streamly-0.9.0: docs/User/HowTo/faq.md
# Frequently Asked Questions
This document provides idioms or examples to solve common programming
problems using streamly. To start with please go through [Streamly Quick
Overview](/docs/User/Tutorials/quick-overview.md) and [`Streamly examples repository`][streamly-examples].
This document provides additional examples.
## Distribute and Zip Concurrently
Transform a stream in multiple ways, generating multiple transformed
streams and then zip the corresponding elements of each resulting stream
together to create a single transformed stream.
Distributing a value to a stream of consumers concurrently:
```haskell ghci
{-# LANGUAGE FlexibleContexts #-}
import Data.Function ((&))
import qualified Streamly.Data.Fold as Fold
import qualified Streamly.Data.Stream.Prelude as Stream
f1 x =
Stream.fromList [return . (+ 1), return . (+ 2)] -- Stream of functions
& fmap ($ x) -- Stream of lazy actions
& Stream.parSequence (Stream.ordered True) -- Evaluate concurrently
& Stream.fold Fold.toList -- Fold to list
```
Use `parApply` to zip streams concurrently. Here, we zip three singleton
streams:
```haskell ghci
f2 x =
let app = Stream.parApply id
in (,,)
`fmap` Stream.fromEffect (return $ show x)
`app` Stream.fromEffect (return $ x + 1)
`app` Stream.fromEffect (return $ fromIntegral x / 2)
& Stream.fold Fold.one
```
Applying a function concurrently to your input stream:
```haskell ghci
g f xs =
Stream.fromList xs
& Stream.parMapM (Stream.ordered True) f
& Stream.fold Fold.toList
```
You can now use the concurrent map to pipe each element through multiple
transformations using the distribute/zip operations.
```haskell docspec
>>> g f1 [1,2,3,4::Int]
[[2,3],[3,4],[4,5],[5,6]]
>>> g f2 [1,2,3,4::Int]
[Just ("1",2,0.5),Just ("2",3,1.0),Just ("3",4,1.5),Just ("4",5,2.0)]
```
Instead of using `parApply` directly, you can use `mkZipType` to
create a zip Applicative newtype so that you can use the `Applicative`
instance.
```haskell
{-# LANGUAGE UndecidableInstances #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE MultiParamTypeClasses #-}
{-# LANGUAGE TemplateHaskell #-}
import Streamly.Internal.Data.Stream.TypeGen
app = parApply id
$(mkZippingType "ZipConcurrent" "app" True)
```
## Sliding Window
The `writeLastN` fold can be used to create a stream of sliding windows.
```haskell docspec
>>> import qualified Streamly.Data.Array as Array
>>> :{
Stream.fromList [1,2,3,4,5::Int]
& Stream.scan (Array.writeLastN 2)
& Stream.fold Fold.toList
:}
[fromList [],fromList [1],fromList [1,2],fromList [2,3],fromList [3,4],fromList [4,5]]
```
Also see the "Streamly.Internal.Data.Fold.Window" module for widnow based folds.