diff --git a/README.md b/README.md --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ ## Version -`1.3.0` +`1.3.1` ## Description diff --git a/amazonka-ml.cabal b/amazonka-ml.cabal --- a/amazonka-ml.cabal +++ b/amazonka-ml.cabal @@ -1,5 +1,5 @@ name: amazonka-ml -version: 1.3.0 +version: 1.3.1 synopsis: Amazon Machine Learning SDK. homepage: https://github.com/brendanhay/amazonka bug-reports: https://github.com/brendanhay/amazonka/issues @@ -44,7 +44,7 @@ , Network.AWS.MachineLearning.CreateBatchPrediction , Network.AWS.MachineLearning.CreateDataSourceFromRDS , Network.AWS.MachineLearning.CreateDataSourceFromRedshift - , Network.AWS.MachineLearning.CreateDataSourceFromS + , Network.AWS.MachineLearning.CreateDataSourceFromS3 , Network.AWS.MachineLearning.CreateEvaluation , Network.AWS.MachineLearning.CreateMLModel , Network.AWS.MachineLearning.CreateRealtimeEndpoint @@ -74,7 +74,7 @@ , Network.AWS.MachineLearning.Types.Sum build-depends: - amazonka-core == 1.3.0.* + amazonka-core == 1.3.1.* , base >= 4.7 && < 5 test-suite amazonka-ml-test @@ -94,9 +94,9 @@ , Test.AWS.MachineLearning.Internal build-depends: - amazonka-core == 1.3.0.* - , amazonka-test == 1.3.0.* - , amazonka-ml == 1.3.0.* + amazonka-core == 1.3.1.* + , amazonka-test == 1.3.1.* + , amazonka-ml == 1.3.1.* , base , bytestring , lens diff --git a/fixture/CreateDataSourceFromS.yaml b/fixture/CreateDataSourceFromS.yaml deleted file mode 100644 --- a/fixture/CreateDataSourceFromS.yaml +++ /dev/null diff --git a/fixture/CreateDataSourceFromS3.yaml b/fixture/CreateDataSourceFromS3.yaml new file mode 100644 --- /dev/null +++ b/fixture/CreateDataSourceFromS3.yaml diff --git a/fixture/CreateDataSourceFromS3Response.proto b/fixture/CreateDataSourceFromS3Response.proto new file mode 100644 --- /dev/null +++ b/fixture/CreateDataSourceFromS3Response.proto 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 @@ -67,8 +67,8 @@ -- ** CreateDataSourceFromRedshift , module Network.AWS.MachineLearning.CreateDataSourceFromRedshift - -- ** CreateDataSourceFromS - , module Network.AWS.MachineLearning.CreateDataSourceFromS + -- ** CreateDataSourceFromS3 + , module Network.AWS.MachineLearning.CreateDataSourceFromS3 -- ** CreateMLModel , module Network.AWS.MachineLearning.CreateMLModel @@ -334,7 +334,7 @@ import Network.AWS.MachineLearning.CreateBatchPrediction import Network.AWS.MachineLearning.CreateDataSourceFromRDS import Network.AWS.MachineLearning.CreateDataSourceFromRedshift -import Network.AWS.MachineLearning.CreateDataSourceFromS +import Network.AWS.MachineLearning.CreateDataSourceFromS3 import Network.AWS.MachineLearning.CreateEvaluation import Network.AWS.MachineLearning.CreateMLModel import Network.AWS.MachineLearning.CreateRealtimeEndpoint diff --git a/gen/Network/AWS/MachineLearning/CreateDataSourceFromS.hs b/gen/Network/AWS/MachineLearning/CreateDataSourceFromS.hs deleted file mode 100644 --- a/gen/Network/AWS/MachineLearning/CreateDataSourceFromS.hs +++ /dev/null @@ -1,219 +0,0 @@ -{-# 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) 2013-2015 Brendan Hay --- License : Mozilla Public License, v. 2.0. --- Maintainer : Brendan Hay --- Stability : auto-generated --- Portability : non-portable (GHC extensions) --- --- 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. --- --- 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'. --- --- 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 - ( - -- * Creating a Request - createDataSourceFromS - , CreateDataSourceFromS - -- * Request Lenses - , cdsfsDataSourceName - , cdsfsComputeStatistics - , cdsfsDataSourceId - , cdsfsDataSpec - - -- * Destructuring the Response - , createDataSourceFromSResponse - , CreateDataSourceFromSResponse - -- * Response Lenses - , cdsfsrsDataSourceId - , cdsfsrsResponseStatus - ) where - -import Network.AWS.MachineLearning.Types -import Network.AWS.MachineLearning.Types.Product -import Network.AWS.Prelude -import Network.AWS.Request -import Network.AWS.Response - --- | /See:/ 'createDataSourceFromS' smart constructor. -data CreateDataSourceFromS = CreateDataSourceFromS' - { _cdsfsDataSourceName :: !