type of the +-- 'MLModel': +-- +-- - BinaryAUC: The binary 'MLModel' uses the Area Under the Curve (AUC) +-- technique to measure performance. +-- +-- - RegressionRMSE: The regression 'MLModel' uses the Root Mean Square +-- Error (RMSE) technique to measure performance. RMSE measures the +-- difference between predicted and actual values for a single +-- variable. +-- +-- - MulticlassAvgFScore: The multiclass 'MLModel' uses the F1 score +-- technique to measure performance. +-- +-- For more information about performance metrics, please see the +-- . +-- +-- /See:/ 'performanceMetrics' smart constructor. +newtype PerformanceMetrics = PerformanceMetrics' + { _pmProperties :: Maybe (Map Text Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'PerformanceMetrics' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'pmProperties' +performanceMetrics + :: PerformanceMetrics +performanceMetrics = + PerformanceMetrics' + { _pmProperties = Nothing + } + +-- | Undocumented member. +pmProperties :: Lens' PerformanceMetrics (HashMap Text Text) +pmProperties = lens _pmProperties (\ s a -> s{_pmProperties = a}) . _Default . _Map; + +instance FromJSON PerformanceMetrics where + parseJSON + = withObject "PerformanceMetrics" + (\ x -> + PerformanceMetrics' <$> + (x .:? "Properties" .!= mempty)) + +-- | The output from a 'Predict' operation: +-- +-- - 'Details' - Contains the following attributes: +-- DetailsAttributes.PREDICTIVE_MODEL_TYPE - REGRESSION | BINARY | +-- MULTICLASS DetailsAttributes.ALGORITHM - SGD +-- +-- - 'PredictedLabel' - Present for either a BINARY or MULTICLASS +-- 'MLModel' request. +-- +-- - 'PredictedScores' - Contains the raw classification score +-- corresponding to each label. +-- +-- - 'PredictedValue' - Present for a REGRESSION 'MLModel' request. +-- +-- +-- /See:/ 'prediction' smart constructor. +data Prediction = Prediction' + { _pPredictedValue :: !(Maybe Double) + , _pPredictedLabel :: !(Maybe Text) + , _pPredictedScores :: !(Maybe (Map Text Double)) + , _pDetails :: !(Maybe (Map DetailsAttributes Text)) + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'Prediction' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'pPredictedValue' +-- +-- * 'pPredictedLabel' +-- +-- * 'pPredictedScores' +-- +-- * 'pDetails' +prediction + :: Prediction +prediction = + Prediction' + { _pPredictedValue = Nothing + , _pPredictedLabel = Nothing + , _pPredictedScores = Nothing + , _pDetails = Nothing + } + +-- | The prediction value for REGRESSION 'MLModel'. +pPredictedValue :: Lens' Prediction (Maybe Double) +pPredictedValue = lens _pPredictedValue (\ s a -> s{_pPredictedValue = a}); + +-- | The prediction label for either a BINARY or MULTICLASS 'MLModel'. +pPredictedLabel :: Lens' Prediction (Maybe Text) +pPredictedLabel = lens _pPredictedLabel (\ s a -> s{_pPredictedLabel = a}); + +-- | Undocumented member. +pPredictedScores :: Lens' Prediction (HashMap Text Double) +pPredictedScores = lens _pPredictedScores (\ s a -> s{_pPredictedScores = a}) . _Default . _Map; + +-- | Undocumented member. +pDetails :: Lens' Prediction (HashMap DetailsAttributes Text) +pDetails = lens _pDetails (\ s a -> s{_pDetails = a}) . _Default . _Map; + +instance FromJSON Prediction where + parseJSON + = withObject "Prediction" + (\ x -> + Prediction' <$> + (x .:? "predictedValue") <*> (x .:? "predictedLabel") + <*> (x .:? "predictedScores" .!= mempty) + <*> (x .:? "details" .!= mempty)) + +-- | The data specification of an Amazon Relational Database Service (Amazon +-- RDS) 'DataSource'. +-- +-- /See:/ 'rdsDataSpec' smart constructor. +data RDSDataSpec = RDSDataSpec' + { _rdsdsDataSchemaURI :: !(Maybe Text) + , _rdsdsDataSchema :: !(Maybe Text) + , _rdsdsDataRearrangement :: !(Maybe Text) + , _rdsdsDatabaseInformation :: !RDSDatabase + , _rdsdsSelectSqlQuery :: !Text + , _rdsdsDatabaseCredentials :: !RDSDatabaseCredentials + , _rdsdsS3StagingLocation :: !Text + , _rdsdsResourceRole :: !Text + , _rdsdsServiceRole :: !Text + , _rdsdsSubnetId :: !Text + , _rdsdsSecurityGroupIds :: ![Text] + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'RDSDataSpec' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'rdsdsDataSchemaURI' +-- +-- * 'rdsdsDataSchema' +-- +-- * 'rdsdsDataRearrangement' +-- +-- * 'rdsdsDatabaseInformation' +-- +-- * 'rdsdsSelectSqlQuery' +-- +-- * 'rdsdsDatabaseCredentials' +-- +-- * 'rdsdsS3StagingLocation' +-- +-- * 'rdsdsResourceRole' +-- +-- * 'rdsdsServiceRole' +-- +-- * 'rdsdsSubnetId' +-- +-- * 'rdsdsSecurityGroupIds' +rdsDataSpec + :: RDSDatabase -- ^ 'rdsdsDatabaseInformation' + -> Text -- ^ 'rdsdsSelectSqlQuery' + -> RDSDatabaseCredentials -- ^ 'rdsdsDatabaseCredentials' + -> Text -- ^ 'rdsdsS3StagingLocation' + -> Text -- ^ 'rdsdsResourceRole' + -> Text -- ^ 'rdsdsServiceRole' + -> Text -- ^ 'rdsdsSubnetId' + -> RDSDataSpec +rdsDataSpec pDatabaseInformation_ pSelectSqlQuery_ pDatabaseCredentials_ pS3StagingLocation_ pResourceRole_ pServiceRole_ pSubnetId_ = + RDSDataSpec' + { _rdsdsDataSchemaURI = Nothing + , _rdsdsDataSchema = Nothing + , _rdsdsDataRearrangement = Nothing + , _rdsdsDatabaseInformation = pDatabaseInformation_ + , _rdsdsSelectSqlQuery = pSelectSqlQuery_ + , _rdsdsDatabaseCredentials = pDatabaseCredentials_ + , _rdsdsS3StagingLocation = pS3StagingLocation_ + , _rdsdsResourceRole = pResourceRole_ + , _rdsdsServiceRole = pServiceRole_ + , _rdsdsSubnetId = pSubnetId_ + , _rdsdsSecurityGroupIds = mempty + } + +-- | The Amazon S3 location of the 'DataSchema'. +rdsdsDataSchemaURI :: Lens' RDSDataSpec (Maybe Text) +rdsdsDataSchemaURI = lens _rdsdsDataSchemaURI (\ s a -> s{_rdsdsDataSchemaURI = a}); + +-- | A JSON string that represents the schema. This is not required if +-- 'DataSchemaUri' is specified. +rdsdsDataSchema :: Lens' RDSDataSpec (Maybe Text) +rdsdsDataSchema = lens _rdsdsDataSchema (\ s a -> s{_rdsdsDataSchema = a}); + +-- | DataRearrangement - A JSON string that represents the splitting +-- requirement of a 'DataSource'. +-- +-- Sample - +-- ' \"{\\\"randomSeed\\\":\\\"some-random-seed\\\", \\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"' +rdsdsDataRearrangement :: Lens' RDSDataSpec (Maybe Text) +rdsdsDataRearrangement = lens _rdsdsDataRearrangement (\ s a -> s{_rdsdsDataRearrangement = a}); + +-- | Describes the 'DatabaseName' and 'InstanceIdentifier' of an an Amazon +-- RDS database. +rdsdsDatabaseInformation :: Lens' RDSDataSpec RDSDatabase +rdsdsDatabaseInformation = lens _rdsdsDatabaseInformation (\ s a -> s{_rdsdsDatabaseInformation = a}); + +-- | The query that is used to retrieve the observation data for the +-- 'DataSource'. +rdsdsSelectSqlQuery :: Lens' RDSDataSpec Text +rdsdsSelectSqlQuery = lens _rdsdsSelectSqlQuery (\ s a -> s{_rdsdsSelectSqlQuery = a}); + +-- | The AWS Identity and Access Management (IAM) credentials that are used +-- connect to the Amazon RDS database. +rdsdsDatabaseCredentials :: Lens' RDSDataSpec RDSDatabaseCredentials +rdsdsDatabaseCredentials = lens _rdsdsDatabaseCredentials (\ s a -> s{_rdsdsDatabaseCredentials = a}); + +-- | The Amazon S3 location for staging Amazon RDS data. The data retrieved +-- from Amazon RDS using 'SelectSqlQuery' is stored in this location. +rdsdsS3StagingLocation :: Lens' RDSDataSpec Text +rdsdsS3StagingLocation = lens _rdsdsS3StagingLocation (\ s a -> s{_rdsdsS3StagingLocation = a}); + +-- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon Elastic +-- Compute Cloud (Amazon EC2) instance to carry out the copy operation from +-- Amazon RDS to an Amazon S3 task. For more information, see +-- +-- for data pipelines. +rdsdsResourceRole :: Lens' RDSDataSpec Text +rdsdsResourceRole = lens _rdsdsResourceRole (\ s a -> s{_rdsdsResourceRole = a}); + +-- | The role (DataPipelineDefaultRole) assumed by AWS Data Pipeline service +-- to monitor the progress of the copy task from Amazon RDS to Amazon S3. +-- For more information, see +-- +-- for data pipelines. +rdsdsServiceRole :: Lens' RDSDataSpec Text +rdsdsServiceRole = lens _rdsdsServiceRole (\ s a -> s{_rdsdsServiceRole = a}); + +-- | The subnet ID to be used to access a VPC-based RDS DB instance. This +-- attribute is used by Data Pipeline to carry out the copy task from +-- Amazon RDS to Amazon S3. +rdsdsSubnetId :: Lens' RDSDataSpec Text +rdsdsSubnetId = lens _rdsdsSubnetId (\ s a -> s{_rdsdsSubnetId = a}); + +-- | The security group IDs to be used to access a VPC-based RDS DB instance. +-- Ensure that there are appropriate ingress rules set up to allow access +-- to the RDS DB instance. This attribute is used by Data Pipeline to carry +-- out the copy operation from Amazon RDS to an Amazon S3 task. +rdsdsSecurityGroupIds :: Lens' RDSDataSpec [Text] +rdsdsSecurityGroupIds = lens _rdsdsSecurityGroupIds (\ s a -> s{_rdsdsSecurityGroupIds = a}) . _Coerce; + +instance ToJSON RDSDataSpec where + toJSON RDSDataSpec'{..} + = object + ["DataSchemaUri" .= _rdsdsDataSchemaURI, + "DataSchema" .= _rdsdsDataSchema, + "DataRearrangement" .= _rdsdsDataRearrangement, + "DatabaseInformation" .= _rdsdsDatabaseInformation, + "SelectSqlQuery" .= _rdsdsSelectSqlQuery, + "DatabaseCredentials" .= _rdsdsDatabaseCredentials, + "S3StagingLocation" .= _rdsdsS3StagingLocation, + "ResourceRole" .= _rdsdsResourceRole, + "ServiceRole" .= _rdsdsServiceRole, + "SubnetId" .= _rdsdsSubnetId, + "SecurityGroupIds" .= _rdsdsSecurityGroupIds] + +-- | The database details of an Amazon RDS database. +-- +-- /See:/ 'rdsDatabase' smart constructor. +data RDSDatabase = RDSDatabase' + { _rdsdInstanceIdentifier :: !Text + , _rdsdDatabaseName :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'RDSDatabase' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'rdsdInstanceIdentifier' +-- +-- * 'rdsdDatabaseName' +rdsDatabase + :: Text -- ^ 'rdsdInstanceIdentifier' + -> Text -- ^ 'rdsdDatabaseName' + -> RDSDatabase +rdsDatabase pInstanceIdentifier_ pDatabaseName_ = + RDSDatabase' + { _rdsdInstanceIdentifier = pInstanceIdentifier_ + , _rdsdDatabaseName = pDatabaseName_ + } + +-- | The ID of an RDS DB instance. +rdsdInstanceIdentifier :: Lens' RDSDatabase Text +rdsdInstanceIdentifier = lens _rdsdInstanceIdentifier (\ s a -> s{_rdsdInstanceIdentifier = a}); + +-- | Undocumented member. +rdsdDatabaseName :: Lens' RDSDatabase Text +rdsdDatabaseName = lens _rdsdDatabaseName (\ s a -> s{_rdsdDatabaseName = a}); + +instance FromJSON RDSDatabase where + parseJSON + = withObject "RDSDatabase" + (\ x -> + RDSDatabase' <$> + (x .: "InstanceIdentifier") <*> + (x .: "DatabaseName")) + +instance ToJSON RDSDatabase where + toJSON RDSDatabase'{..} + = object + ["InstanceIdentifier" .= _rdsdInstanceIdentifier, + "DatabaseName" .