Deprecated: Please use "Streamly.Internal.Data.Stream from streamly-core package", Streamly.Internal.Data.Stream.Concurrent, Streamly.Internal.Data.Stream.Exception.Lifted, & Streamly.Internal.Data.Stream.Time from streamly package instead.
This is an internal module which is a superset of the corresponding released module Streamly.Prelude. It contains some additional unreleased or experimental APIs.
Documentation
newtype StreamK (m :: Type -> Type) a Source #
Constructors
| MkStream (forall r. State StreamK m a -> (a -> StreamK m a -> m r) -> (a -> m r) -> m r -> m r) |
Instances
For SerialT streams:
(<>) =serial--Semigroup(>>=) = flip .concatMapWithserial--Monad
A single Monad bind behaves like a for loop:
>>>:{IsStream.toList $ do x <- IsStream.fromList [1,2] -- foreach x in stream return x :} [1,2]
Nested monad binds behave like nested for loops:
>>>:{IsStream.toList $ do x <- IsStream.fromList [1,2] -- foreach x in stream y <- IsStream.fromList [3,4] -- foreach y in stream return (x, y) :} [(1,3),(1,4),(2,3),(2,4)]
Since: 0.2.0 (Streamly)
Since: 0.8.0
Instances
For WSerialT streams:
(<>) =wSerial--Semigroup(>>=) = flip .concatMapWithwSerial--Monad
Note that <> is associative only if we disregard the ordering of elements
in the resulting stream.
A single Monad bind behaves like a for loop:
>>>:{IsStream.toList $ IsStream.fromWSerial $ do x <- IsStream.fromList [1,2] -- foreach x in stream return x :} [1,2]
Nested monad binds behave like interleaved nested for loops:
>>>:{IsStream.toList $ IsStream.fromWSerial $ do x <- IsStream.fromList [1,2] -- foreach x in stream y <- IsStream.fromList [3,4] -- foreach y in stream return (x, y) :} [(1,3),(2,3),(1,4),(2,4)]
It is a result of interleaving all the nested iterations corresponding to
element 1 in the first stream with all the nested iterations of element
2:
>>>import Streamly.Prelude (wSerial)>>>IsStream.toList $ IsStream.fromList [(1,3),(1,4)] `IsStream.wSerial` IsStream.fromList [(2,3),(2,4)][(1,3),(2,3),(1,4),(2,4)]
The W in the name stands for wide or breadth wise scheduling in
contrast to the depth wise scheduling behavior of SerialT.
Since: 0.2.0 (Streamly)
Since: 0.8.0
Instances
For AheadT streams:
(<>) =ahead(>>=) = flip .concatMapWithahead
A single Monad bind behaves like a for loop with iterations executed
concurrently, ahead of time, producing side effects of iterations out of
order, but results in order:
>>>:{Stream.toList $ Stream.fromAhead $ do x <- Stream.fromList [2,1] -- foreach x in stream Stream.fromEffect $ delay x :} 1 sec 2 sec [2,1]
Nested monad binds behave like nested for loops with nested iterations
executed concurrently, ahead of time:
>>>:{Stream.toList $ Stream.fromAhead $ do x <- Stream.fromList [1,2] -- foreach x in stream y <- Stream.fromList [2,4] -- foreach y in stream Stream.fromEffect $ delay (x + y) :} 3 sec 4 sec 5 sec 6 sec [3,5,4,6]
The behavior can be explained as follows. All the iterations corresponding
to the element 1 in the first stream constitute one output stream and all
the iterations corresponding to 2 constitute another output stream and
these two output streams are merged using ahead.
Since: 0.3.0 (Streamly)
Since: 0.8.0
Instances
| IsStream AheadT Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| MonadTrans AheadT Source # | |
| (MonadReader r m, MonadAsync m) => MonadReader r (AheadT m) Source # | |
| (MonadState s m, MonadAsync m) => MonadState s (AheadT m) Source # | |
| (MonadBase b m, Monad m, MonadAsync m) => MonadBase b (AheadT m) Source # | |
Defined in Streamly.Internal.Data.Stream.Ahead | |
| (MonadIO m, MonadAsync m) => MonadIO (AheadT m) Source # | |
| (Monad m, MonadAsync m) => Applicative (AheadT m) Source # | |
Defined in Streamly.Internal.Data.Stream.Ahead | |
| Monad m => Functor (AheadT m) Source # | |
| MonadAsync m => Monad (AheadT m) Source # | |
| (MonadThrow m, MonadAsync m) => MonadThrow (AheadT m) Source # | |
| MonadAsync m => Monoid (AheadT m a) Source # | |
| MonadAsync m => Semigroup (AheadT m a) Source # | |
For AsyncT streams:
(<>) =async(>>=) = flip .concatMapWithasync
A single Monad bind behaves like a for loop with iterations of the loop
executed concurrently a la the async combinator, producing results and
side effects of iterations out of order:
>>>:{Stream.toList $ Stream.fromAsync $ do x <- Stream.fromList [2,1] -- foreach x in stream Stream.fromEffect $ delay x :} 1 sec 2 sec [1,2]
Nested monad binds behave like nested for loops with nested iterations
executed concurrently, a la the async combinator:
>>>:{Stream.toList $ Stream.fromAsync $ do x <- Stream.fromList [1,2] -- foreach x in stream y <- Stream.fromList [2,4] -- foreach y in stream Stream.fromEffect $ delay (x + y) :} 3 sec 4 sec 5 sec 6 sec [3,4,5,6]
The behavior can be explained as follows. All the iterations corresponding
to the element 1 in the first stream constitute one output stream and all
the iterations corresponding to 2 constitute another output stream and
these two output streams are merged using async.