(Maybe Text) - , _cdsfsComputeStatistics :: !(Maybe Bool) - , _cdsfsDataSourceId :: !Text - , _cdsfsDataSpec :: !S3DataSpec - } deriving (Eq,Read,Show,Data,Typeable,Generic) - --- | Creates a value of 'CreateDataSourceFromS' with the minimum fields required to make a request. --- --- Use one of the following lenses to modify other fields as desired: --- --- * 'cdsfsDataSourceName' --- --- * 'cdsfsComputeStatistics' --- --- * 'cdsfsDataSourceId' --- --- * 'cdsfsDataSpec' -createDataSourceFromS - :: Text -- ^ 'cdsfsDataSourceId' - -> S3DataSpec -- ^ 'cdsfsDataSpec' - -> CreateDataSourceFromS -createDataSourceFromS pDataSourceId_ pDataSpec_ = - CreateDataSourceFromS' - { _cdsfsDataSourceName = Nothing - , _cdsfsComputeStatistics = Nothing - , _cdsfsDataSourceId = pDataSourceId_ - , _cdsfsDataSpec = pDataSpec_ - } - --- | A user-supplied name or description of the 'DataSource'. -cdsfsDataSourceName :: Lens' CreateDataSourceFromS (Maybe Text) -cdsfsDataSourceName = lens _cdsfsDataSourceName (\ s a -> s{_cdsfsDataSourceName = 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 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. --- --- - DataRearrangement - A JSON string representing the splitting --- requirement of a 'Datasource'. --- --- Sample - --- ' \"{\\\"randomSeed\\\":\\\"some-random-seed\\\", \\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"' --- -cdsfsDataSpec :: Lens' CreateDataSourceFromS S3DataSpec -cdsfsDataSpec = lens _cdsfsDataSpec (\ s a -> s{_cdsfsDataSpec = a}); - -instance AWSRequest CreateDataSourceFromS where - type Rs CreateDataSourceFromS = - CreateDataSourceFromSResponse - request = postJSON machineLearning - response - = receiveJSON - (\ s h x -> - CreateDataSourceFromSResponse' <$> - (x .?> "DataSourceId") <*> (pure (fromEnum s))) - -instance ToHeaders CreateDataSourceFromS where - toHeaders - = const - (mconcat - ["X-Amz-Target" =# - ("AmazonML_20141212.CreateDataSourceFromS" :: - ByteString), - "Content-Type" =# - ("application/x-amz-json-1.1" :: ByteString)]) - -instance ToJSON CreateDataSourceFromS where - toJSON CreateDataSourceFromS'{..} - = object - (catMaybes - [("DataSourceName" .=) <$> _cdsfsDataSourceName, - ("ComputeStatistics" .=) <$> _cdsfsComputeStatistics, - Just ("DataSourceId" .= _cdsfsDataSourceId), - Just ("DataSpec" .= _cdsfsDataSpec)]) - -instance ToPath CreateDataSourceFromS where - toPath = const "/" - -instance ToQuery CreateDataSourceFromS where - toQuery = const mempty - --- | 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) - , _cdsfsrsResponseStatus :: !Int - } deriving (Eq,Read,Show,Data,Typeable,Generic) - --- | 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' --- --- * 'cdsfsrsResponseStatus' -createDataSourceFromSResponse - :: Int -- ^ 'cdsfsrsResponseStatus' - -> CreateDataSourceFromSResponse -createDataSourceFromSResponse pResponseStatus_ = - CreateDataSourceFromSResponse' - { _cdsfsrsDataSourceId = Nothing - , _cdsfsrsResponseStatus = pResponseStatus_ - } - --- | 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}); - --- | The response status