= _rdsdDatabaseName] + +-- | The database credentials to connect to a database on an RDS DB instance. +-- +-- /See:/ 'rdsDatabaseCredentials' smart constructor. +data RDSDatabaseCredentials = RDSDatabaseCredentials' + { _rdsdcUsername :: !Text + , _rdsdcPassword :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'RDSDatabaseCredentials' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'rdsdcUsername' +-- +-- * 'rdsdcPassword' +rdsDatabaseCredentials + :: Text -- ^ 'rdsdcUsername' + -> Text -- ^ 'rdsdcPassword' + -> RDSDatabaseCredentials +rdsDatabaseCredentials pUsername_ pPassword_ = + RDSDatabaseCredentials' + { _rdsdcUsername = pUsername_ + , _rdsdcPassword = pPassword_ + } + +-- | Undocumented member. +rdsdcUsername :: Lens' RDSDatabaseCredentials Text +rdsdcUsername = lens _rdsdcUsername (\ s a -> s{_rdsdcUsername = a}); + +-- | Undocumented member. +rdsdcPassword :: Lens' RDSDatabaseCredentials Text +rdsdcPassword = lens _rdsdcPassword (\ s a -> s{_rdsdcPassword = a}); + +instance ToJSON RDSDatabaseCredentials where + toJSON RDSDatabaseCredentials'{..} + = object + ["Username" .= _rdsdcUsername, + "Password" .= _rdsdcPassword] + +-- | The datasource details that are specific to Amazon RDS. +-- +-- /See:/ 'rdsMetadata' smart constructor. +data RDSMetadata = RDSMetadata' + { _rmSelectSqlQuery :: !(Maybe Text) + , _rmDataPipelineId :: !(Maybe Text) + , _rmDatabase :: !(Maybe RDSDatabase) + , _rmDatabaseUserName :: !(Maybe Text) + , _rmResourceRole :: !(Maybe Text) + , _rmServiceRole :: !(Maybe Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'RDSMetadata' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'rmSelectSqlQuery' +-- +-- * 'rmDataPipelineId' +-- +-- * 'rmDatabase' +-- +-- * 'rmDatabaseUserName' +-- +-- * 'rmResourceRole' +-- +-- * 'rmServiceRole' +rdsMetadata + :: RDSMetadata +rdsMetadata = + RDSMetadata' + { _rmSelectSqlQuery = Nothing + , _rmDataPipelineId = Nothing + , _rmDatabase = Nothing + , _rmDatabaseUserName = Nothing + , _rmResourceRole = Nothing + , _rmServiceRole = Nothing + } + +-- | The SQL query that is supplied during CreateDataSourceFromRDS. Returns +-- only if 'Verbose' is true in 'GetDataSourceInput'. +rmSelectSqlQuery :: Lens' RDSMetadata (Maybe Text) +rmSelectSqlQuery = lens _rmSelectSqlQuery (\ s a -> s{_rmSelectSqlQuery = a}); + +-- | The ID of the Data Pipeline instance that is used to carry to copy data +-- from Amazon RDS to Amazon S3. You can use the ID to find details about +-- the instance in the Data Pipeline console. +rmDataPipelineId :: Lens' RDSMetadata (Maybe Text) +rmDataPipelineId = lens _rmDataPipelineId (\ s a -> s{_rmDataPipelineId = a}); + +-- | The database details required to connect to an Amazon RDS. +rmDatabase :: Lens' RDSMetadata (Maybe RDSDatabase) +rmDatabase = lens _rmDatabase (\ s a -> s{_rmDatabase = a}); + +-- | Undocumented member. +rmDatabaseUserName :: Lens' RDSMetadata (Maybe Text) +rmDatabaseUserName = lens _rmDatabaseUserName (\ s a -> s{_rmDatabaseUserName = a}); + +-- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon EC2 +-- instance to carry out the copy task from Amazon RDS to Amazon S3. For +-- more information, see +-- +-- for data pipelines. +rmResourceRole :: Lens' RDSMetadata (Maybe Text) +rmResourceRole = lens _rmResourceRole (\ s a -> s{_rmResourceRole = a}); + +-- | The role (DataPipelineDefaultRole) assumed by the Data Pipeline service +-- to monitor the progress of the copy task from Amazon RDS to Amazon S3. +-- For more information, see +-- +-- for data pipelines. +rmServiceRole :: Lens' RDSMetadata (Maybe Text) +rmServiceRole = lens _rmServiceRole (\ s a -> s{_rmServiceRole = a}); + +instance FromJSON RDSMetadata where + parseJSON + = withObject "RDSMetadata" + (\ x -> + RDSMetadata' <$> + (x .:? "SelectSqlQuery") <*> (x .:? "DataPipelineId") + <*> (x .:? "Database") + <*> (x .:? "DatabaseUserName") + <*> (x .:? "ResourceRole") + <*> (x .:? "ServiceRole")) + +-- | Describes the real-time endpoint information for an 'MLModel'. +-- +-- /See:/ 'realtimeEndpointInfo' smart constructor. +data RealtimeEndpointInfo = RealtimeEndpointInfo' + { _reiCreatedAt :: !(Maybe POSIX) + , _reiEndpointURL :: !(Maybe Text) + , _reiEndpointStatus :: !(Maybe RealtimeEndpointStatus) + , _reiPeakRequestsPerSecond :: !(Maybe Int) + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'RealtimeEndpointInfo' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'reiCreatedAt' +-- +-- * 'reiEndpointURL' +-- +-- * 'reiEndpointStatus' +-- +-- * 'reiPeakRequestsPerSecond' +realtimeEndpointInfo + :: RealtimeEndpointInfo +realtimeEndpointInfo = + RealtimeEndpointInfo' + { _reiCreatedAt = Nothing + , _reiEndpointURL = Nothing + , _reiEndpointStatus = Nothing + , _reiPeakRequestsPerSecond = Nothing + } + +-- | The time that the request to create the real-time endpoint for the +-- 'MLModel' was received. The time is expressed in epoch time. +reiCreatedAt :: Lens' RealtimeEndpointInfo (Maybe UTCTime) +reiCreatedAt = lens _reiCreatedAt (\ s a -> s{_reiCreatedAt = a}) . mapping _Time; + +-- | The URI that specifies where to send real-time prediction requests for +-- the 'MLModel'. +-- +-- Note +-- +-- The application must wait until the real-time endpoint is ready before +-- using this URI. +reiEndpointURL :: Lens' RealtimeEndpointInfo (Maybe Text) +reiEndpointURL = lens _reiEndpointURL (\ s a -> s{_reiEndpointURL = a}); + +-- | The current status of the real-time endpoint for the 'MLModel'. This +-- element can have one of the following values: +-- +-- - NONE - Endpoint does not exist or was previously deleted. +-- - READY - Endpoint is ready to be used for real-time predictions. +-- - UPDATING - Updating\/creating the endpoint. +reiEndpointStatus :: Lens' RealtimeEndpointInfo (Maybe RealtimeEndpointStatus) +reiEndpointStatus = lens _reiEndpointStatus (\ s a -> s{_reiEndpointStatus = a}); + +-- | The maximum processing rate for the real-time endpoint for 'MLModel', +-- measured in incoming requests per second. +reiPeakRequestsPerSecond :: Lens' RealtimeEndpointInfo (Maybe Int) +reiPeakRequestsPerSecond = lens _reiPeakRequestsPerSecond (\ s a -> s{_reiPeakRequestsPerSecond = a}); + +instance FromJSON RealtimeEndpointInfo where + parseJSON + = withObject "RealtimeEndpointInfo" + (\ x -> + RealtimeEndpointInfo' <$> + (x .:? "CreatedAt") <*> (x .:? "EndpointUrl") <*> + (x .:? "EndpointStatus") + <*> (x .:? "PeakRequestsPerSecond")) + +-- | Describes the data specification of an Amazon Redshift 'DataSource'. +-- +-- /See:/ 'redshiftDataSpec' smart constructor. +data RedshiftDataSpec = RedshiftDataSpec' + { _rDataSchemaURI :: !(Maybe Text) + , _rDataSchema :: !(Maybe Text) + , _rDataRearrangement :: !(Maybe Text) + , _rDatabaseInformation :: !RedshiftDatabase + , _rSelectSqlQuery :: !Text + , _rDatabaseCredentials :: !RedshiftDatabaseCredentials + , _rS3StagingLocation :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'RedshiftDataSpec' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'rDataSchemaURI' +-- +-- * 'rDataSchema' +-- +-- * 'rDataRearrangement' +-- +-- * 'rDatabaseInformation' +-- +-- * 'rSelectSqlQuery' +-- +-- * 'rDatabaseCredentials' +-- +-- * 'rS3StagingLocation' +redshiftDataSpec + :: RedshiftDatabase -- ^ 'rDatabaseInformation' + -> Text -- ^ 'rSelectSqlQuery' + -> RedshiftDatabaseCredentials -- ^ 'rDatabaseCredentials' + -> Text -- ^ 'rS3StagingLocation' + -> RedshiftDataSpec +redshiftDataSpec pDatabaseInformation_ pSelectSqlQuery_ pDatabaseCredentials_ pS3StagingLocation_ = + RedshiftDataSpec' + { _rDataSchemaURI = Nothing + , _rDataSchema = Nothing + , _rDataRearrangement = Nothing + , _rDatabaseInformation = pDatabaseInformation_ + , _rSelectSqlQuery = pSelectSqlQuery_ + , _rDatabaseCredentials = pDatabaseCredentials_ + , _rS3StagingLocation = pS3StagingLocation_ + } + +-- | Describes the schema location for an Amazon Redshift 'DataSource'. +rDataSchemaURI :: Lens' RedshiftDataSpec (Maybe Text) +rDataSchemaURI = lens _rDataSchemaURI (\ s a -> s{_rDataSchemaURI = a}); + +-- | Describes the schema for an Amazon Redshift 'DataSource'. +rDataSchema :: Lens' RedshiftDataSpec (Maybe Text) +rDataSchema = lens _rDataSchema (\ s a -> s{_rDataSchema = a}); + +-- | Describes the splitting specifications for a 'DataSource'. +rDataRearrangement :: Lens' RedshiftDataSpec (Maybe Text) +rDataRearrangement = lens _rDataRearrangement (\ s a -> s{_rDataRearrangement = a}); + +-- | Describes the 'DatabaseName' and 'ClusterIdentifier' for an Amazon +-- Redshift 'DataSource'. +rDatabaseInformation :: Lens' RedshiftDataSpec RedshiftDatabase +rDatabaseInformation = lens _rDatabaseInformation (\ s a -> s{_rDatabaseInformation = a}); + +-- | Describes the SQL Query to execute on an Amazon Redshift database for an +-- Amazon Redshift 'DataSource'. +rSelectSqlQuery :: Lens' RedshiftDataSpec Text +rSelectSqlQuery = lens _rSelectSqlQuery (\ s a -> s{_rSelectSqlQuery = a}); + +-- | Describes AWS Identity and Access Management (IAM) credentials that are +-- used connect to the Amazon Redshift database. +rDatabaseCredentials :: Lens' RedshiftDataSpec RedshiftDatabaseCredentials +rDatabaseCredentials = lens _rDatabaseCredentials (\ s a -> s{_rDatabaseCredentials = a}); + +-- | Describes an Amazon S3 location to store the result set of the +-- 'SelectSqlQuery' query. +rS3StagingLocation :: Lens' RedshiftDataSpec Text +rS3StagingLocation = lens _rS3StagingLocation (\ s a -> s{_rS3StagingLocation = a}); + +instance ToJSON RedshiftDataSpec where + toJSON RedshiftDataSpec'{..} + = object + ["DataSchemaUri" .= _rDataSchemaURI, + "DataSchema" .= _rDataSchema, + "DataRearrangement" .= _rDataRearrangement, + "DatabaseInformation" .= _rDatabaseInformation, + "SelectSqlQuery" .= _rSelectSqlQuery, + "DatabaseCredentials" .= _rDatabaseCredentials, + "S3StagingLocation" .= _rS3StagingLocation] + +-- | Describes the database details required to connect to an Amazon Redshift +-- database. +-- +-- /See:/ 'redshiftDatabase' smart constructor. +data RedshiftDatabase = RedshiftDatabase' + { _rdDatabaseName :: !Text + , _rdClusterIdentifier :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'RedshiftDatabase' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'rdDatabaseName' +-- +-- * 'rdClusterIdentifier' +redshiftDatabase + :: Text -- ^ 'rdDatabaseName' + -> Text -- ^ 'rdClusterIdentifier' + -> RedshiftDatabase +redshiftDatabase pDatabaseName_ pClusterIdentifier_ = + RedshiftDatabase' + { _rdDatabaseName = pDatabaseName_ + , _rdClusterIdentifier = pClusterIdentifier_ + } + +-- | Undocumented member. +rdDatabaseName :: Lens' RedshiftDatabase Text +rdDatabaseName = lens _rdDatabaseName (\ s a -> s{_rdDatabaseName = a}); + +-- | Undocumented member. +rdClusterIdentifier :: Lens' RedshiftDatabase Text +rdClusterIdentifier = lens _rdClusterIdentifier (\ s a -> s{_rdClusterIdentifier = a}); + +instance FromJSON RedshiftDatabase where + parseJSON + = withObject "RedshiftDatabase" + (\ x -> + RedshiftDatabase' <$> + (x .: "DatabaseName") <*> (x .: "ClusterIdentifier")) + +instance ToJSON RedshiftDatabase where + toJSON RedshiftDatabase'{..} + = object + ["DatabaseName" .= _rdDatabaseName, + "ClusterIdentifier" .