Since: 0.1.0 (Streamly)
Since: 0.8.0
Instances
| IsStream AsyncT Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| MonadTrans AsyncT Source # | |
| (MonadReader r m, MonadAsync m) => MonadReader r (AsyncT m) Source # | |
| (MonadState s m, MonadAsync m) => MonadState s (AsyncT m) Source # | |
| (MonadBase b m, Monad m, MonadAsync m) => MonadBase b (AsyncT m) Source # | |
Defined in Streamly.Internal.Data.Stream.Async | |
| (MonadIO m, MonadAsync m) => MonadIO (AsyncT m) Source # | |
| (Monad m, MonadAsync m) => Applicative (AsyncT m) Source # | |
Defined in Streamly.Internal.Data.Stream.Async | |
| Monad m => Functor (AsyncT m) Source # | |
| MonadAsync m => Monad (AsyncT m) Source # | |
| (MonadThrow m, MonadAsync m) => MonadThrow (AsyncT m) Source # | |
| MonadAsync m => Monoid (AsyncT m a) Source # | |
| MonadAsync m => Semigroup (AsyncT m a) Source # | |
For WAsyncT streams:
(<>) =wAsync(>>=) = flip .concatMapWithwAsync
A single Monad bind behaves like a for loop with iterations of the loop
executed concurrently a la the wAsync combinator, producing results and
side effects of iterations out of order:
>>>:{Stream.toList $ Stream.fromWAsync $ do x <- Stream.fromList [2,1] -- foreach x in stream Stream.fromEffect $ delay x :} 1 sec 2 sec [1,2]
Nested monad binds behave like nested for loops with nested iterations
executed concurrently, a la the wAsync combinator:
>>>:{Stream.toList $ Stream.fromWAsync $ do x <- Stream.fromList [1,2] -- foreach x in stream y <- Stream.fromList [2,4] -- foreach y in stream Stream.fromEffect $ delay (x + y) :} 3 sec 4 sec 5 sec 6 sec [3,4,5,6]
The behavior can be explained as follows. All the iterations corresponding
to the element 1 in the first stream constitute one WAsyncT output
stream and all the iterations corresponding to 2 constitute another
WAsyncT output stream and these two output streams are merged using
wAsync.
The W in the name stands for wide or breadth wise scheduling in
contrast to the depth wise scheduling behavior of AsyncT.
Since: 0.2.0 (Streamly)
Since: 0.8.0
Instances
| IsStream WAsyncT Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| MonadTrans WAsyncT Source # | |
| (MonadReader r m, MonadAsync m) => MonadReader r (WAsyncT m) Source # | |
| (MonadState s m, MonadAsync m) => MonadState s (WAsyncT m) Source # | |
| (MonadBase b m, Monad m, MonadAsync m) => MonadBase b (WAsyncT m) Source # | |
Defined in Streamly.Internal.Data.Stream.Async | |
| (MonadIO m, MonadAsync m) => MonadIO (WAsyncT m) Source # | |
| (Monad m, MonadAsync m) => Applicative (WAsyncT m) Source # | |
Defined in Streamly.Internal.Data.Stream.Async | |
| Monad m => Functor (WAsyncT m) Source # | |
| MonadAsync m => Monad (WAsyncT m) Source # | |
| (MonadThrow m, MonadAsync m) => MonadThrow (WAsyncT m) Source # | |
| MonadAsync m => Monoid (WAsyncT m a) Source # | |
| MonadAsync m => Semigroup (WAsyncT m a) Source # | |
For ParallelT streams:
(<>) =parallel(>>=) = flip .concatMapWithparallel
See AsyncT, ParallelT is similar except that all
iterations are strictly concurrent while in AsyncT it depends on the
consumer demand and available threads. See parallel for more details.
Since: 0.1.0 (Streamly)
Since: 0.7.0 (maxBuffer applies to ParallelT streams)
Since: 0.8.0
Instances
data ZipSerialM m a Source #
For ZipSerialM streams:
(<>) = serial
(*) = 'Streamly.Prelude.serial.zipWith' id
Applicative evaluates the streams being zipped serially:
>>>s1 = Stream.fromFoldable [1, 2]>>>s2 = Stream.fromFoldable [3, 4]>>>s3 = Stream.fromFoldable [5, 6]>>>Stream.toList $ Stream.fromZipSerial $ (,,) <$> s1 <*> s2 <*> s3[(1,3,5),(2,4,6)]
Since: 0.2.0 (Streamly)
Since: 0.8.0
Instances
For ZipAsyncM streams:
(<>) = serial
(*) = 'Streamly.Prelude.serial.zipAsyncWith' id
Applicative evaluates the streams being zipped concurrently, the following would take half the time that it would take in serial zipping:
>>>s = Stream.fromFoldableM $ Prelude.map delay [1, 1, 1]>>>Stream.toList $ Stream.fromZipAsync $ (,) <$> s <*> s... [(1,1),(1,1),(1,1)]
Since: 0.2.0 (Streamly)
Since: 0.8.0
Instances
| IsStream ZipAsyncM Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| MonadAsync m => Applicative (ZipAsyncM m) Source # | |
Defined in Streamly.Internal.Data.Stream.ZipAsync Methods pure :: a -> ZipAsyncM m a Source # (<*>) :: ZipAsyncM m (a -> b) -> ZipAsyncM m a -> ZipAsyncM m b Source # liftA2 :: (a -> b -> c) -> ZipAsyncM m a -> ZipAsyncM m b -> ZipAsyncM m c Source # (*>) :: ZipAsyncM m a -> ZipAsyncM m b -> ZipAsyncM m b Source # (<*) :: ZipAsyncM m a -> ZipAsyncM m b -> ZipAsyncM m a Source # | |
| Monad m => Functor (ZipAsyncM m) Source # | |
| Monoid (ZipAsyncM m a) Source # | |
| Semigroup (ZipAsyncM m a) Source # | |
type ZipSerial = ZipSerialM IO Source #
class (forall m a. MonadAsync m => Semigroup (t m a), forall m a. MonadAsync m => Monoid (t m a), forall m. Monad m => Functor (t m), forall m. MonadAsync m => Applicative (t m)) => IsStream t where Source #
Class of types that can represent a stream of elements of some type a in
some monad m.
Since: 0.2.0 (Streamly)
Since: 0.8.0
Methods
consM :: MonadAsync m => m a -> t m a -> t m a infixr 5 Source #
Constructs a stream by adding a monadic action at the head of an existing stream. For example:
> toList $ getLine `consM` getLine `consM` nil hello world ["hello","world"]
Concurrent (do not use fromParallel to construct infinite streams)
Since: 0.2.0
(|:) :: MonadAsync m => m a -> t m a -> t m a infixr 5 Source #
Operator equivalent of consM. We can read it as "parallel colon"
to remember that | comes before :.