code. -cdsfsrsResponseStatus :: Lens' CreateDataSourceFromSResponse Int -cdsfsrsResponseStatus = lens _cdsfsrsResponseStatus (\ s a -> s{_cdsfsrsResponseStatus = a}); diff --git a/gen/Network/AWS/MachineLearning/CreateDataSourceFromS3.hs b/gen/Network/AWS/MachineLearning/CreateDataSourceFromS3.hs new file mode 100644 --- /dev/null +++ b/gen/Network/AWS/MachineLearning/CreateDataSourceFromS3.hs @@ -0,0 +1,219 @@ +{-# 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.CreateDataSourceFromS3 +-- Copyright : (c) 2013-2015 Brendan Hay +-- License : Mozilla Public License, v. 2.0. +-- Maintainer : Brendan Hay +-- Stability : auto-generated +-- Portability : non-portable (GHC extensions) +-- +-- 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. +-- +-- 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'. +-- +-- 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 CreateDataSourceFromS3. +module Network.AWS.MachineLearning.CreateDataSourceFromS3 + ( + -- * Creating a Request + createDataSourceFromS3 + , CreateDataSourceFromS3 + -- * Request Lenses + , cdsfsDataSourceName + , cdsfsComputeStatistics + , cdsfsDataSourceId + , cdsfsDataSpec + + -- * Destructuring the Response + , createDataSourceFromS3Response + , CreateDataSourceFromS3Response + -- * Response Lenses + , cdsfsrsDataSourceId + , cdsfsrsResponseStatus + ) where + +import Network.AWS.MachineLearning.Types +import Network.AWS.MachineLearning.Types.Product +import Network.AWS.Prelude +import Network.AWS.Request +import Network.AWS.Response + +-- | /See:/ 'createDataSourceFromS3' smart constructor. +data CreateDataSourceFromS3 = CreateDataSourceFromS3' + { _cdsfsDataSourceName :: !(Maybe Text) + , _cdsfsComputeStatistics :: !(Maybe Bool) + , _cdsfsDataSourceId :: !Text + , _cdsfsDataSpec :: !S3DataSpec + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'CreateDataSourceFromS3' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'cdsfsDataSourceName' +-- +-- * 'cdsfsComputeStatistics' +-- +-- * 'cdsfsDataSourceId' +-- +-- * 'cdsfsDataSpec' +createDataSourceFromS3 + :: Text -- ^ 'cdsfsDataSourceId' + -> S3DataSpec -- ^ 'cdsfsDataSpec' + -> CreateDataSourceFromS3 +createDataSourceFromS3 pDataSourceId_ pDataSpec_ = + CreateDataSourceFromS3' + { _cdsfsDataSourceName = Nothing + , _cdsfsComputeStatistics = Nothing + , _cdsfsDataSourceId = pDataSourceId_ + , _cdsfsDataSpec = pDataSpec_ + } + +-- | A user-supplied name or description of the 'DataSource'. +cdsfsDataSourceName :: Lens' CreateDataSourceFromS3 (Maybe Text) +cdsfsDataSourceName = lens _cdsfsDataSourceName (\ s a -> s{_cdsfsDataSourceName = 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' CreateDataSourceFromS3 (Maybe Bool) +cdsfsComputeStatistics = lens _cdsfsComputeStatistics (\ s a -> s{_cdsfsComputeStatistics = a}); + +-- | A user-supplied identifier that uniquely identifies the 'DataSource'. +cdsfsDataSourceId :: Lens' CreateDataSourceFromS3 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. +-- +-- - 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}); + +instance AWSRequest CreateDataSourceFromS3 where + type Rs CreateDataSourceFromS3 = + CreateDataSourceFromS3Response + request = postJSON machineLearning + response + = receiveJSON + (\ s h x -> + CreateDataSourceFromS3Response' <$> + (x .?> "DataSourceId") <*> (pure (fromEnum s))) + +instance ToHeaders CreateDataSourceFromS3 where + toHeaders + = const + (mconcat + ["X-Amz-Target" =# + ("AmazonML_20141212.CreateDataSourceFromS3" :: + ByteString), + "Content-Type" =# + ("application/x-amz-json-1.1" :: ByteString)]) + +instance ToJSON CreateDataSourceFromS3 where + toJSON CreateDataSourceFromS3'{..