= _rdClusterIdentifier] + +-- | Describes the database credentials for connecting to a database on an +-- Amazon Redshift cluster. +-- +-- /See:/ 'redshiftDatabaseCredentials' smart constructor. +data RedshiftDatabaseCredentials = RedshiftDatabaseCredentials' + { _rdcUsername :: !Text + , _rdcPassword :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'RedshiftDatabaseCredentials' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'rdcUsername' +-- +-- * 'rdcPassword' +redshiftDatabaseCredentials + :: Text -- ^ 'rdcUsername' + -> Text -- ^ 'rdcPassword' + -> RedshiftDatabaseCredentials +redshiftDatabaseCredentials pUsername_ pPassword_ = + RedshiftDatabaseCredentials' + { _rdcUsername = pUsername_ + , _rdcPassword = pPassword_ + } + +-- | Undocumented member. +rdcUsername :: Lens' RedshiftDatabaseCredentials Text +rdcUsername = lens _rdcUsername (\ s a -> s{_rdcUsername = a}); + +-- | Undocumented member. +rdcPassword :: Lens' RedshiftDatabaseCredentials Text +rdcPassword = lens _rdcPassword (\ s a -> s{_rdcPassword = a}); + +instance ToJSON RedshiftDatabaseCredentials where + toJSON RedshiftDatabaseCredentials'{..} + = object + ["Username" .= _rdcUsername, + "Password" .= _rdcPassword] + +-- | Describes the 'DataSource' details specific to Amazon Redshift. +-- +-- /See:/ 'redshiftMetadata' smart constructor. +data RedshiftMetadata = RedshiftMetadata' + { _redSelectSqlQuery :: !(Maybe Text) + , _redRedshiftDatabase :: !(Maybe RedshiftDatabase) + , _redDatabaseUserName :: !(Maybe Text) + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'RedshiftMetadata' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'redSelectSqlQuery' +-- +-- * 'redRedshiftDatabase' +-- +-- * 'redDatabaseUserName' +redshiftMetadata + :: RedshiftMetadata +redshiftMetadata = + RedshiftMetadata' + { _redSelectSqlQuery = Nothing + , _redRedshiftDatabase = Nothing + , _redDatabaseUserName = Nothing + } + +-- | The SQL query that is specified during CreateDataSourceFromRedshift. +-- Returns only if 'Verbose' is true in GetDataSourceInput. +redSelectSqlQuery :: Lens' RedshiftMetadata (Maybe Text) +redSelectSqlQuery = lens _redSelectSqlQuery (\ s a -> s{_redSelectSqlQuery = a}); + +-- | Undocumented member. +redRedshiftDatabase :: Lens' RedshiftMetadata (Maybe RedshiftDatabase) +redRedshiftDatabase = lens _redRedshiftDatabase (\ s a -> s{_redRedshiftDatabase = a}); + +-- | Undocumented member. +redDatabaseUserName :: Lens' RedshiftMetadata (Maybe Text) +redDatabaseUserName = lens _redDatabaseUserName (\ s a -> s{_redDatabaseUserName = a}); + +instance FromJSON RedshiftMetadata where + parseJSON + = withObject "RedshiftMetadata" + (\ x -> + RedshiftMetadata' <$> + (x .:? "SelectSqlQuery") <*> + (x .:? "RedshiftDatabase") + <*> (x .:? "DatabaseUserName")) + +-- | Describes the data specification of a 'DataSource'. +-- +-- /See:/ 's3DataSpec' smart constructor. +data S3DataSpec = S3DataSpec' + { _sdsDataSchema :: !(Maybe Text) + , _sdsDataSchemaLocationS3 :: !(Maybe Text) + , _sdsDataRearrangement :: !(Maybe Text) + , _sdsDataLocationS3 :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'S3DataSpec' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'sdsDataSchema' +-- +-- * 'sdsDataSchemaLocationS3' +-- +-- * 'sdsDataRearrangement' +-- +-- * 'sdsDataLocationS3' +s3DataSpec + :: Text -- ^ 'sdsDataLocationS3' + -> S3DataSpec +s3DataSpec pDataLocationS3_ = + S3DataSpec' + { _sdsDataSchema = Nothing + , _sdsDataSchemaLocationS3 = Nothing + , _sdsDataRearrangement = Nothing + , _sdsDataLocationS3 = pDataLocationS3_ + } + +-- | Describes the schema for an Amazon S3 'DataSource'. +sdsDataSchema :: Lens' S3DataSpec (Maybe Text) +sdsDataSchema = lens _sdsDataSchema (\ s a -> s{_sdsDataSchema = a}); + +-- | Describes the schema Location in Amazon S3. +sdsDataSchemaLocationS3 :: Lens' S3DataSpec (Maybe Text) +sdsDataSchemaLocationS3 = lens _sdsDataSchemaLocationS3 (\ s a -> s{_sdsDataSchemaLocationS3 = a}); + +-- | Describes the splitting requirement of a 'Datasource'. +sdsDataRearrangement :: Lens' S3DataSpec (Maybe Text) +sdsDataRearrangement = lens _sdsDataRearrangement (\ s a -> s{_sdsDataRearrangement = a}); + +-- | The location of the data file(s) used by a 'DataSource'. The URI +-- specifies a data file or an Amazon Simple Storage Service (Amazon S3) +-- directory or bucket containing data files. +sdsDataLocationS3 :: Lens' S3DataSpec Text +sdsDataLocationS3 = lens _sdsDataLocationS3 (\ s a -> s{_sdsDataLocationS3 = a}); + +instance ToJSON S3DataSpec where + toJSON S3DataSpec'{..} + = object + ["DataSchema" .= _sdsDataSchema, + "DataSchemaLocationS3" .= _sdsDataSchemaLocationS3, + "DataRearrangement" .= _sdsDataRearrangement, + "DataLocationS3" .= _sdsDataLocationS3] diff --git a/gen/Network/AWS/MachineLearning/Types/Sum.hs b/gen/Network/AWS/MachineLearning/Types/Sum.hs new file mode 100644 --- /dev/null +++ b/gen/Network/AWS/MachineLearning/Types/Sum.hs @@ -0,0 +1,429 @@ +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE LambdaCase #-} +{-# LANGUAGE OverloadedStrings #-} + +{-# OPTIONS_GHC -fno-warn-unused-imports #-} + +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | +-- Module : Network.AWS.MachineLearning.Types.Sum +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. +-- Maintainer : Brendan Hay +-- Stability : auto-generated +-- Portability : non-portable (GHC extensions) +-- +module Network.AWS.MachineLearning.Types.Sum where + +import Network.AWS.Prelude + +-- | The function used to train a 'MLModel'. Training choices supported by +-- Amazon ML include the following: +-- +-- - SGD - Stochastic Gradient Descent. +-- - RandomForest - Random forest of decision trees. +data Algorithm = + SGD + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText Algorithm where + parser = takeLowerText >>= \case + "sgd" -> pure SGD + e -> fromTextError $ "Failure parsing Algorithm from value: '" <> e + <> "'. Accepted values: sgd" + +instance ToText Algorithm where + toText = \case + SGD -> "sgd" + +instance Hashable Algorithm +instance ToByteString Algorithm +instance ToQuery Algorithm +instance ToHeader Algorithm + +instance FromJSON Algorithm where + parseJSON = parseJSONText "Algorithm" + +-- | A list of the variables to use in searching or filtering +-- 'BatchPrediction'. +-- +-- - 'CreatedAt' - Sets the search criteria to 'BatchPrediction' creation +-- date. +-- - 'Status' - Sets the search criteria to 'BatchPrediction' status. +-- - 'Name' - Sets the search criteria to the contents of +-- 'BatchPrediction' ____ 'Name'. +-- - 'IAMUser' - Sets the search criteria to the user account that +-- invoked the 'BatchPrediction' creation. +-- - 'MLModelId' - Sets the search criteria to the 'MLModel' used in the +-- 'BatchPrediction'. +-- - 'DataSourceId' - Sets the search criteria to the 'DataSource' used +-- in the 'BatchPrediction'. +-- - 'DataURI' - Sets the search criteria to the data file(s) used in the +-- 'BatchPrediction'. The URL can identify either a file or an Amazon +-- Simple Storage Service (Amazon S3) bucket or directory. +data BatchPredictionFilterVariable + = BatchCreatedAt + | BatchDataSourceId + | BatchDataURI + | BatchIAMUser + | BatchLastUpdatedAt + | BatchMLModelId + | BatchName + | BatchStatus + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText BatchPredictionFilterVariable where + parser = takeLowerText >>= \case + "createdat" -> pure BatchCreatedAt + "datasourceid" -> pure BatchDataSourceId + "datauri" -> pure BatchDataURI + "iamuser" -> pure BatchIAMUser + "lastupdatedat" -> pure BatchLastUpdatedAt + "mlmodelid" -> pure BatchMLModelId + "name" -> pure BatchName + "status" -> pure BatchStatus + e -> fromTextError $ "Failure parsing BatchPredictionFilterVariable from value: '" <> e + <> "'. Accepted values: createdat, datasourceid, datauri, iamuser, lastupdatedat, mlmodelid, name, status" + +instance ToText BatchPredictionFilterVariable where + toText = \case + BatchCreatedAt -> "createdat" + BatchDataSourceId -> "datasourceid" + BatchDataURI -> "datauri" + BatchIAMUser -> "iamuser" + BatchLastUpdatedAt -> "lastupdatedat" + BatchMLModelId -> "mlmodelid" + BatchName -> "name" + BatchStatus -> "status" + +instance Hashable BatchPredictionFilterVariable +instance ToByteString BatchPredictionFilterVariable +instance ToQuery BatchPredictionFilterVariable +instance ToHeader BatchPredictionFilterVariable + +instance ToJSON BatchPredictionFilterVariable where + toJSON = toJSONText + +-- | A list of the variables to use in searching or filtering 'DataSource'. +-- +-- - 'CreatedAt' - Sets the search criteria to 'DataSource' creation +-- date. +-- - 'Status' - Sets the search criteria to 'DataSource' status. +-- - 'Name' - Sets the search criteria to the contents of 'DataSource' +-- ____ 'Name'. +-- - 'DataUri' - Sets the search criteria to the URI of data files used +-- to create the 'DataSource'. The URI can identify either a file or an +-- Amazon Simple Storage Service (Amazon S3) bucket or directory. +-- - 'IAMUser' - Sets the search criteria to the user account that +-- invoked the 'DataSource' creation. +-- +-- Note +-- +-- The variable names should match the variable names in the 'DataSource'. +data DataSourceFilterVariable + = DataCreatedAt + | DataDATALOCATIONS3 + | DataIAMUser + | DataLastUpdatedAt + | DataName + | DataStatus + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText DataSourceFilterVariable where + parser = takeLowerText >>= \case + "createdat" -> pure DataCreatedAt + "datalocations3" -> pure DataDATALOCATIONS3 + "iamuser" -> pure DataIAMUser + "lastupdatedat" -> pure DataLastUpdatedAt + "name" -> pure DataName + "status" -> pure DataStatus + e -> fromTextError $ "Failure parsing DataSourceFilterVariable from value: '" <> e + <> "'. Accepted values: createdat, datalocations3, iamuser, lastupdatedat, name, status" + +instance ToText DataSourceFilterVariable where + toText = \case + DataCreatedAt -> "createdat" + DataDATALOCATIONS3 -> "datalocations3" + DataIAMUser -> "iamuser" + DataLastUpdatedAt -> "lastupdatedat" + DataName -> "name" + DataStatus -> "status" + +instance Hashable DataSourceFilterVariable +instance ToByteString DataSourceFilterVariable +instance ToQuery DataSourceFilterVariable +instance ToHeader DataSourceFilterVariable + +instance ToJSON DataSourceFilterVariable where + toJSON = toJSONText + +-- | Contains the key values of 'DetailsMap': PredictiveModelType - Indicates +-- the type of the 'MLModel'. Algorithm - Indicates the algorithm was used +-- for the 'MLModel'. +data DetailsAttributes + = Algorithm + | PredictiveModelType + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText DetailsAttributes where + parser = takeLowerText >>= \case + "algorithm" -> pure Algorithm + "predictivemodeltype" -> pure PredictiveModelType + e -> fromTextError $ "Failure parsing DetailsAttributes from value: '" <> e + <> "'. Accepted values: algorithm, predictivemodeltype" + +instance ToText DetailsAttributes where + toText = \case + Algorithm -> "algorithm" + PredictiveModelType -> "predictivemodeltype" + +instance Hashable DetailsAttributes +instance ToByteString DetailsAttributes +instance ToQuery DetailsAttributes +instance ToHeader DetailsAttributes + +instance FromJSON DetailsAttributes where + parseJSON = parseJSONText "DetailsAttributes" + +-- | Entity status with the following possible values: +-- +-- - PENDING +-- - INPROGRESS +-- - FAILED +-- - COMPLETED +-- - DELETED +data EntityStatus + = Completed + | Deleted + | Failed + | Inprogress + | Pending + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText EntityStatus where + parser = takeLowerText >>= \case + "completed" -> pure Completed + "deleted" -> pure Deleted + "failed" -> pure Failed + "inprogress" -> pure Inprogress + "pending" -> pure Pending + e -> fromTextError $ "Failure parsing EntityStatus from value: '" <> e + <> "'. Accepted values: completed, deleted, failed, inprogress, pending" + +instance ToText EntityStatus where + toText = \case + Completed -> "completed" + Deleted -> "deleted" + Failed -> "failed" + Inprogress -> "inprogress" + Pending -> "pending" + +instance Hashable EntityStatus +instance ToByteString EntityStatus +instance ToQuery EntityStatus +instance ToHeader EntityStatus + +instance FromJSON EntityStatus where + parseJSON = parseJSONText "EntityStatus" + +-- | A list of the variables to use in searching or filtering 'Evaluation'. +-- +-- - 'CreatedAt' - Sets the search criteria to 'Evaluation' creation +-- date. +-- - 'Status' - Sets the search criteria to 'Evaluation' status. +-- - 'Name' - Sets the search criteria to the contents of 'Evaluation' +-- ____ 'Name'. +-- - 'IAMUser' - Sets the search criteria to the user account that +-- invoked an evaluation. +-- - 'MLModelId' - Sets the search criteria to the 'Predictor' that was +-- evaluated. +-- - 'DataSourceId' - Sets the search criteria to the 'DataSource' used +-- in evaluation. +-- - 'DataUri' - Sets the search criteria to the data file(s) used in +-- evaluation. The URL can identify either a file or an Amazon Simple +-- Storage Service (Amazon S3) bucket or directory. +data EvaluationFilterVariable + = EvalCreatedAt + | EvalDataSourceId + | EvalDataURI + | EvalIAMUser + | EvalLastUpdatedAt + | EvalMLModelId + | EvalName + | EvalStatus + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText EvaluationFilterVariable where + parser = takeLowerText >>= \case + "createdat" -> pure EvalCreatedAt + "datasourceid" -> pure EvalDataSourceId + "datauri" -> pure EvalDataURI + "iamuser" -> pure EvalIAMUser + "lastupdatedat" -> pure EvalLastUpdatedAt + "mlmodelid" -> pure EvalMLModelId + "name" -> pure EvalName + "status" -> pure EvalStatus + e -> fromTextError $ "Failure parsing EvaluationFilterVariable from value: '" <> e + <> "'. Accepted values: createdat, datasourceid, datauri, iamuser, lastupdatedat, mlmodelid, name, status" + +instance ToText EvaluationFilterVariable where + toText = \case + EvalCreatedAt -> "createdat" + EvalDataSourceId -> "datasourceid" + EvalDataURI -> "datauri" + EvalIAMUser -> "iamuser" + EvalLastUpdatedAt -> "lastupdatedat" + EvalMLModelId -> "mlmodelid" + EvalName -> "name" + EvalStatus -> "status" + +instance Hashable EvaluationFilterVariable +instance ToByteString EvaluationFilterVariable +instance ToQuery EvaluationFilterVariable +instance ToHeader EvaluationFilterVariable + +instance ToJSON EvaluationFilterVariable where + toJSON = toJSONText + +data MLModelFilterVariable + = MLMFVAlgorithm + | MLMFVCreatedAt + | MLMFVIAMUser + | MLMFVLastUpdatedAt + | MLMFVMLModelType + | MLMFVName + | MLMFVRealtimeEndpointStatus + | MLMFVStatus + | MLMFVTrainingDataSourceId + | MLMFVTrainingDataURI + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText MLModelFilterVariable where + parser = takeLowerText >>= \case + "algorithm" -> pure MLMFVAlgorithm + "createdat" -> pure MLMFVCreatedAt + "iamuser" -> pure MLMFVIAMUser + "lastupdatedat" -> pure MLMFVLastUpdatedAt + "mlmodeltype" -> pure MLMFVMLModelType + "name" -> pure MLMFVName + "realtimeendpointstatus" -> pure MLMFVRealtimeEndpointStatus + "status" -> pure MLMFVStatus + "trainingdatasourceid" -> pure MLMFVTrainingDataSourceId + "trainingdatauri" -> pure MLMFVTrainingDataURI + e -> fromTextError $ "Failure parsing MLModelFilterVariable from value: '" <> e + <> "'. Accepted values: algorithm, createdat, iamuser, lastupdatedat, mlmodeltype, name, realtimeendpointstatus, status, trainingdatasourceid, trainingdatauri" + +instance ToText MLModelFilterVariable where + toText = \case + MLMFVAlgorithm -> "algorithm" + MLMFVCreatedAt -> "createdat" + MLMFVIAMUser -> "iamuser" + MLMFVLastUpdatedAt -> "lastupdatedat" + MLMFVMLModelType -> "mlmodeltype" + MLMFVName -> "name" + MLMFVRealtimeEndpointStatus -> "realtimeendpointstatus" + MLMFVStatus -> "status" + MLMFVTrainingDataSourceId -> "trainingdatasourceid" + MLMFVTrainingDataURI -> "trainingdatauri" + +instance Hashable MLModelFilterVariable +instance ToByteString MLModelFilterVariable +instance ToQuery MLModelFilterVariable +instance ToHeader MLModelFilterVariable + +instance ToJSON MLModelFilterVariable where + toJSON = toJSONText + +data MLModelType + = Binary + | Multiclass + | Regression + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText MLModelType where + parser = takeLowerText >>= \case + "binary" -> pure Binary + "multiclass" -> pure Multiclass + "regression" -> pure Regression + e -> fromTextError $ "Failure parsing MLModelType from value: '" <> e + <> "'. Accepted values: binary, multiclass, regression" + +instance ToText MLModelType where + toText = \case + Binary -> "binary" + Multiclass -> "multiclass" + Regression -> "regression" + +instance Hashable MLModelType +instance ToByteString MLModelType +instance ToQuery MLModelType +instance ToHeader MLModelType + +instance ToJSON MLModelType where + toJSON = toJSONText + +instance FromJSON MLModelType where + parseJSON = parseJSONText "MLModelType" + +data RealtimeEndpointStatus + = RESFailed + | RESNone + | RESReady + | RESUpdating + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText RealtimeEndpointStatus where + parser = takeLowerText >>= \case + "failed" -> pure RESFailed + "none" -> pure RESNone + "ready" -> pure RESReady + "updating" -> pure RESUpdating + e -> fromTextError $ "Failure parsing RealtimeEndpointStatus from value: '" <> e + <> "'. Accepted values: failed, none, ready, updating" + +instance ToText RealtimeEndpointStatus where + toText = \case + RESFailed -> "failed" + RESNone -> "none" + RESReady -> "ready" + RESUpdating -> "updating" + +instance Hashable RealtimeEndpointStatus +instance ToByteString RealtimeEndpointStatus +instance ToQuery RealtimeEndpointStatus +instance ToHeader RealtimeEndpointStatus + +instance FromJSON RealtimeEndpointStatus where + parseJSON = parseJSONText "RealtimeEndpointStatus" + +-- | The sort order specified in a listing condition. Possible values include +-- the following: +-- +-- - 'asc' - Present the information in ascending order (from A-Z). +-- - 'dsc' - Present the information in descending order (from Z-A). +data SortOrder + = Asc + | Dsc + deriving (Eq,Ord,Read,Show,Enum,Data,Typeable,Generic) + +instance FromText SortOrder where + parser = takeLowerText >>= \case + "asc" -> pure Asc + "dsc" -> pure Dsc + e -> fromTextError $ "Failure parsing SortOrder from value: '" <> e + <> "'. Accepted values: asc, dsc" + +instance ToText SortOrder where + toText = \case + Asc -> "asc" + Dsc -> "dsc" + +instance Hashable SortOrder +instance ToByteString SortOrder +instance ToQuery SortOrder +instance ToHeader SortOrder + +instance ToJSON SortOrder where + toJSON = toJSONText diff --git a/gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs b/gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs --- a/gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs +++ b/gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs @@ -1,130 +1,149 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.UpdateBatchPrediction --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Updates the 'BatchPredictionName' of a 'BatchPrediction'. +-- Updates the 'BatchPredictionName' of a 'BatchPrediction'. -- --- You can use the 'GetBatchPrediction' operation to view the contents of the +-- You can use the GetBatchPrediction operation to view the contents of the -- updated data element. -- --- +-- /See:/ for UpdateBatchPrediction. module Network.AWS.MachineLearning.UpdateBatchPrediction ( - -- * Request - UpdateBatchPrediction - -- ** Request constructor - , updateBatchPrediction - -- ** Request lenses + -- * Creating a Request + updateBatchPrediction + , UpdateBatchPrediction + -- * Request Lenses , ubpBatchPredictionId , ubpBatchPredictionName - -- * Response - , UpdateBatchPredictionResponse - -- ** Response constructor + -- * Destructuring the Response , updateBatchPredictionResponse - -- ** Response lenses - , ubprBatchPredictionId + , UpdateBatchPredictionResponse + -- * Response Lenses + , ubprsBatchPredictionId + , ubprsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data UpdateBatchPrediction = UpdateBatchPrediction - { _ubpBatchPredictionId :: Text - , _ubpBatchPredictionName :: Text - } deriving (Eq, Ord, Read, Show) +-- | /See:/ 'updateBatchPrediction' smart constructor. +data UpdateBatchPrediction = UpdateBatchPrediction' + { _ubpBatchPredictionId :: !Text + , _ubpBatchPredictionName :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'UpdateBatchPrediction' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'UpdateBatchPrediction' with the minimum fields required to make a request. -- --- * 'ubpBatchPredictionId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'ubpBatchPredictionName' @::@ 'Text' +-- * 'ubpBatchPredictionId' -- -updateBatchPrediction :: Text -- ^ 'ubpBatchPredictionId' - -> Text -- ^ 'ubpBatchPredictionName' - -> UpdateBatchPrediction -updateBatchPrediction p1 p2 = UpdateBatchPrediction - { _ubpBatchPredictionId = p1 - , _ubpBatchPredictionName = p2 +-- * 'ubpBatchPredictionName' +updateBatchPrediction + :: Text -- ^ 'ubpBatchPredictionId' + -> Text -- ^ 'ubpBatchPredictionName' + -> UpdateBatchPrediction +updateBatchPrediction pBatchPredictionId_ pBatchPredictionName_ = + UpdateBatchPrediction' + { _ubpBatchPredictionId = pBatchPredictionId_ + , _ubpBatchPredictionName = pBatchPredictionName_ } -- | The ID assigned to the 'BatchPrediction' during creation. ubpBatchPredictionId :: Lens' UpdateBatchPrediction Text -ubpBatchPredictionId = - lens _ubpBatchPredictionId (\s a -> s { _ubpBatchPredictionId = a }) +ubpBatchPredictionId = lens _ubpBatchPredictionId (\ s a -> s{_ubpBatchPredictionId = a}); -- | A new user-supplied name or description of the 'BatchPrediction'. ubpBatchPredictionName :: Lens' UpdateBatchPrediction Text -ubpBatchPredictionName = - lens _ubpBatchPredictionName (\s a -> s { _ubpBatchPredictionName = a }) +ubpBatchPredictionName = lens _ubpBatchPredictionName (\ s a -> s{_ubpBatchPredictionName = a}); -newtype UpdateBatchPredictionResponse = UpdateBatchPredictionResponse - { _ubprBatchPredictionId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest UpdateBatchPrediction where + type Sv UpdateBatchPrediction = MachineLearning + type Rs UpdateBatchPrediction = + UpdateBatchPredictionResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + UpdateBatchPredictionResponse' <$> + (x .?