> toList $ getLine |: getLine |: nil hello world ["hello","world"]
let delay = threadDelay 1000000 >> print 1 drain $ fromSerial $ delay |: delay |: delay |: nil drain $ fromParallel $ delay |: delay |: delay |: nil
Concurrent (do not use fromParallel to construct infinite streams)
Since: 0.2.0
Instances
| IsStream AheadT Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| IsStream AsyncT Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| IsStream WAsyncT Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| IsStream ParallelT Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| IsStream SerialT Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| IsStream WSerialT Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
| IsStream ZipSerialM Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type Methods toStream :: forall (m :: Type -> Type) a. ZipSerialM m a -> StreamK m a fromStream :: forall (m :: Type -> Type) a. StreamK m a -> ZipSerialM m a consM :: MonadAsync m => m a -> ZipSerialM m a -> ZipSerialM m a Source # (|:) :: MonadAsync m => m a -> ZipSerialM m a -> ZipSerialM m a Source # | |
| IsStream ZipAsyncM Source # | |
Defined in Streamly.Internal.Data.Stream.IsStream.Type | |
fromList :: (Monad m, IsStream t) => [a] -> t m a Source #
fromList =foldrconsnil
Construct a stream from a list of pure values. This is more efficient than
fromFoldable for serial streams.
Since: 0.4.0
cons :: IsStream t => a -> t m a -> t m a infixr 5 Source #
Construct a stream by adding a pure value at the head of an existing
stream. For serial streams this is the same as (return a) `consM` r but
more efficient. For concurrent streams this is not concurrent whereas
consM is concurrent. For example:
> toList $ 1 `cons` 2 `cons` 3 `cons` nil [1,2,3]
Since: 0.1.0
mkStream :: IsStream t => (forall r. State StreamK m a -> (a -> t m a -> m r) -> (a -> m r) -> m r -> m r) -> t m a Source #
Build a stream from an SVar, a stop continuation, a singleton stream
continuation and a yield continuation.
foldStreamShared :: IsStream t => State StreamK m a -> (a -> t m a -> m r) -> (a -> m r) -> m r -> t m a -> m r Source #
Fold a stream by providing an SVar, a stop continuation, a singleton continuation and a yield continuation. The stream would share the current SVar passed via the State.
foldStream :: IsStream t => State StreamK m a -> (a -> t m a -> m r) -> (a -> m r) -> m r -> t m a -> m r Source #
Fold a stream by providing a State, stop continuation, a singleton continuation and a yield continuation. The stream will not use the SVar passed via State.
foldlx' :: (IsStream t, Monad m) => (x -> a -> x) -> x -> (x -> b) -> t m a -> m b Source #
Strict left fold with an extraction function. Like the standard strict
left fold, but applies a user supplied extraction function (the third
argument) to the folded value at the end. This is designed to work with the
foldl library. The suffix x is a mnemonic for extraction.
Since: 0.7.0
foldlMx' :: (IsStream t, Monad m) => (x -> a -> m x) -> m x -> (x -> m b) -> t m a -> m b Source #
Like foldlx', but with a monadic step function.
Since: 0.7.0
concatMapWith :: IsStream t => (t m b -> t m b -> t m b) -> (a -> t m b) -> t m a -> t m b Source #
concatMapWith mixer generator stream is a two dimensional looping
combinator. The generator function is used to generate streams from the
elements in the input stream and the mixer function is used to merge
those streams.
Note we can merge streams concurrently by using a concurrent merge function.
Since: 0.7.0
Since: 0.8.0 (signature change)
fromStreamK :: IsStream t => StreamK m a -> t m a Source #
foldrMx :: (IsStream t, Monad m) => (a -> m x -> m x) -> m x -> (m x -> m b) -> t m a -> m b Source #
adapt :: (IsStream t1, IsStream t2) => t1 m a -> t2 m a Source #
Adapt any specific stream type to any other specific stream type.
Since: 0.1.0 (Streamly)
Since: 0.8.0
concatFoldableWith :: (IsStream t, Foldable f) => (t m a -> t m a -> t m a) -> f (t m a) -> t m a Source #
A variant of fold that allows you to fold a Foldable
container of streams using the specified stream sum operation.
concatFoldableWith async $ map return [1..3]Equivalent to:
concatFoldableWith f = Prelude.foldr f D.nil concatFoldableWith f = D.concatMapFoldableWith f id
Since: 0.8.0 (Renamed foldWith to concatFoldableWith)
Since: 0.1.0 (Streamly)
concatMapFoldableWith :: (IsStream t, Foldable f) => (t m b -> t m b -> t m b) -> (a -> t m b) -> f a -> t m b Source #
A variant of foldMap that allows you to map a monadic streaming action
on a Foldable container and then fold it using the specified stream merge
operation.
concatMapFoldableWith async return [1..3]Equivalent to:
concatMapFoldableWith f g = Prelude.foldr (f . g) S.nil concatMapFoldableWith f g xs = S.concatMapWith f g (S.fromFoldable xs)
Since: 0.8.0 (Renamed foldMapWith to concatMapFoldableWith)
Since: 0.1.0 (Streamly)
concatForFoldableWith :: (IsStream t, Foldable f) => (t m b -> t m b -> t m b) -> f a -> (a -> t m b) -> t m b Source #
Like concatMapFoldableWith but with the last two arguments reversed i.e. the
monadic streaming function is the last argument.
Equivalent to:
concatForFoldableWith f xs g = Prelude.foldr (f . g) D.nil xs concatForFoldableWith f = flip (D.concatMapFoldableWith f)
Since: 0.8.0 (Renamed forEachWith to concatForFoldableWith)
Since: 0.1.0 (Streamly)
fromSerial :: IsStream t => SerialT m a -> t m a Source #
fromWSerial :: IsStream t => WSerialT m a -> t m a Source #
fromWAsync :: IsStream t => WAsyncT m a -> t m a Source #
fromParallel :: IsStream t => ParallelT m a -> t m a Source #
fromZipSerial :: IsStream t => ZipSerialM m a -> t m a Source #
fromZipAsync :: IsStream t => ZipAsyncM m a -> t m a Source #
toConsK :: IsStream t => (m a -> t m a -> t m a) -> m a -> StreamK m a -> StreamK m a Source #
Adapt a polymorphic consM operation to a StreamK cons operation
Primitives
cons :: IsStream t => a -> t m a -> t m a infixr 5 Source #
Construct a stream by adding a pure value at the head of an existing
stream. For serial streams this is the same as (return a) `consM` r but
more efficient. For concurrent streams this is not concurrent whereas
consM is concurrent. For example:
> toList $ 1 `cons` 2 `cons` 3 `cons` nil [1,2,3]
Since: 0.1.0
consM :: (IsStream t, MonadAsync m) => m a -> t m a -> t m a infixr 5 Source #
Constructs a stream by adding a monadic action at the head of an existing stream. For example:
> toList $ getLine `consM` getLine `consM` nil hello world ["hello","world"]
Concurrent (do not use fromParallel to construct infinite streams)
Since: 0.2.0
(|:) :: (IsStream t, MonadAsync m) => m a -> t m a -> t m a infixr 5 Source #
Operator equivalent of consM. We can read it as "parallel colon"
to remember that | comes before :.
