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Export the Tee type via Data.Fold (#2166)

f5fa162Ranjeet Ranjan4 years ago

core/src/Streamly/Data/Fold.hs+1

compare with master

unifiedsplit

@@ -131,6 +131,7 @@ module Streamly.Data.Fold

131 -- * Fold Type

132

133 Fold -- (..)

134+ , Tee (..)

134

135

135 -- * Constructors

136 -- * Constructors

136 , foldl'

137 , foldl'

core/src/Streamly/Data/Fold/Tee.hs+1−27

@@ -6,34 +6,8 @@

6-- Stability : released

7-- Portability : GHC

8--

9−-- The 'Tee' type is a newtype wrapper over the 'Streamly.Data.Fold.Fold' type providing

10−-- distributive 'Applicative', 'Semigroup', 'Monoid', 'Num', 'Floating' and

11−-- 'Fractional' instances. The input received by the composed 'Tee' is

12−-- replicated and distributed to both the constituent Tees.

13−--

14−-- For example, to compute the average of numbers in a stream without going

15−-- through the stream twice:

16−--

17−-- >>> import Streamly.Data.Fold.Tee (Tee(..))

18−-- >>> import qualified Streamly.Data.Stream as Stream

19−-- >>> import qualified Streamly.Data.Fold as Fold

20−--

21−-- >>> avg = (/) <$> (Tee Fold.sum) <*> (Tee $ fmap fromIntegral Fold.length)

22−-- >>> Stream.fold (unTee avg) $ Stream.fromList [1.0..100.0]

23−-- 50.5

24−--

25−-- Similarly, the 'Semigroup' and 'Monoid' instances of 'Tee' distribute the

26−-- input to both the folds and combine the outputs using Monoid or Semigroup

27−-- instances of the output types:

28−--

29−-- >>> import Data.Monoid (Sum(..))

30−-- >>> t = Tee Fold.one <> Tee Fold.latest

31−-- >>> Stream.fold (unTee t) (fmap Sum $ Stream.enumerateFromTo 1.0 100.0)

32−-- Just (Sum {getSum = 101.0})

33−--

34−-- The 'Num', 'Floating', and 'Fractional' instances work in the same way.

35−--

36module Streamly.Data.Fold.Tee

9module Streamly.Data.Fold.Tee

10+{-# DEPRECATED "Please use \"Streamly.Data.Fold\" instead." #-}

37 ( Tee(..)

11 ( Tee(..)

38 )

12 )

39where

13where

core/src/Streamly/Internal/Data/Fold.hs+2

@@ -18,6 +18,7 @@ module Streamly.Internal.Data.Fold

18 -- * Fold Type

19 Step (..)

20 , Fold (..)

21+ , Tee (..)

22 -- * Constructors

23 -- * Constructors

23 -- | Which constructor to use?

24 -- | Which constructor to use?

@@ -334,6 +335,7 @@ import Prelude hiding

334 , scanl, scanl1, replicate, concatMap, mconcat, foldMap, unzip

335 , scanl, scanl1, replicate, concatMap, mconcat, foldMap, unzip

335 , span, splitAt, break, mapM, zip, maybe)

336 , span, splitAt, break, mapM, zip, maybe)

336import Streamly.Internal.Data.Fold.Type

337import Streamly.Internal.Data.Fold.Type

338+import Streamly.Internal.Data.Fold.Tee

337

339

338-- $setup

340-- $setup

339-- >>> :m

341-- >>> :m

core/src/Streamly/Internal/Data/Fold/Tee.hs+25

@@ -24,6 +24,31 @@ import qualified Streamly.Internal.Data.Fold.Type as Fold

24-- 'Applicative', 'Semigroup', 'Monoid', 'Num', 'Floating' and 'Fractional'

25-- instances.

26--

27+-- The input received by the

28+-- composed 'Tee' is replicated and distributed to both the constituent Tees.

29+--

30+-- For example, to compute the average of numbers in a stream without going

31+-- through the stream twice:

32+--

33+-- >>> import Streamly.Internal.Data.Fold.Tee (Tee(..))

34+-- >>> import qualified Streamly.Data.Stream as Stream

35+-- >>> import qualified Streamly.Data.Fold as Fold

36+--

37+-- >>> avg = (/) <$> (Tee Fold.sum) <*> (Tee $ fmap fromIntegral Fold.length)

38+-- >>> Stream.fold (unTee avg) $ Stream.fromList [1.0..100.0]

39+-- 50.5

40+--

41+-- Similarly, the 'Semigroup' and 'Monoid' instances of 'Tee' distribute the

42+-- input to both the folds and combine the outputs using Monoid or Semigroup

43+-- instances of the output types:

44+--

45+-- >>> import Data.Monoid (Sum(..))

46+-- >>> t = Tee Fold.one <> Tee Fold.latest

47+-- >>> Stream.fold (unTee t) (fmap Sum $ Stream.enumerateFromTo 1.0 100.0)

48+-- Just (Sum {getSum = 101.0})

49+--

50+-- The 'Num', 'Floating', and 'Fractional' instances work in the same way.

51+--

27newtype Tee m a b =

52newtype Tee m a b =

28 Tee { unTee :: Fold m a b }

53 Tee { unTee :: Fold m a b }

29 deriving (Functor)

54 deriving (Functor)