> "BatchPredictionId") <*> (pure (fromEnum s))) --- | 'UpdateBatchPredictionResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'ubprBatchPredictionId' @::@ 'Maybe' 'Text' --- -updateBatchPredictionResponse :: UpdateBatchPredictionResponse -updateBatchPredictionResponse = UpdateBatchPredictionResponse - { _ubprBatchPredictionId = Nothing - } +instance ToHeaders UpdateBatchPrediction where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.UpdateBatchPrediction" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | The ID assigned to the 'BatchPrediction' during creation. This value should be --- identical to the value of the 'BatchPredictionId' in the request. -ubprBatchPredictionId :: Lens' UpdateBatchPredictionResponse (Maybe Text) -ubprBatchPredictionId = - lens _ubprBatchPredictionId (\s a -> s { _ubprBatchPredictionId = a }) +instance ToJSON UpdateBatchPrediction where + toJSON UpdateBatchPrediction'{..} + = object + ["BatchPredictionId" .= _ubpBatchPredictionId, + "BatchPredictionName" .= _ubpBatchPredictionName] instance ToPath UpdateBatchPrediction where - toPath = const "/" + toPath = const "/" instance ToQuery UpdateBatchPrediction where - toQuery = const mempty - -instance ToHeaders UpdateBatchPrediction + toQuery = const mempty -instance ToJSON UpdateBatchPrediction where - toJSON UpdateBatchPrediction{..} = object - [ "BatchPredictionId" .= _ubpBatchPredictionId - , "BatchPredictionName" .= _ubpBatchPredictionName - ] +-- | Represents the output of an UpdateBatchPrediction operation. +-- +-- You can see the updated content by using the GetBatchPrediction +-- operation. +-- +-- /See:/ 'updateBatchPredictionResponse' smart constructor. +data UpdateBatchPredictionResponse = UpdateBatchPredictionResponse' + { _ubprsBatchPredictionId :: !(Maybe Text) + , _ubprsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest UpdateBatchPrediction where - type Sv UpdateBatchPrediction = MachineLearning - type Rs UpdateBatchPrediction = UpdateBatchPredictionResponse +-- | Creates a value of 'UpdateBatchPredictionResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'ubprsBatchPredictionId' +-- +-- * 'ubprsStatus' +updateBatchPredictionResponse + :: Int -- ^ 'ubprsStatus' + -> UpdateBatchPredictionResponse +updateBatchPredictionResponse pStatus_ = + UpdateBatchPredictionResponse' + { _ubprsBatchPredictionId = Nothing + , _ubprsStatus = pStatus_ + } - request = post "UpdateBatchPrediction" - response = jsonResponse +-- | The ID assigned to the 'BatchPrediction' during creation. This value +-- should be identical to the value of the 'BatchPredictionId' in the +-- request. +ubprsBatchPredictionId :: Lens' UpdateBatchPredictionResponse (Maybe Text) +ubprsBatchPredictionId = lens _ubprsBatchPredictionId (\ s a -> s{_ubprsBatchPredictionId = a}); -instance FromJSON UpdateBatchPredictionResponse where - parseJSON = withObject "UpdateBatchPredictionResponse" $ \o -> UpdateBatchPredictionResponse - <$> o .:? "BatchPredictionId" +-- | The response status code. +ubprsStatus :: Lens' UpdateBatchPredictionResponse Int +ubprsStatus = lens _ubprsStatus (\ s a -> s{_ubprsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/UpdateDataSource.hs b/gen/Network/AWS/MachineLearning/UpdateDataSource.hs --- a/gen/Network/AWS/MachineLearning/UpdateDataSource.hs +++ b/gen/Network/AWS/MachineLearning/UpdateDataSource.hs @@ -1,129 +1,147 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.UpdateDataSource --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Updates the 'DataSourceName' of a 'DataSource'. +-- Updates the 'DataSourceName' of a 'DataSource'. -- --- You can use the 'GetDataSource' operation to view the contents of the updated --- data element. +-- You can use the GetDataSource operation to view the contents of the +-- updated data element. -- --- +-- /See:/ for UpdateDataSource. module Network.AWS.MachineLearning.UpdateDataSource ( - -- * Request - UpdateDataSource - -- ** Request constructor - , updateDataSource - -- ** Request lenses + -- * Creating a Request + updateDataSource + , UpdateDataSource + -- * Request Lenses , udsDataSourceId , udsDataSourceName - -- * Response - , UpdateDataSourceResponse - -- ** Response constructor + -- * Destructuring the Response , updateDataSourceResponse - -- ** Response lenses - , udsrDataSourceId + , UpdateDataSourceResponse + -- * Response Lenses + , udsrsDataSourceId + , udsrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data UpdateDataSource = UpdateDataSource - { _udsDataSourceId :: Text - , _udsDataSourceName :: Text - } deriving (Eq, Ord, Read, Show) +-- | /See:/ 'updateDataSource' smart constructor. +data UpdateDataSource = UpdateDataSource' + { _udsDataSourceId :: !Text + , _udsDataSourceName :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'UpdateDataSource' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'UpdateDataSource' with the minimum fields required to make a request. -- --- * 'udsDataSourceId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'udsDataSourceName' @::@ 'Text' +-- * 'udsDataSourceId' -- -updateDataSource :: Text -- ^ 'udsDataSourceId' - -> Text -- ^ 'udsDataSourceName' - -> UpdateDataSource -updateDataSource p1 p2 = UpdateDataSource - { _udsDataSourceId = p1 - , _udsDataSourceName = p2 +-- * 'udsDataSourceName' +updateDataSource + :: Text -- ^ 'udsDataSourceId' + -> Text -- ^ 'udsDataSourceName' + -> UpdateDataSource +updateDataSource pDataSourceId_ pDataSourceName_ = + UpdateDataSource' + { _udsDataSourceId = pDataSourceId_ + , _udsDataSourceName = pDataSourceName_ } -- | The ID assigned to the 'DataSource' during creation. udsDataSourceId :: Lens' UpdateDataSource Text -udsDataSourceId = lens _udsDataSourceId (\s a -> s { _udsDataSourceId = a }) +udsDataSourceId = lens _udsDataSourceId (\ s a -> s{_udsDataSourceId = a}); --- | A new user-supplied name or description of the 'DataSource' that will replace --- the current description. +-- | A new user-supplied name or description of the 'DataSource' that will +-- replace the current description. udsDataSourceName :: Lens' UpdateDataSource Text -udsDataSourceName = - lens _udsDataSourceName (\s a -> s { _udsDataSourceName = a }) +udsDataSourceName = lens _udsDataSourceName (\ s a -> s{_udsDataSourceName = a}); -newtype UpdateDataSourceResponse = UpdateDataSourceResponse - { _udsrDataSourceId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest UpdateDataSource where + type Sv UpdateDataSource = MachineLearning + type Rs UpdateDataSource = UpdateDataSourceResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + UpdateDataSourceResponse' <$> + (x .?> "DataSourceId") <*> (pure (fromEnum s))) --- | 'UpdateDataSourceResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'udsrDataSourceId' @::@ 'Maybe' 'Text' --- -updateDataSourceResponse :: UpdateDataSourceResponse -updateDataSourceResponse = UpdateDataSourceResponse - { _udsrDataSourceId = Nothing - } +instance ToHeaders UpdateDataSource where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.UpdateDataSource" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | The ID assigned to the 'DataSource' during creation. This value should be --- identical to the value of the 'DataSourceID' in the request. -udsrDataSourceId :: Lens' UpdateDataSourceResponse (Maybe Text) -udsrDataSourceId = lens _udsrDataSourceId (\s a -> s { _udsrDataSourceId = a }) +instance ToJSON UpdateDataSource where + toJSON UpdateDataSource'{..} + = object + ["DataSourceId" .= _udsDataSourceId, + "DataSourceName" .= _udsDataSourceName] instance ToPath UpdateDataSource where - toPath = const "/" + toPath = const "/" instance ToQuery UpdateDataSource where - toQuery = const mempty - -instance ToHeaders UpdateDataSource + toQuery = const mempty -instance ToJSON UpdateDataSource where - toJSON UpdateDataSource{..} = object - [ "DataSourceId" .= _udsDataSourceId - , "DataSourceName" .= _udsDataSourceName - ] +-- | Represents the output of an UpdateDataSource operation. +-- +-- You can see the updated content by using the GetBatchPrediction +-- operation. +-- +-- /See:/ 'updateDataSourceResponse' smart constructor. +data UpdateDataSourceResponse = UpdateDataSourceResponse' + { _udsrsDataSourceId :: !(Maybe Text) + , _udsrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest UpdateDataSource where - type Sv UpdateDataSource = MachineLearning - type Rs UpdateDataSource = UpdateDataSourceResponse +-- | Creates a value of 'UpdateDataSourceResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'udsrsDataSourceId' +-- +-- * 'udsrsStatus' +updateDataSourceResponse + :: Int -- ^ 'udsrsStatus' + -> UpdateDataSourceResponse +updateDataSourceResponse pStatus_ = + UpdateDataSourceResponse' + { _udsrsDataSourceId = Nothing + , _udsrsStatus = pStatus_ + } - request = post "UpdateDataSource" - response = jsonResponse +-- | The ID assigned to the 'DataSource' during creation. This value should +-- be identical to the value of the 'DataSourceID' in the request. +udsrsDataSourceId :: Lens' UpdateDataSourceResponse (Maybe Text) +udsrsDataSourceId = lens _udsrsDataSourceId (\ s a -> s{_udsrsDataSourceId = a}); -instance FromJSON UpdateDataSourceResponse where - parseJSON = withObject "UpdateDataSourceResponse" $ \o -> UpdateDataSourceResponse - <$> o .:? "DataSourceId" +-- | The response status code. +udsrsStatus :: Lens' UpdateDataSourceResponse Int +udsrsStatus = lens _udsrsStatus (\ s a -> s{_udsrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/UpdateEvaluation.hs b/gen/Network/AWS/MachineLearning/UpdateEvaluation.hs --- a/gen/Network/AWS/MachineLearning/UpdateEvaluation.hs +++ b/gen/Network/AWS/MachineLearning/UpdateEvaluation.hs @@ -1,128 +1,146 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.UpdateEvaluation --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Updates the 'EvaluationName' of an 'Evaluation'. +-- Updates the 'EvaluationName' of an 'Evaluation'. -- --- You can use the 'GetEvaluation' operation to view the contents of the updated --- data element. +-- You can use the GetEvaluation operation to view the contents of the +-- updated data element. -- --- +-- /See:/ for UpdateEvaluation. module Network.AWS.MachineLearning.UpdateEvaluation ( - -- * Request - UpdateEvaluation - -- ** Request constructor - , updateEvaluation - -- ** Request lenses + -- * Creating a Request + updateEvaluation + , UpdateEvaluation + -- * Request Lenses , ueEvaluationId , ueEvaluationName - -- * Response - , UpdateEvaluationResponse - -- ** Response constructor + -- * Destructuring the Response , updateEvaluationResponse - -- ** Response lenses - , uerEvaluationId + , UpdateEvaluationResponse + -- * Response Lenses + , uersEvaluationId + , uersStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data UpdateEvaluation = UpdateEvaluation - { _ueEvaluationId :: Text - , _ueEvaluationName :: Text - } deriving (Eq, Ord, Read, Show) +-- | /See:/ 'updateEvaluation' smart constructor. +data UpdateEvaluation = UpdateEvaluation' + { _ueEvaluationId :: !Text + , _ueEvaluationName :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'UpdateEvaluation' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'UpdateEvaluation' with the minimum fields required to make a request. -- --- * 'ueEvaluationId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'ueEvaluationName' @::@ 'Text' +-- * 'ueEvaluationId' -- -updateEvaluation :: Text -- ^ 'ueEvaluationId' - -> Text -- ^ 'ueEvaluationName' - -> UpdateEvaluation -updateEvaluation p1 p2 = UpdateEvaluation - { _ueEvaluationId = p1 - , _ueEvaluationName = p2 +-- * 'ueEvaluationName' +updateEvaluation + :: Text -- ^ 'ueEvaluationId' + -> Text -- ^ 'ueEvaluationName' + -> UpdateEvaluation +updateEvaluation pEvaluationId_ pEvaluationName_ = + UpdateEvaluation' + { _ueEvaluationId = pEvaluationId_ + , _ueEvaluationName = pEvaluationName_ } -- | The ID assigned to the 'Evaluation' during creation. ueEvaluationId :: Lens' UpdateEvaluation Text -ueEvaluationId = lens _ueEvaluationId (\s a -> s { _ueEvaluationId = a }) +ueEvaluationId = lens _ueEvaluationId (\ s a -> s{_ueEvaluationId = a}); --- | A new user-supplied name or description of the 'Evaluation' that will replace --- the current content. +-- | A new user-supplied name or description of the 'Evaluation' that will +-- replace the current content. ueEvaluationName :: Lens' UpdateEvaluation Text -ueEvaluationName = lens _ueEvaluationName (\s a -> s { _ueEvaluationName = a }) +ueEvaluationName = lens _ueEvaluationName (\ s a -> s{_ueEvaluationName = a}); -newtype UpdateEvaluationResponse = UpdateEvaluationResponse - { _uerEvaluationId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +instance AWSRequest UpdateEvaluation where + type Sv UpdateEvaluation = MachineLearning + type Rs UpdateEvaluation = UpdateEvaluationResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + UpdateEvaluationResponse' <$> + (x .?> "EvaluationId") <*> (pure (fromEnum s))) --- | 'UpdateEvaluationResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'uerEvaluationId' @::@ 'Maybe' 'Text' --- -updateEvaluationResponse :: UpdateEvaluationResponse -updateEvaluationResponse = UpdateEvaluationResponse - { _uerEvaluationId = Nothing - } +instance ToHeaders UpdateEvaluation where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.UpdateEvaluation" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) --- | The ID assigned to the 'Evaluation' during creation. This value should be --- identical to the value of the 'Evaluation' in the request. -uerEvaluationId :: Lens' UpdateEvaluationResponse (Maybe Text) -uerEvaluationId = lens _uerEvaluationId (\s a -> s { _uerEvaluationId = a }) +instance ToJSON UpdateEvaluation where + toJSON UpdateEvaluation'{..} + = object + ["EvaluationId" .= _ueEvaluationId, + "EvaluationName" .= _ueEvaluationName] instance ToPath UpdateEvaluation where - toPath = const "/" + toPath = const "/" instance ToQuery UpdateEvaluation where - toQuery = const mempty - -instance ToHeaders UpdateEvaluation + toQuery = const mempty -instance ToJSON UpdateEvaluation where - toJSON UpdateEvaluation{..} = object - [ "EvaluationId" .= _ueEvaluationId - , "EvaluationName" .= _ueEvaluationName - ] +-- | Represents the output of an UpdateEvaluation operation. +-- +-- You can see the updated content by using the GetEvaluation operation. +-- +-- /See:/ 'updateEvaluationResponse' smart constructor. +data UpdateEvaluationResponse = UpdateEvaluationResponse' + { _uersEvaluationId :: !(Maybe Text) + , _uersStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest UpdateEvaluation where - type Sv UpdateEvaluation = MachineLearning - type Rs UpdateEvaluation = UpdateEvaluationResponse +-- | Creates a value of 'UpdateEvaluationResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'uersEvaluationId' +-- +-- * 'uersStatus' +updateEvaluationResponse + :: Int -- ^ 'uersStatus' + -> UpdateEvaluationResponse +updateEvaluationResponse pStatus_ = + UpdateEvaluationResponse' + { _uersEvaluationId = Nothing + , _uersStatus = pStatus_ + } - request = post "UpdateEvaluation" - response = jsonResponse +-- | The ID assigned to the 'Evaluation' during creation. This value should +-- be identical to the value of the 'Evaluation' in the request. +uersEvaluationId :: Lens' UpdateEvaluationResponse (Maybe Text) +uersEvaluationId = lens _uersEvaluationId (\ s a -> s{_uersEvaluationId = a}); -instance FromJSON UpdateEvaluationResponse where - parseJSON = withObject "UpdateEvaluationResponse" $ \o -> UpdateEvaluationResponse - <$> o .:? "EvaluationId" +-- | The response status code. +uersStatus :: Lens' UpdateEvaluationResponse Int +uersStatus = lens _uersStatus (\ s a -> s{_uersStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/UpdateMLModel.hs b/gen/Network/AWS/MachineLearning/UpdateMLModel.hs --- a/gen/Network/AWS/MachineLearning/UpdateMLModel.hs +++ b/gen/Network/AWS/MachineLearning/UpdateMLModel.hs @@ -1,141 +1,160 @@ -{-# LANGUAGE DataKinds #-} -{-# LANGUAGE DeriveGeneric #-} -{-# LANGUAGE FlexibleInstances #-} -{-# LANGUAGE GeneralizedNewtypeDeriving #-} -{-# LANGUAGE LambdaCase #-} -{-# LANGUAGE NoImplicitPrelude #-} -{-# LANGUAGE OverloadedStrings #-} -{-# LANGUAGE RecordWildCards #-} -{-# LANGUAGE TypeFamilies #-} +{-# LANGUAGE DeriveDataTypeable #-} +{-# LANGUAGE DeriveGeneric #-} +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE RecordWildCards #-} +{-# LANGUAGE TypeFamilies #-} {-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-unused-binds #-} +{-# OPTIONS_GHC -fno-warn-unused-matches #-} +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | -- Module : Network.AWS.MachineLearning.UpdateMLModel --- Copyright : (c) 2013-2014 Brendan Hay --- License : This Source Code Form is subject to the terms of --- the Mozilla Public License, v. 2.0. --- A copy of the MPL can be found in the LICENSE file or --- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay --- Stability : experimental +-- Stability : auto-generated -- Portability : non-portable (GHC extensions) -- --- Derived from AWS service descriptions, licensed under Apache 2.0. - --- | Updates the 'MLModelName' and the 'ScoreThreshold' of an 'MLModel'. +-- Updates the 'MLModelName' and the 'ScoreThreshold' of an 'MLModel'. -- --- You can use the 'GetMLModel' operation to view the contents of the updated +-- You can use the GetMLModel operation to view the contents of the updated -- data element. -- --- +-- /See:/ for UpdateMLModel. module Network.AWS.MachineLearning.UpdateMLModel ( - -- * Request - UpdateMLModel - -- ** Request constructor - , updateMLModel - -- ** Request lenses - , umlmMLModelId + -- * Creating a Request + updateMLModel + , UpdateMLModel + -- * Request Lenses , umlmMLModelName , umlmScoreThreshold + , umlmMLModelId - -- * Response - , UpdateMLModelResponse - -- ** Response constructor + -- * Destructuring the Response , updateMLModelResponse - -- ** Response lenses - , umlmrMLModelId + , UpdateMLModelResponse + -- * Response Lenses + , umlmrsMLModelId + , umlmrsStatus ) where -import Network.AWS.Data (Object) -import Network.AWS.Prelude -import Network.AWS.Request.JSON -import Network.AWS.MachineLearning.Types -import qualified GHC.Exts +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response -data UpdateMLModel = UpdateMLModel - { _umlmMLModelId :: Text - , _umlmMLModelName :: Maybe Text - , _umlmScoreThreshold :: Maybe Double - } deriving (Eq, Ord, Read, Show) +-- | /See:/ 'updateMLModel' smart constructor. +data UpdateMLModel = UpdateMLModel' + { _umlmMLModelName :: !(Maybe Text) + , _umlmScoreThreshold :: !(Maybe Double) + , _umlmMLModelId :: !Text + } deriving (Eq,Read,Show,Data,Typeable,Generic) --- | 'UpdateMLModel' constructor. --- --- The fields accessible through corresponding lenses are: +-- | Creates a value of 'UpdateMLModel' with the minimum fields required to make a request. -- --- * 'umlmMLModelId' @::@ 'Text' +-- Use one of the following lenses to modify other fields as desired: -- --- * 'umlmMLModelName' @::@ 'Maybe' 'Text' +-- * 'umlmMLModelName' -- --- * 'umlmScoreThreshold' @::@ 'Maybe' 'Double' +-- * 'umlmScoreThreshold' -- -updateMLModel :: Text -- ^ 'umlmMLModelId' - -> UpdateMLModel -updateMLModel p1 = UpdateMLModel - { _umlmMLModelId = p1 - , _umlmMLModelName = Nothing +-- * 'umlmMLModelId' +updateMLModel + :: Text -- ^ 'umlmMLModelId' + -> UpdateMLModel +updateMLModel pMLModelId_ = + UpdateMLModel' + { _umlmMLModelName = Nothing , _umlmScoreThreshold = Nothing + , _umlmMLModelId = pMLModelId_ } --- | The ID assigned to the 'MLModel' during creation. -umlmMLModelId :: Lens' UpdateMLModel Text -umlmMLModelId = lens _umlmMLModelId (\s a -> s { _umlmMLModelId = a }) - -- | A user-supplied name or description of the 'MLModel'. umlmMLModelName :: Lens' UpdateMLModel (Maybe Text) -umlmMLModelName = lens _umlmMLModelName (\s a -> s { _umlmMLModelName = a }) +umlmMLModelName = lens _umlmMLModelName (\ s a -> s{_umlmMLModelName = a}); --- | The 'ScoreThreshold' used in binary classification 'MLModel' that marks the --- boundary between a positive prediction and a negative prediction. +-- | The 'ScoreThreshold' used in binary classification 'MLModel' that marks +-- the boundary between a positive prediction and a negative prediction. -- --- Output values greater than or equal to the 'ScoreThreshold' receive a positive --- result from the 'MLModel', such as 'true'. Output values less than the 'ScoreThreshold' receive a negative response from the 'MLModel', such as 'false'. +-- Output values greater than or equal to the 'ScoreThreshold' receive a +-- positive result from the 'MLModel', such as 'true'. Output values less +-- than the 'ScoreThreshold' receive a negative response from the +-- 'MLModel', such as 'false'. umlmScoreThreshold :: Lens' UpdateMLModel (Maybe Double) -umlmScoreThreshold = - lens _umlmScoreThreshold (\s a -> s { _umlmScoreThreshold = a }) +umlmScoreThreshold = lens _umlmScoreThreshold (\ s a -> s{_umlmScoreThreshold = a}); -newtype UpdateMLModelResponse = UpdateMLModelResponse - { _umlmrMLModelId :: Maybe Text - } deriving (Eq, Ord, Read, Show, Monoid) +-- | The ID assigned to the 'MLModel' during creation. +umlmMLModelId :: Lens' UpdateMLModel Text +umlmMLModelId = lens _umlmMLModelId (\ s a -> s{_umlmMLModelId = a}); --- | 'UpdateMLModelResponse' constructor. --- --- The fields accessible through corresponding lenses are: --- --- * 'umlmrMLModelId' @::@ 'Maybe' 'Text' --- -updateMLModelResponse :: UpdateMLModelResponse -updateMLModelResponse = UpdateMLModelResponse - { _umlmrMLModelId = Nothing - } +instance AWSRequest UpdateMLModel where + type Sv UpdateMLModel = MachineLearning + type Rs UpdateMLModel = UpdateMLModelResponse + request = postJSON + response + = receiveJSON + (\ s h x -> + UpdateMLModelResponse' <$> + (x .?