> toList $ getLine |: getLine |: nil hello world ["hello","world"]
let delay = threadDelay 1000000 >> print 1 drain $ fromSerial $ delay |: delay |: delay |: nil drain $ fromParallel $ delay |: delay |: delay |: nil
Concurrent (do not use fromParallel to construct infinite streams)
Since: 0.2.0
From Unfold
unfold :: (IsStream t, Monad m) => Unfold m a b -> a -> t m b Source #
Convert an Unfold into a stream by supplying it an input seed.
>>>Stream.drain $ Stream.unfold Unfold.replicateM (3, putStrLn "hello")hello hello hello
Since: 0.7.0
unfold0 :: (IsStream t, Monad m) => Unfold m Void b -> t m b Source #
Convert an Unfold with a closed input end into a stream.
Pre-release
Unfolding
unfoldr :: (Monad m, IsStream t) => (b -> Maybe (a, b)) -> b -> t m a Source #
>>>:{unfoldr step s = case step s of Nothing -> Stream.nil Just (a, b) -> a `Stream.cons` unfoldr step b :}
Build a stream by unfolding a pure step function step starting from a
seed s. The step function returns the next element in the stream and the
next seed value. When it is done it returns Nothing and the stream ends.
For example,
>>>:{let f b = if b > 2 then Nothing else Just (b, b + 1) in Stream.toList $ Stream.unfoldr f 0 :} [0,1,2]
Since: 0.1.0
unfoldrM :: forall t m b a. (IsStream t, MonadAsync m) => (b -> m (Maybe (a, b))) -> b -> t m a Source #
Build a stream by unfolding a monadic step function starting from a
seed. The step function returns the next element in the stream and the next
seed value. When it is done it returns Nothing and the stream ends. For
example,
>>>:{let f b = if b > 2 then return Nothing else return (Just (b, b + 1)) in Stream.toList $ Stream.unfoldrM f 0 :} [0,1,2]
When run concurrently, the next unfold step can run concurrently with the processing of the output of the previous step. Note that more than one step cannot run concurrently as the next step depends on the output of the previous step.
>>>:{let f b = if b > 2 then return Nothing else threadDelay 1000000 >> return (Just (b, b + 1)) in Stream.toList $ Stream.delay 1 $ Stream.fromAsync $ Stream.unfoldrM f 0 :} [0,1,2]
Concurrent
Since: 0.1.0
From Values
fromPure :: IsStream t => a -> t m a Source #
fromPure a = a `cons` nil
Create a singleton stream from a pure value.
The following holds in monadic streams, but not in Zip streams:
fromPure = pure fromPure = fromEffect . pure
In Zip applicative streams fromPure is not the same as pure because in that
case pure is equivalent to repeat instead. fromPure and pure are
equally efficient, in other cases fromPure may be slightly more efficient
than the other equivalent definitions.
Since: 0.8.0 (Renamed yield to fromPure)
fromEffect :: (Monad m, IsStream t) => m a -> t m a Source #
fromEffect m = m `consM` nil
Create a singleton stream from a monadic action.
> Stream.toList $ Stream.fromEffect getLine hello ["hello"]
Since: 0.8.0 (Renamed yieldM to fromEffect)
repeat :: (IsStream t, Monad m) => a -> t m a Source #
Generate an infinite stream by repeating a pure value.
Since: 0.4.0
repeatM :: (IsStream t, MonadAsync m) => m a -> t m a Source #
>>>repeatM = fix . consM>>>repeatM = cycle1 . fromEffect
Generate a stream by repeatedly executing a monadic action forever.
>>>:{repeatAsync = Stream.repeatM (threadDelay 1000000 >> print 1) & Stream.take 10 & Stream.fromAsync & Stream.drain :}
Concurrent, infinite (do not use with fromParallel)
Since: 0.2.0
replicate :: (IsStream t, Monad m) => Int -> a -> t m a Source #
>>>replicate n = Stream.take n . Stream.repeat
Generate a stream of length n by repeating a value n times.
Since: 0.6.0
replicateM :: forall t m a. (IsStream t, MonadAsync m) => Int -> m a -> t m a Source #
>>>replicateM n = Stream.take n . Stream.repeatM
Generate a stream by performing a monadic action n times. Same as:
>>>pr n = threadDelay 1000000 >> print n
This runs serially and takes 3 seconds:
>>>Stream.drain $ Stream.fromSerial $ Stream.replicateM 3 $ pr 11 1 1
This runs concurrently and takes just 1 second:
>>>Stream.drain $ Stream.fromAsync $ Stream.replicateM 3 $ pr 11 1 1
Concurrent
Since: 0.1.1
Enumeration
class Enum a => Enumerable a where Source #
Types that can be enumerated as a stream. The operations in this type
class are equivalent to those in the Enum type class, except that these
generate a stream instead of a list. Use the functions in
Streamly.Internal.Data.Stream.Enumeration module to define new instances.
Since: 0.6.0
Methods
enumerateFrom :: (IsStream t, Monad m) => a -> t m a Source #
enumerateFrom from generates a stream starting with the element
from, enumerating up to maxBound when the type is Bounded or
generating an infinite stream when the type is not Bounded.
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFrom (0 :: Int) [0,1,2,3]
For Fractional types, enumeration is numerically stable. However, no
overflow or underflow checks are performed.
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFrom 1.1 [1.1,2.1,3.1,4.1]
Since: 0.6.0
enumerateFromTo :: (IsStream t, Monad m) => a -> a -> t m a Source #
Generate a finite stream starting with the element from, enumerating
the type up to the value to. If to is smaller than from then an
empty stream is returned.