} + = object + (catMaybes + [("DataSourceName" .=) <$> _cdsfsDataSourceName, + ("ComputeStatistics" .=) <$> _cdsfsComputeStatistics, + Just ("DataSourceId" .= _cdsfsDataSourceId), + Just ("DataSpec" .= _cdsfsDataSpec)]) + +instance ToPath CreateDataSourceFromS3 where + toPath = const "/" + +instance ToQuery CreateDataSourceFromS3 where + toQuery = const mempty + +-- | 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:/ 'createDataSourceFromS3Response' smart constructor. +data CreateDataSourceFromS3Response = CreateDataSourceFromS3Response' + { _cdsfsrsDataSourceId :: !(Maybe Text) + , _cdsfsrsResponseStatus :: !Int + } deriving (Eq,Read,Show,Data,Typeable,Generic) + +-- | Creates a value of 'CreateDataSourceFromS3Response' with the minimum fields required to make a request. +-- +-- Use one of the following lenses to modify other fields as desired: +-- +-- * 'cdsfsrsDataSourceId' +-- +-- * 'cdsfsrsResponseStatus' +createDataSourceFromS3Response + :: Int -- ^ 'cdsfsrsResponseStatus' + -> CreateDataSourceFromS3Response +createDataSourceFromS3Response pResponseStatus_ = + CreateDataSourceFromS3Response' + { _cdsfsrsDataSourceId = Nothing + , _cdsfsrsResponseStatus = pResponseStatus_ + } + +-- | 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' CreateDataSourceFromS3Response (Maybe Text) +cdsfsrsDataSourceId = lens _cdsfsrsDataSourceId (\ s a -> s{_cdsfsrsDataSourceId = a}); + +-- | The response status code. +cdsfsrsResponseStatus :: Lens' CreateDataSourceFromS3Response Int +cdsfsrsResponseStatus = lens _cdsfsrsResponseStatus (\ s a -> s{_cdsfsrsResponseStatus = a}); diff --git a/test/Test/AWS/Gen/MachineLearning.hs b/test/Test/AWS/Gen/MachineLearning.hs --- a/test/Test/AWS/Gen/MachineLearning.hs +++ b/test/Test/AWS/Gen/MachineLearning.hs @@ -37,8 +37,8 @@ -- , testCreateDataSourceFromRedshift $ -- createDataSourceFromRedshift -- --- , testCreateDataSourceFromS $ --- createDataSourceFromS +-- , testCreateDataSourceFromS3 $ +-- createDataSourceFromS3 -- -- , testCreateMLModel $ -- createMLModel @@ -115,8 +115,8 @@ -- , testCreateDataSourceFromRedshiftResponse $ -- createDataSourceFromRedshiftResponse -- --- , testCreateDataSourceFromSResponse $ --- createDataSourceFromSResponse +-- , testCreateDataSourceFromS3Response $ +-- createDataSourceFromS3Response -- -- , testCreateMLModelResponse $ -- createMLModelResponse @@ -201,10 +201,10 @@ "CreateDataSourceFromRedshift" "fixture/CreateDataSourceFromRedshift.yaml" -testCreateDataSourceFromS :: CreateDataSourceFromS -> TestTree -testCreateDataSourceFromS = req - "CreateDataSourceFromS" - "fixture/CreateDataSourceFromS.yaml" +testCreateDataSourceFromS3 :: CreateDataSourceFromS3 -> TestTree +testCreateDataSourceFromS3 = req + "CreateDataSourceFromS3" + "fixture/CreateDataSourceFromS3.yaml" testCreateMLModel :: CreateMLModel -> TestTree testCreateMLModel = req @@ -334,12 +334,12 @@ machineLearning (Proxy :: Proxy CreateDataSourceFromRedshift) -testCreateDataSourceFromSResponse :: CreateDataSourceFromSResponse -> TestTree -testCreateDataSourceFromSResponse = res - "CreateDataSourceFromSResponse" - "fixture/CreateDataSourceFromSResponse.proto" +testCreateDataSourceFromS3Response :: CreateDataSourceFromS3Response -> TestTree +testCreateDataSourceFromS3Response = res + "CreateDataSourceFromS3Response" + "fixture/CreateDataSourceFromS3Response.proto" machineLearning - (Proxy :: Proxy CreateDataSourceFromS) + (Proxy :: Proxy CreateDataSourceFromS3) testCreateMLModelResponse :: CreateMLModelResponse -> TestTree testCreateMLModelResponse = res