> "MLModelId") <*> (pure (fromEnum s))) --- | The ID assigned to the 'MLModel' during creation. This value should be --- identical to the value of the 'MLModelID' in the request. -umlmrMLModelId :: Lens' UpdateMLModelResponse (Maybe Text) -umlmrMLModelId = lens _umlmrMLModelId (\s a -> s { _umlmrMLModelId = a }) +instance ToHeaders UpdateMLModel where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.UpdateMLModel" :: ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) +instance ToJSON UpdateMLModel where + toJSON UpdateMLModel'{..} + = object + ["MLModelName" .= _umlmMLModelName, + "ScoreThreshold" .= _umlmScoreThreshold, + "MLModelId" .= _umlmMLModelId] + instance ToPath UpdateMLModel where - toPath = const "/" + toPath = const "/" instance ToQuery UpdateMLModel where - toQuery = const mempty - -instance ToHeaders UpdateMLModel + toQuery = const mempty -instance ToJSON UpdateMLModel where - toJSON UpdateMLModel{..} = object - [ "MLModelId" .= _umlmMLModelId - , "MLModelName" .= _umlmMLModelName - , "ScoreThreshold" .= _umlmScoreThreshold - ] +-- | Represents the output of an UpdateMLModel operation. +-- +-- You can see the updated content by using the GetMLModel operation. +-- +-- /See:/ 'updateMLModelResponse' smart constructor. +data UpdateMLModelResponse = UpdateMLModelResponse' + { _umlmrsMLModelId :: !(Maybe Text) + , _umlmrsStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) -instance AWSRequest UpdateMLModel where - type Sv UpdateMLModel = MachineLearning - type Rs UpdateMLModel = UpdateMLModelResponse +-- | Creates a value of 'UpdateMLModelResponse' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'umlmrsMLModelId' +-- +-- * 'umlmrsStatus' +updateMLModelResponse + :: Int -- ^ 'umlmrsStatus' + -> UpdateMLModelResponse +updateMLModelResponse pStatus_ = + UpdateMLModelResponse' + { _umlmrsMLModelId = Nothing + , _umlmrsStatus = pStatus_ + } - request = post "UpdateMLModel" - response = jsonResponse +-- | The ID assigned to the 'MLModel' during creation. This value should be +-- identical to the value of the 'MLModelID' in the request. +umlmrsMLModelId :: Lens' UpdateMLModelResponse (Maybe Text) +umlmrsMLModelId = lens _umlmrsMLModelId (\ s a -> s{_umlmrsMLModelId = a}); -instance FromJSON UpdateMLModelResponse where - parseJSON = withObject "UpdateMLModelResponse" $ \o -> UpdateMLModelResponse - <$> o .:? "MLModelId" +-- | The response status code. +umlmrsStatus :: Lens' UpdateMLModelResponse Int +umlmrsStatus = lens _umlmrsStatus (\ s a -> s{_umlmrsStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/Waiters.hs b/gen/Network/AWS/MachineLearning/Waiters.hs new file mode 100644 --- /dev/null +++ b/gen/Network/AWS/MachineLearning/Waiters.hs @@ -0,0 +1,104 @@ +{-# LANGUAGE OverloadedStrings #-} +{-# LANGUAGE TypeFamilies #-} + +{-# OPTIONS_GHC -fno-warn-unused-imports #-} + +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | +-- Module : Network.AWS.MachineLearning.Waiters +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. +-- Maintainer : Brendan Hay +-- Stability : auto-generated +-- Portability : non-portable (GHC extensions) +-- +module Network.AWS.MachineLearning.Waiters where + +import Network.AWS.MachineLearning.DescribeBatchPredictions +import Network.AWS.MachineLearning.DescribeDataSources +import Network.AWS.MachineLearning.DescribeEvaluations +import Network.AWS.MachineLearning.DescribeMLModels +import Network.AWS.MachineLearning.Types +import Network.AWS.Prelude +import Network.AWS.Waiter + +-- | Polls 'Network.AWS.MachineLearning.DescribeMLModels' every 30 seconds until a +-- successful state is reached. An error is returned after 60 failed checks. +mLModelAvailable :: Wait DescribeMLModels +mLModelAvailable = + Wait + { _waitName = "MLModelAvailable" + , _waitAttempts = 60 + , _waitDelay = 30 + , _waitAcceptors = [ matchAll + "COMPLETED" + AcceptSuccess + (folding (concatOf dmlmsrsResults) . + mlmStatus . _Just . to toTextCI) + , matchAny + "FAILED" + AcceptFailure + (folding (concatOf dmlmsrsResults) . + mlmStatus . _Just . to toTextCI)] + } + +-- | Polls 'Network.AWS.MachineLearning.DescribeBatchPredictions' every 30 seconds until a +-- successful state is reached. An error is returned after 60 failed checks. +batchPredictionAvailable :: Wait DescribeBatchPredictions +batchPredictionAvailable = + Wait + { _waitName = "BatchPredictionAvailable" + , _waitAttempts = 60 + , _waitDelay = 30 + , _waitAcceptors = [ matchAll + "COMPLETED" + AcceptSuccess + (folding (concatOf drsResults) . + bpStatus . _Just . to toTextCI) + , matchAny + "FAILED" + AcceptFailure + (folding (concatOf drsResults) . + bpStatus . _Just . to toTextCI)] + } + +-- | Polls 'Network.AWS.MachineLearning.DescribeDataSources' every 30 seconds until a +-- successful state is reached. An error is returned after 60 failed checks. +dataSourceAvailable :: Wait DescribeDataSources +dataSourceAvailable = + Wait + { _waitName = "DataSourceAvailable" + , _waitAttempts = 60 + , _waitDelay = 30 + , _waitAcceptors = [ matchAll + "COMPLETED" + AcceptSuccess + (folding (concatOf ddssrsResults) . + dsStatus . _Just . to toTextCI) + , matchAny + "FAILED" + AcceptFailure + (folding (concatOf ddssrsResults) . + dsStatus . _Just . to toTextCI)] + } + +-- | Polls 'Network.AWS.MachineLearning.DescribeEvaluations' every 30 seconds until a +-- successful state is reached. An error is returned after 60 failed checks. +evaluationAvailable :: Wait DescribeEvaluations +evaluationAvailable = + Wait + { _waitName = "EvaluationAvailable" + , _waitAttempts = 60 + , _waitDelay = 30 + , _waitAcceptors = [ matchAll + "COMPLETED" + AcceptSuccess + (folding (concatOf desrsResults) . + eStatus . _Just . to toTextCI) + , matchAny + "FAILED" + AcceptFailure + (folding (concatOf desrsResults) . + eStatus . _Just . to toTextCI)] + } diff --git a/test/Main.hs b/test/Main.hs new file mode 100644 --- /dev/null +++ b/test/Main.hs @@ -0,0 +1,21 @@ +{-# OPTIONS_GHC -fno-warn-unused-imports #-} + +-- | +-- Module : Main +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. +-- Maintainer : Brendan Hay +-- Stability : auto-generated +-- Portability : non-portable (GHC extensions) +-- +module Main (main) where + +import Test.Tasty +import Test.AWS.MachineLearning +import Test.AWS.MachineLearning.Internal + +main :: IO () +main = defaultMain $ testGroup "MachineLearning" + [ testGroup "tests" tests + , testGroup "fixtures" fixtures + ] diff --git a/test/Test/AWS/Gen/MachineLearning.hs b/test/Test/AWS/Gen/MachineLearning.hs new file mode 100644 --- /dev/null +++ b/test/Test/AWS/Gen/MachineLearning.hs @@ -0,0 +1,464 @@ +{-# OPTIONS_GHC -fno-warn-unused-imports #-} +{-# OPTIONS_GHC -fno-warn-orphans #-} + +-- Derived from AWS service descriptions, licensed under Apache 2.0. + +-- | +-- Module : Test.AWS.Gen.MachineLearning +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. +-- Maintainer : Brendan Hay +-- Stability : auto-generated +-- Portability : non-portable (GHC extensions) +-- +module Test.AWS.Gen.MachineLearning where + +import Data.Proxy +import Test.AWS.Fixture +import Test.AWS.Prelude +import Test.Tasty +import Network.AWS.MachineLearning +import Test.AWS.MachineLearning.Internal + +-- Auto-generated: the actual test selection needs to be manually placed into +-- the top-level so that real test data can be incrementally added. +-- +-- This commented snippet is what the entire set should look like: + +-- fixtures :: TestTree +-- fixtures = +-- [ testGroup "request" +-- [ testDeleteDataSource $ +-- deleteDataSource +-- +-- , testUpdateDataSource $ +-- updateDataSource +-- +-- , testCreateDataSourceFromRedshift $ +-- createDataSourceFromRedshift +-- +-- , testCreateDataSourceFromS $ +-- createDataSourceFromS +-- +-- , testCreateMLModel $ +-- createMLModel +-- +-- , testDeleteBatchPrediction $ +-- deleteBatchPrediction +-- +-- , testUpdateBatchPrediction $ +-- updateBatchPrediction +-- +-- , testGetMLModel $ +-- getMLModel +-- +-- , testGetDataSource $ +-- getDataSource +-- +-- , testDeleteMLModel $ +-- deleteMLModel +-- +-- , testUpdateMLModel $ +-- updateMLModel +-- +-- , testDescribeBatchPredictions $ +-- describeBatchPredictions +-- +-- , testUpdateEvaluation $ +-- updateEvaluation +-- +-- , testDeleteEvaluation $ +-- deleteEvaluation +-- +-- , testGetBatchPrediction $ +-- getBatchPrediction +-- +-- , testCreateEvaluation $ +-- createEvaluation +-- +-- , testCreateDataSourceFromRDS $ +-- createDataSourceFromRDS +-- +-- , testCreateBatchPrediction $ +-- createBatchPrediction +-- +-- , testPredict $ +-- predict +-- +-- , testDeleteRealtimeEndpoint $ +-- deleteRealtimeEndpoint +-- +-- , testDescribeEvaluations $ +-- describeEvaluations +-- +-- , testGetEvaluation $ +-- getEvaluation +-- +-- , testCreateRealtimeEndpoint $ +-- createRealtimeEndpoint +-- +-- , testDescribeMLModels $ +-- describeMLModels +-- +-- , testDescribeDataSources $ +-- describeDataSources +-- +-- ] + +-- , testGroup "response" +-- [ testDeleteDataSourceResponse $ +-- deleteDataSourceResponse +-- +-- , testUpdateDataSourceResponse $ +-- updateDataSourceResponse +-- +-- , testCreateDataSourceFromRedshiftResponse $ +-- createDataSourceFromRedshiftResponse +-- +-- , testCreateDataSourceFromSResponse $ +-- createDataSourceFromSResponse +-- +-- , testCreateMLModelResponse $ +-- createMLModelResponse +-- +-- , testDeleteBatchPredictionResponse $ +-- deleteBatchPredictionResponse +-- +-- , testUpdateBatchPredictionResponse $ +-- updateBatchPredictionResponse +-- +-- , testGetMLModelResponse $ +-- getMLModelResponse +-- +-- , testGetDataSourceResponse $ +-- getDataSourceResponse +-- +-- , testDeleteMLModelResponse $ +-- deleteMLModelResponse +-- +-- , testUpdateMLModelResponse $ +-- updateMLModelResponse +-- +-- , testDescribeBatchPredictionsResponse $ +-- describeBatchPredictionsResponse +-- +-- , testUpdateEvaluationResponse $ +-- updateEvaluationResponse +-- +-- , testDeleteEvaluationResponse $ +-- deleteEvaluationResponse +-- +-- , testGetBatchPredictionResponse $ +-- getBatchPredictionResponse +-- +-- , testCreateEvaluationResponse $ +-- createEvaluationResponse +-- +-- , testCreateDataSourceFromRDSResponse $ +-- createDataSourceFromRDSResponse +-- +-- , testCreateBatchPredictionResponse $ +-- createBatchPredictionResponse +-- +-- , testPredictResponse $ +-- predictResponse +-- +-- , testDeleteRealtimeEndpointResponse $ +-- deleteRealtimeEndpointResponse +-- +-- , testDescribeEvaluationsResponse $ +-- describeEvaluationsResponse +-- +-- , testGetEvaluationResponse $ +-- getEvaluationResponse +-- +-- , testCreateRealtimeEndpointResponse $ +-- createRealtimeEndpointResponse +-- +-- , testDescribeMLModelsResponse $ +-- describeMLModelsResponse +-- +-- , testDescribeDataSourcesResponse $ +-- describeDataSourcesResponse +-- +-- ] +-- ] + +-- Requests + +testDeleteDataSource :: DeleteDataSource -> TestTree +testDeleteDataSource = req + "DeleteDataSource" + "fixture/DeleteDataSource" + +testUpdateDataSource :: UpdateDataSource -> TestTree +testUpdateDataSource = req + "UpdateDataSource" + "fixture/UpdateDataSource" + +testCreateDataSourceFromRedshift :: CreateDataSourceFromRedshift -> TestTree +testCreateDataSourceFromRedshift = req + "CreateDataSourceFromRedshift" + "fixture/CreateDataSourceFromRedshift" + +testCreateDataSourceFromS :: CreateDataSourceFromS -> TestTree +testCreateDataSourceFromS = req + "CreateDataSourceFromS" + "fixture/CreateDataSourceFromS" + +testCreateMLModel :: CreateMLModel -> TestTree +testCreateMLModel = req + "CreateMLModel" + "fixture/CreateMLModel" + +testDeleteBatchPrediction :: DeleteBatchPrediction -> TestTree +testDeleteBatchPrediction = req + "DeleteBatchPrediction" + "fixture/DeleteBatchPrediction" + +testUpdateBatchPrediction :: UpdateBatchPrediction -> TestTree +testUpdateBatchPrediction = req + "UpdateBatchPrediction" + "fixture/UpdateBatchPrediction" + +testGetMLModel :: GetMLModel -> TestTree +testGetMLModel = req + "GetMLModel" + "fixture/GetMLModel" + +testGetDataSource :: GetDataSource -> TestTree +testGetDataSource = req + "GetDataSource" + "fixture/GetDataSource" + +testDeleteMLModel :: DeleteMLModel -> TestTree +testDeleteMLModel = req + "DeleteMLModel" + "fixture/DeleteMLModel" + +testUpdateMLModel :: UpdateMLModel -> TestTree +testUpdateMLModel = req + "UpdateMLModel" + "fixture/UpdateMLModel" + +testDescribeBatchPredictions :: DescribeBatchPredictions -> TestTree +testDescribeBatchPredictions = req + "DescribeBatchPredictions" + "fixture/DescribeBatchPredictions" + +testUpdateEvaluation :: UpdateEvaluation -> TestTree +testUpdateEvaluation = req + "UpdateEvaluation" + "fixture/UpdateEvaluation" + +testDeleteEvaluation :: DeleteEvaluation -> TestTree +testDeleteEvaluation = req + "DeleteEvaluation" + "fixture/DeleteEvaluation" + +testGetBatchPrediction :: GetBatchPrediction -> TestTree +testGetBatchPrediction = req + "GetBatchPrediction" + "fixture/GetBatchPrediction" + +testCreateEvaluation :: CreateEvaluation -> TestTree +testCreateEvaluation = req + "CreateEvaluation" + "fixture/CreateEvaluation" + +testCreateDataSourceFromRDS :: CreateDataSourceFromRDS -> TestTree +testCreateDataSourceFromRDS = req + "CreateDataSourceFromRDS" + "fixture/CreateDataSourceFromRDS" + +testCreateBatchPrediction :: CreateBatchPrediction -> TestTree +testCreateBatchPrediction = req + "CreateBatchPrediction" + "fixture/CreateBatchPrediction" + +testPredict :: Predict -> TestTree +testPredict = req + "Predict" + "fixture/Predict" + +testDeleteRealtimeEndpoint :: DeleteRealtimeEndpoint -> TestTree +testDeleteRealtimeEndpoint = req + "DeleteRealtimeEndpoint" + "fixture/DeleteRealtimeEndpoint" + +testDescribeEvaluations :: DescribeEvaluations -> TestTree +testDescribeEvaluations = req + "DescribeEvaluations" + "fixture/DescribeEvaluations" + +testGetEvaluation :: GetEvaluation -> TestTree +testGetEvaluation = req + "GetEvaluation" + "fixture/GetEvaluation" + +testCreateRealtimeEndpoint :: CreateRealtimeEndpoint -> TestTree +testCreateRealtimeEndpoint = req + "CreateRealtimeEndpoint" + "fixture/CreateRealtimeEndpoint" + +testDescribeMLModels :: DescribeMLModels -> TestTree +testDescribeMLModels = req + "DescribeMLModels" + "fixture/DescribeMLModels" + +testDescribeDataSources :: DescribeDataSources -> TestTree +testDescribeDataSources = req + "DescribeDataSources" + "fixture/DescribeDataSources" + +-- Responses + +testDeleteDataSourceResponse :: DeleteDataSourceResponse -> TestTree +testDeleteDataSourceResponse = res + "DeleteDataSourceResponse" + "fixture/DeleteDataSourceResponse" + (Proxy :: Proxy DeleteDataSource) + +testUpdateDataSourceResponse :: UpdateDataSourceResponse -> TestTree +testUpdateDataSourceResponse = res + "UpdateDataSourceResponse" + "fixture/UpdateDataSourceResponse" + (Proxy :: Proxy UpdateDataSource) + +testCreateDataSourceFromRedshiftResponse :: CreateDataSourceFromRedshiftResponse -> TestTree +testCreateDataSourceFromRedshiftResponse = res + "CreateDataSourceFromRedshiftResponse" + "fixture/CreateDataSourceFromRedshiftResponse" + (Proxy :: Proxy CreateDataSourceFromRedshift) + +testCreateDataSourceFromSResponse :: CreateDataSourceFromSResponse -> TestTree +testCreateDataSourceFromSResponse = res + "CreateDataSourceFromSResponse" + "fixture/CreateDataSourceFromSResponse" + (Proxy :: Proxy CreateDataSourceFromS) + +testCreateMLModelResponse :: CreateMLModelResponse -> TestTree +testCreateMLModelResponse = res + "CreateMLModelResponse" + "fixture/CreateMLModelResponse" + (Proxy :: Proxy CreateMLModel) + +testDeleteBatchPredictionResponse :: DeleteBatchPredictionResponse -> TestTree +testDeleteBatchPredictionResponse = res + "DeleteBatchPredictionResponse" + "fixture/DeleteBatchPredictionResponse" + (Proxy :: Proxy DeleteBatchPrediction) + +testUpdateBatchPredictionResponse :: UpdateBatchPredictionResponse -> TestTree +testUpdateBatchPredictionResponse = res + "UpdateBatchPredictionResponse" + "fixture/UpdateBatchPredictionResponse" + (Proxy :: Proxy UpdateBatchPrediction) + +testGetMLModelResponse :: GetMLModelResponse -> TestTree +testGetMLModelResponse = res + "GetMLModelResponse" + "fixture/GetMLModelResponse" + (Proxy :: Proxy GetMLModel) + +testGetDataSourceResponse :: GetDataSourceResponse -> TestTree +testGetDataSourceResponse = res + "GetDataSourceResponse" + "fixture/GetDataSourceResponse" + (Proxy :: Proxy GetDataSource) + +testDeleteMLModelResponse :: DeleteMLModelResponse -> TestTree +testDeleteMLModelResponse = res + "DeleteMLModelResponse" + "fixture/DeleteMLModelResponse" + (Proxy :: Proxy DeleteMLModel) + +testUpdateMLModelResponse :: UpdateMLModelResponse -> TestTree +testUpdateMLModelResponse = res + "UpdateMLModelResponse" + "fixture/UpdateMLModelResponse" + (Proxy :: Proxy UpdateMLModel) + +testDescribeBatchPredictionsResponse :: DescribeBatchPredictionsResponse -> TestTree +testDescribeBatchPredictionsResponse = res + "DescribeBatchPredictionsResponse" + "fixture/DescribeBatchPredictionsResponse" + (Proxy :: Proxy DescribeBatchPredictions) + +testUpdateEvaluationResponse :: UpdateEvaluationResponse -> TestTree +testUpdateEvaluationResponse = res + "UpdateEvaluationResponse" + "fixture/UpdateEvaluationResponse" + (Proxy :: Proxy UpdateEvaluation) + +testDeleteEvaluationResponse :: DeleteEvaluationResponse -> TestTree +testDeleteEvaluationResponse = res + "DeleteEvaluationResponse" + "fixture/DeleteEvaluationResponse" + (Proxy :: Proxy DeleteEvaluation) + +testGetBatchPredictionResponse :: GetBatchPredictionResponse -> TestTree +testGetBatchPredictionResponse = res + "GetBatchPredictionResponse" + "fixture/GetBatchPredictionResponse" + (Proxy :: Proxy GetBatchPrediction) + +testCreateEvaluationResponse :: CreateEvaluationResponse -> TestTree +testCreateEvaluationResponse = res + "CreateEvaluationResponse" + "fixture/CreateEvaluationResponse" + (Proxy :: Proxy CreateEvaluation) + +testCreateDataSourceFromRDSResponse :: CreateDataSourceFromRDSResponse -> TestTree +testCreateDataSourceFromRDSResponse = res + "CreateDataSourceFromRDSResponse" + "fixture/CreateDataSourceFromRDSResponse" + (Proxy :: Proxy CreateDataSourceFromRDS) + +testCreateBatchPredictionResponse :: CreateBatchPredictionResponse -> TestTree +testCreateBatchPredictionResponse = res + "CreateBatchPredictionResponse" + "fixture/CreateBatchPredictionResponse" + (Proxy :: Proxy CreateBatchPrediction) + +testPredictResponse :: PredictResponse -> TestTree +testPredictResponse = res + "PredictResponse" + "fixture/PredictResponse" + (Proxy :: Proxy Predict) + +testDeleteRealtimeEndpointResponse :: DeleteRealtimeEndpointResponse -> TestTree +testDeleteRealtimeEndpointResponse = res + "DeleteRealtimeEndpointResponse" + "fixture/DeleteRealtimeEndpointResponse" + (Proxy :: Proxy DeleteRealtimeEndpoint) + +testDescribeEvaluationsResponse :: DescribeEvaluationsResponse -> TestTree +testDescribeEvaluationsResponse = res + "DescribeEvaluationsResponse" + "fixture/DescribeEvaluationsResponse" + (Proxy :: Proxy DescribeEvaluations) + +testGetEvaluationResponse :: GetEvaluationResponse -> TestTree +testGetEvaluationResponse = res + "GetEvaluationResponse" + "fixture/GetEvaluationResponse" + (Proxy :: Proxy GetEvaluation) + +testCreateRealtimeEndpointResponse :: CreateRealtimeEndpointResponse -> TestTree +testCreateRealtimeEndpointResponse = res + "CreateRealtimeEndpointResponse" + "fixture/CreateRealtimeEndpointResponse" + (Proxy :: Proxy CreateRealtimeEndpoint) + +testDescribeMLModelsResponse :: DescribeMLModelsResponse -> TestTree +testDescribeMLModelsResponse = res + "DescribeMLModelsResponse" + "fixture/DescribeMLModelsResponse" + (Proxy :: Proxy DescribeMLModels) + +testDescribeDataSourcesResponse :: DescribeDataSourcesResponse -> TestTree +testDescribeDataSourcesResponse = res + "DescribeDataSourcesResponse" + "fixture/DescribeDataSourcesResponse" + (Proxy :: Proxy DescribeDataSources) diff --git a/test/Test/AWS/MachineLearning.hs b/test/Test/AWS/MachineLearning.hs new file mode 100644 --- /dev/null +++ b/test/Test/AWS/MachineLearning.hs @@ -0,0 +1,26 @@ +{-# LANGUAGE OverloadedStrings #-} + +-- Module : Test.AWS.MachineLearning +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : This Source Code Form is subject to the terms of +-- the Mozilla Public License, v. 2.0. +-- A copy of the MPL can be found in the LICENSE file or +-- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Maintainer : Brendan Hay +-- Stability : experimental +-- Portability : non-portable (GHC extensions) + +module Test.AWS.MachineLearning + ( tests + , fixtures + ) where + +import Network.AWS.MachineLearning +import Test.AWS.Gen.MachineLearning +import Test.Tasty + +tests :: [TestTree] +tests = [] + +fixtures :: [TestTree] +fixtures = [] diff --git a/test/Test/AWS/MachineLearning/Internal.hs b/test/Test/AWS/MachineLearning/Internal.hs new file mode 100644 --- /dev/null +++ b/test/Test/AWS/MachineLearning/Internal.hs @@ -0,0 +1,16 @@ +{-# LANGUAGE OverloadedStrings #-} +{-# OPTIONS_GHC -fno-warn-unused-imports #-} + +-- Module : Test.AWS.MachineLearning.Internal +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : This Source Code Form is subject to the terms of +-- the Mozilla Public License, v. 2.0. +-- A copy of the MPL can be found in the LICENSE file or +-- you can obtain it at http://mozilla.org/MPL/2.0/. +-- Maintainer : Brendan Hay +-- Stability : experimental +-- Portability : non-portable (GHC extensions) + +module Test.AWS.MachineLearning.Internal where + +import Test.AWS.Prelude