>>> Stream.toList $ Stream.enumerateFromTo 0 4 [0,1,2,3,4]
For Fractional types, the last element is equal to the specified to
value after rounding to the nearest integral value.
>>> Stream.toList $ Stream.enumerateFromTo 1.1 4 [1.1,2.1,3.1,4.1] >>> Stream.toList $ Stream.enumerateFromTo 1.1 4.6 [1.1,2.1,3.1,4.1,5.1]
Since: 0.6.0
enumerateFromThen :: (IsStream t, Monad m) => a -> a -> t m a Source #
enumerateFromThen from then generates a stream whose first element
is from, the second element is then and the successive elements are
in increments of then - from. Enumeration can occur downwards or
upwards depending on whether then comes before or after from. For
Bounded types the stream ends when maxBound is reached, for
unbounded types it keeps enumerating infinitely.
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromThen 0 2 [0,2,4,6] >>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromThen 0 (-2) [0,-2,-4,-6]
Since: 0.6.0
enumerateFromThenTo :: (IsStream t, Monad m) => a -> a -> a -> t m a Source #
enumerateFromThenTo from then to generates a finite stream whose
first element is from, the second element is then and the successive
elements are in increments of then - from up to to. Enumeration can
occur downwards or upwards depending on whether then comes before or
after from.
>>> Stream.toList $ Stream.enumerateFromThenTo 0 2 6 [0,2,4,6] >>> Stream.toList $ Stream.enumerateFromThenTo 0 (-2) (-6) [0,-2,-4,-6]
Since: 0.6.0
Instances
enumerateTo :: (IsStream t, Monad m, Bounded a, Enumerable a) => a -> t m a Source #
Time Enumeration
times :: (IsStream t, MonadAsync m) => t m (AbsTime, RelTime64) Source #
times returns a stream of time value tuples with clock of 10 ms
granularity. The first component of the tuple is an absolute time reference
(epoch) denoting the start of the stream and the second component is a time
relative to the reference.
>>>Stream.mapM_ (\x -> print x >> threadDelay 1000000) $ Stream.take 3 $ Stream.times(AbsTime (TimeSpec {sec = ..., nsec = ...}),RelTime64 (NanoSecond64 ...)) (AbsTime (TimeSpec {sec = ..., nsec = ...}),RelTime64 (NanoSecond64 ...)) (AbsTime (TimeSpec {sec = ..., nsec = ...}),RelTime64 (NanoSecond64 ...))
Note: This API is not safe on 32-bit machines.
Pre-release
absTimes :: (IsStream t, MonadAsync m, Functor (t m)) => t m AbsTime Source #
absTimes returns a stream of absolute timestamps using a clock of 10 ms
granularity.
>>>Stream.mapM_ print $ Stream.delayPre 1 $ Stream.take 3 $ Stream.absTimesAbsTime (TimeSpec {sec = ..., nsec = ...}) AbsTime (TimeSpec {sec = ..., nsec = ...}) AbsTime (TimeSpec {sec = ..., nsec = ...})
Note: This API is not safe on 32-bit machines.
Pre-release
absTimesWith :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m AbsTime Source #
absTimesWith g returns a stream of absolute timestamps using a clock of
granularity g specified in seconds. A low granularity clock is more
expensive in terms of CPU usage. Any granularity lower than 1 ms is treated
as 1 ms.
>>>Stream.mapM_ print $ Stream.delayPre 1 $ Stream.take 3 $ absTimesWith 0.01AbsTime (TimeSpec {sec = ..., nsec = ...}) AbsTime (TimeSpec {sec = ..., nsec = ...}) AbsTime (TimeSpec {sec = ..., nsec = ...})
Note: This API is not safe on 32-bit machines.
Pre-release
relTimes :: (IsStream t, MonadAsync m, Functor (t m)) => t m RelTime64 Source #
relTimes returns a stream of relative time values starting from 0,
using a clock of granularity 10 ms.
>>>Stream.mapM_ print $ Stream.delayPre 1 $ Stream.take 3 $ Stream.relTimesRelTime64 (NanoSecond64 ...) RelTime64 (NanoSecond64 ...) RelTime64 (NanoSecond64 ...)
Note: This API is not safe on 32-bit machines.
Pre-release
relTimesWith :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m RelTime64 Source #
relTimesWith g returns a stream of relative time values starting from 0,
using a clock of granularity g specified in seconds. A low granularity
clock is more expensive in terms of CPU usage. Any granularity lower than 1
ms is treated as 1 ms.
>>>Stream.mapM_ print $ Stream.delayPre 1 $ Stream.take 3 $ Stream.relTimesWith 0.01RelTime64 (NanoSecond64 ...) RelTime64 (NanoSecond64 ...) RelTime64 (NanoSecond64 ...)
Note: This API is not safe on 32-bit machines.
Pre-release
durations :: Double -> t m RelTime64 Source #
durations g returns a stream of relative time values measuring the time
elapsed since the immediate predecessor element of the stream was generated.
The first element of the stream is always 0. durations uses a clock of
granularity g specified in seconds. A low granularity clock is more
expensive in terms of CPU usage. The minimum granularity is 1 millisecond.
Durations lower than 1 ms will be 0.
Note: This API is not safe on 32-bit machines.
Unimplemented
ticks :: Rate -> t m () Source #
Generate ticks at the specified rate. The rate is adaptive, the tick
generation speed can be increased or decreased at different times to achieve
the specified rate. The specific behavior for different styles of Rate
specifications is documented under Rate. The effective maximum rate
achieved by a stream is governed by the processor speed.
Unimplemented
timeout :: AbsTime -> t m () Source #
Generate a singleton event at or after the specified absolute time. Note that this is different from a threadDelay, a threadDelay starts from the time when the action is evaluated, whereas if we use AbsTime based timeout it will immediately expire if the action is evaluated too late.
Unimplemented
From Generators
fromIndices :: (IsStream t, Monad m) => (Int -> a) -> t m a Source #
>>>fromIndices f = fmap f $ Stream.enumerateFrom 0>>>fromIndices f = let g i = f i `Stream.cons` g (i + 1) in g 0
Generate an infinite stream, whose values are the output of a function f
applied on the corresponding index. Index starts at 0.
>>>Stream.toList $ Stream.take 5 $ Stream.fromIndices id[0,1,2,3,4]
Since: 0.6.0
fromIndicesM :: forall t m a. (IsStream t, MonadAsync m) => (Int -> m a) -> t m a Source #
>>>fromIndicesM f = Stream.mapM f $ Stream.enumerateFrom 0>>>fromIndicesM f = let g i = f i `Stream.consM` g (i + 1) in g 0
Generate an infinite stream, whose values are the output of a monadic
function f applied on the corresponding index. Index starts at 0.
Concurrent
Since: 0.6.0
Iteration
iterate :: (IsStream t, Monad m) => (a -> a) -> a -> t m a Source #
>>>iterate f x = x `Stream.cons` iterate f x
Generate an infinite stream with x as the first element and each
successive element derived by applying the function f on the previous
element.
>>>Stream.toList $ Stream.take 5 $ Stream.iterate (+1) 1[1,2,3,4,5]
Since: 0.1.2
iterateM :: forall t m a. (IsStream t, MonadAsync m) => (a -> m a) -> m a -> t m a Source #
>>>iterateM f m = m >>= \a -> return a `Stream.consM` iterateM f (f a)
Generate an infinite stream with the first element generated by the action
m and each successive element derived by applying the monadic function
f on the previous element.
>>>pr n = threadDelay 1000000 >> print n>>>:{Stream.iterateM (\x -> pr x >> return (x + 1)) (return 0) & Stream.take 3 & Stream.fromSerial & Stream.toList :} 0 1 [0,1,2]
When run concurrently, the next iteration can run concurrently with the processing of the previous iteration. Note that more than one iteration cannot run concurrently as the next iteration depends on the output of the previous iteration.
>>>:{Stream.iterateM (\x -> pr x >> return (x + 1)) (return 0) & Stream.delay 1 & Stream.take 3 & Stream.fromAsync & Stream.toList :} 0 1 ...
Concurrent
Since: 0.1.2
Since: 0.7.0 (signature change)
Cyclic Elements
mfix :: (IsStream t, Monad m) => (m a -> t m a) -> t m a Source #
We can define cyclic structures using let:
>>>let (a, b) = ([1, b], head a) in (a, b)([1,1],1)
The function fix defined as:
>>>fix f = let x = f x in x
ensures that the argument of a function and its output refer to the same
lazy value x i.e. the same location in memory. Thus x can be defined
in terms of itself, creating structures with cyclic references.
>>>f ~(a, b) = ([1, b], head a)>>>fix f([1,1],1)
mfix is essentially the same as fix but for monadic
values.
Using mfix for streams we can construct a stream in which each element of
the stream is defined in a cyclic fashion. The argument of the function
being fixed represents the current element of the stream which is being
returned by the stream monad. Thus, we can use the argument to construct
itself.
Pre-release
From Containers
fromList :: (Monad m, IsStream t) => [a] -> t m a Source #
fromList =foldrconsnil
Construct a stream from a list of pure values. This is more efficient than
fromFoldable for serial streams.
Since: 0.4.0
fromListM :: (MonadAsync m, IsStream t) => [m a] -> t m a Source #
>>>fromListM = Stream.fromFoldableM>>>fromListM = Stream.sequence . Stream.fromList>>>fromListM = Stream.mapM id . Stream.fromList>>>fromListM = Prelude.foldr Stream.consM Stream.nil
Construct a stream from a list of monadic actions. This is more efficient
than fromFoldableM for serial streams.
Since: 0.4.0
fromFoldable :: (IsStream t, Foldable f) => f a -> t m a Source #
>>>fromFoldable = Prelude.foldr Stream.cons Stream.nil
Construct a stream from a Foldable containing pure values:
Since: 0.2.0
fromFoldableM :: (IsStream t, MonadAsync m, Foldable f) => f (m a) -> t m a Source #
>>>fromFoldableM = Prelude.foldr Stream.consM Stream.nil
Construct a stream from a Foldable containing monadic actions.
>>>pr n = threadDelay 1000000 >> print n>>>Stream.drain $ Stream.fromSerial $ Stream.fromFoldableM $ map pr [1,2,3]1 2 3
>>>Stream.drain $ Stream.fromAsync $ Stream.fromFoldableM $ map pr [1,2,3]... ... ...
Concurrent (do not use with fromParallel on infinite containers)
Since: 0.3.0
fromCallback :: MonadAsync m => ((a -> m ()) -> m ()) -> SerialT m a Source #
Takes a callback setter function and provides it with a callback. The callback when invoked adds a value at the tail of the stream. Returns a stream of values generated by the callback.
Pre-release
fromPrimIORef :: (IsStream t, MonadIO m, Unbox a) => IORef a -> t m a Source #
Construct a stream by reading an Unboxed IORef repeatedly.
Pre-release
Deprecated
fromHandle :: (IsStream t, MonadIO m) => Handle -> t m String Source #
Read lines from an IO Handle into a stream of Strings.
Since: 0.1.0
currentTime :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m AbsTime Source #
maximumBy :: Monad m => (a -> a -> Ordering) -> SerialT m a -> m (Maybe a) Source #
Determine the maximum element in a stream using the supplied comparison function.
maximumBy = Stream.fold Fold.maximumBy
Since: 0.6.0
minimumBy :: Monad m => (a -> a -> Ordering) -> SerialT m a -> m (Maybe a) Source #
Determine the minimum element in a stream using the supplied comparison function.
minimumBy = Stream.fold Fold.minimumBy
Since: 0.6.0
foldr :: Monad m => (a -> b -> b) -> b -> SerialT m a -> m b Source #
Right fold, lazy for lazy monads and pure streams, and strict for strict monads.
Please avoid using this routine in strict monads like IO unless you need a
strict right fold. This is provided only for use in lazy monads (e.g.
Identity) or pure streams. Note that with this signature it is not possible
to implement a lazy foldr when the monad m is strict. In that case it
would be strict in its accumulator and therefore would necessarily consume
all its input.
Since: 0.1.0
toList :: Monad m => SerialT m a -> m [a] Source #
toList = Stream.foldr (:) []
Convert a stream into a list in the underlying monad. The list can be
consumed lazily in a lazy monad (e.g. Identity). In a strict monad (e.g.
IO) the whole list is generated and buffered before it can be consumed.
Warning! working on large lists accumulated as buffers in memory could be very inefficient, consider using Streamly.Array instead.
Since: 0.1.0
mconcat :: (Monad m, Monoid a) => SerialT m a -> m a Source #
Fold a stream of monoid elements by appending them.
mconcat = Stream.fold Fold.mconcat
Pre-release
head :: Monad m => SerialT m a -> m (Maybe a) Source #
Extract the first element of the stream, if any.
head = (!! 0) head = Stream.fold Fold.one
Since: 0.1.0
uncons :: (IsStream t, Monad m) => SerialT m a -> m (Maybe (a, t m a)) Source #
Decompose a stream into its head and tail. If the stream is empty, returns
Nothing. If the stream is non-empty, returns Just (a, ma), where a is
the head of the stream and ma its tail.
This can be used to do pretty much anything in an imperative manner, as it just breaks down the stream into individual elements and we can loop over them as we deem fit. For example, this can be used to convert a streamly stream into other stream types.
All the folds in this module can be expressed in terms of uncons, however,
this is generally less efficient than specific folds because it takes apart
the stream one element at a time, therefore, does not take adavantage of
stream fusion.
Since: 0.1.0
tail :: (IsStream t, Monad m) => SerialT m a -> m (Maybe (t m a)) Source #
tail = fmap (fmap snd) . Stream.uncons
Extract all but the first element of the stream, if any.
Since: 0.1.1
last :: Monad m => SerialT m a -> m (Maybe a) Source #
Extract the last element of the stream, if any.
last xs = xs !! (Stream.length xs - 1) last = Stream.fold Fold.last
Since: 0.1.1
init :: (IsStream t, Monad m) => SerialT m a -> m (Maybe (t m a)) Source #
Extract all but the last element of the stream, if any.
Since: 0.5.0
null :: Monad m => SerialT m a -> m Bool Source #
Determine whether the stream is empty.
null = Stream.fold Fold.null
Since: 0.1.1
foldl' :: Monad m => (b -> a -> b) -> b -> SerialT m a -> m b Source #
Left associative/strict push fold. foldl' reduce initial stream invokes
reduce with the accumulator and the next input in the input stream, using
initial as the initial value of the current value of the accumulator. When
the input is exhausted the current value of the accumulator is returned.
Make sure to use a strict data structure for accumulator to not build
unnecessary lazy expressions unless that's what you want. See the previous
section for more details.
Since: 0.2.0
foldl1' :: Monad m => (a -> a -> a) -> SerialT m a -> m (Maybe a) Source #
Strict left fold, for non-empty streams, using first element as the
starting value. Returns Nothing if the stream is empty.
Since: 0.5.0
sum :: (Monad m, Num a) => SerialT m a -> m a Source #
Determine the sum of all elements of a stream of numbers. Returns 0 when
the stream is empty. Note that this is not numerically stable for floating
point numbers.
sum = Stream.fold Fold.sum
Since: 0.1.0
product :: (Monad m, Num a) => SerialT m a -> m a Source #
Determine the product of all elements of a stream of numbers. Returns 1
when the stream is empty.
product = Stream.fold Fold.product
Since: 0.1.1
foldr1 :: Monad m => (a -> a -> a) -> SerialT m a -> m (Maybe a) Source #
Lazy right fold for non-empty streams, using first element as the starting
value. Returns Nothing if the stream is empty.
Since: 0.5.0
maximum :: (Monad m, Ord a) => SerialT m a -> m (Maybe a) Source #
maximum = maximumBy compare
maximum = Stream.fold Fold.maximum
Determine the maximum element in a stream.
Since: 0.1.0
minimum :: (Monad m, Ord a) => SerialT m a -> m (Maybe a) Source #
minimum = minimumBy compare
minimum = Stream.fold Fold.minimum
Determine the minimum element in a stream.
Since: 0.1.0
and :: Monad m => SerialT m Bool -> m Bool Source #
Determines if all elements of a boolean stream are True.
and = Stream.fold Fold.and
Since: 0.5.0
or :: Monad m => SerialT m Bool -> m Bool Source #
Determines whether at least one element of a boolean stream is True.
or = Stream.fold Fold.or
Since: 0.5.0
any :: Monad m => (a -> Bool) -> SerialT m a -> m Bool Source #
Determine whether any of the elements of a stream satisfy a predicate.
any = Stream.fold Fold.any
Since: 0.1.0
all :: Monad m => (a -> Bool) -> SerialT m a -> m Bool Source #
Determine whether all elements of a stream satisfy a predicate.
all = Stream.fold Fold.all
Since: 0.1.0
elem :: (Monad m, Eq a) => a -> SerialT m a -> m Bool Source #
Determine whether an element is present in the stream.
elem = Stream.fold Fold.elem
Since: 0.1.0
notElem :: (Monad m, Eq a) => a -> SerialT m a -> m Bool Source #
Determine whether an element is not present in the stream.
notElem = Stream.fold Fold.length
Since: 0.1.0
lookup :: (Monad m, Eq a) => a -> SerialT m (a, b) -> m (Maybe b) Source #
In a stream of (key-value) pairs (a, b), return the value b of the
first pair where the key equals the given value a.
lookup = snd <$> Stream.find ((==) . fst) lookup = Stream.fold Fold.lookup
Since: 0.5.0
(!!) :: Monad m => SerialT m a -> Int -> m (Maybe a) Source #
Lookup the element at the given index.
Since: 0.6.0
fold :: Monad m => Fold m a b -> SerialT m a -> m b Source #
Fold a stream using the supplied left Fold and reducing the resulting
expression strictly at each step. The behavior is similar to foldl'. A
Fold can terminate early without consuming the full stream. See the
documentation of individual Folds for termination behavior.
>>>Stream.fold Fold.sum (Stream.enumerateFromTo 1 100)5050
Folds never fail, therefore, they produce a default value even when no input is provided. It means we can always fold an empty stream and get a valid result. For example:
>>>Stream.fold Fold.sum Stream.nil0
However, foldMany on an empty stream results in an empty stream.
Therefore, Stream.fold f is not the same as Stream.head . Stream.foldMany
f.
fold f = Stream.parse (Parser.fromFold f)
Since: 0.7.0
foldrM :: Monad m => (a -> m b -> m b) -> m b -> SerialT m a -> m b Source #
Right associative/lazy pull fold. foldrM build final stream constructs
an output structure using the step function build. build is invoked with
the next input element and the remaining (lazy) tail of the output
structure. It builds a lazy output expression using the two. When the "tail
structure" in the output expression is evaluated it calls build again thus
lazily consuming the input stream until either the output expression built
by build is free of the "tail" or the input is exhausted in which case
final is used as the terminating case for the output structure. For more
details see the description in the previous section.
Example, determine if any element is odd in a stream:
>>>Stream.foldrM (\x xs -> if odd x then return True else xs) (return False) $ Stream.fromList (2:4:5:undefined)True
Since: 0.7.0 (signature changed)
Since: 0.2.0 (signature changed)
Since: 0.1.0
mapM_ :: Monad m => (a -> m b) -> SerialT m a -> m () Source #
mapM_ = Stream.drain . Stream.mapM
Apply a monadic action to each element of the stream and discard the output of the action. This is not really a pure transformation operation but a transformation followed by fold.
Since: 0.1.0
find :: Monad m => (a -> Bool) -> SerialT m a -> m (Maybe a) Source #
Like findM but with a non-monadic predicate.
find p = findM (return . p) find = Stream.fold Fold.find
Since: 0.5.0
stripPrefix :: (Eq a, IsStream t, Monad m) => t m a -> t m a -> m (Maybe (t m a)) Source #
stripPrefix prefix stream strips prefix from stream if it is a
prefix of stream. Returns Nothing if the stream does not start with the
given prefix, stripped stream otherwise. Returns Just nil when the prefix
is the same as the stream.
See also "Streamly.Internal.Data.Stream.IsStream.Nesting.dropPrefix".
Space: O(1)
Since: 0.6.0
elemIndex :: (Monad m, Eq a) => a -> SerialT m a -> m (Maybe Int) Source #
Returns the first index where a given value is found in the stream.
elemIndex a = Stream.findIndex (== a)
Since: 0.5.0
findIndex :: Monad m => (a -> Bool) -> SerialT m a -> m (Maybe Int) Source #
Returns the first index that satisfies the given predicate.
findIndex = Stream.fold Fold.findIndex
Since: 0.5.0
isPrefixOf :: (Eq a, IsStream t, Monad m) => t m a -> t m a -> m Bool Source #
Returns True if the first stream is the same as or a prefix of the
second. A stream is a prefix of itself.
>>>Stream.isPrefixOf (Stream.fromList "hello") (Stream.fromList "hello" :: SerialT IO Char)True
Since: 0.6.0
isSuffixOf :: (Monad m, Eq a) => SerialT m a -> SerialT m a -> m Bool Source #
Returns True if the first stream is a suffix of the second. A stream is
considered a suffix of itself.
>>>Stream.isSuffixOf (Stream.fromList "hello") (Stream.fromList "hello" :: SerialT IO Char)True
Space: O(n), buffers entire input stream and the suffix.
Pre-release
Suboptimal - Help wanted.
isInfixOf :: (MonadIO m, Eq a, Enum a, Storable a, Unbox a) => SerialT m a -> SerialT m a -> m Bool Source #
isSubsequenceOf :: (Eq a, IsStream t, Monad m) => t m a -> t m a -> m Bool Source #
Returns True if all the elements of the first stream occur, in order, in
the second stream. The elements do not have to occur consecutively. A stream
is a subsequence of itself.
>>>Stream.isSubsequenceOf (Stream.fromList "hlo") (Stream.fromList "hello" :: SerialT IO Char)True
Since: 0.6.0
the :: (Eq a, Monad m) => SerialT m a -> m (Maybe a) Source #
Ensures that all the elements of the stream are identical and then returns that unique element.
Since: 0.6.0
stripSuffix :: (Monad m, Eq a) => SerialT m a -> SerialT m a -> m (Maybe (SerialT m a)) Source #
Drops the given suffix from a stream. Returns Nothing if the stream does
not end with the given suffix. Returns Just nil when the suffix is the
same as the stream.
It may be more efficient to convert the stream to an Array and use stripSuffix on that especially if the elements have a Storable or Prim instance.
See also "Streamly.Internal.Data.Stream.IsStream.Nesting.dropSuffix".
Space: O(n), buffers the entire input stream as well as the suffix
Pre-release
drain :: Monad m => SerialT m a -> m () Source #
drain = mapM_ (\_ -> return ()) drain = Stream.fold Fold.drain
Run a stream, discarding the results. By default it interprets the stream
as SerialT, to run other types of streams use the type adapting
combinators for example Stream.drain . .fromAsync
Since: 0.7.0
foldlS :: IsStream t => (t m b -> a -> t m b) -> t m b -> t m a -> t m b Source #
Lazy left fold to a stream.
foldlT :: (Monad m, IsStream t, Monad (s m), MonadTrans s) => (s m b -> a -> s m b) -> s m b -> t m a -> s m b Source #
Lazy left fold to a transformer monad.
For example, to reverse a stream:
D.toList $ D.foldlT (flip D.cons) D.nil $ (D.fromList [1..5] :: SerialT IO Int)
eqBy :: (IsStream t, Monad m) => (a -> b -> Bool) -> t m a -> t m b -> m Bool Source #
Compare two streams for equality using an equality function.
Since: 0.6.0
cmpBy :: (IsStream t, Monad m) => (a -> b -> Ordering) -> t m a -> t m b -> m Ordering Source #
Compare two streams lexicographically using a comparison function.
Since: 0.6.0
parse :: Monad m => Parser a m b -> SerialT m a -> m (Either ParseError b) Source #
Parse a stream using the supplied Parser.
Unlike folds, parsers may not always result in a valid output, they may result in an error. For example:
>>>Stream.parse (Parser.takeEQ 1 Fold.drain) Stream.nilLeft (ParseError "takeEQ: Expecting exactly 1 elements, input terminated on 0")
Note:
fold f = Stream.parse (Parser.fromFold f)
parse p is not the same as head . parseMany p on an empty stream.
Pre-release
toStreamRev :: Monad m => SerialT m a -> m (SerialT n a) Source #
Convert a stream to a pure stream in reverse order.
toStreamRev = Stream.foldl' (flip Stream.cons) Stream.nil
Pre-release
toListRev :: Monad m => SerialT m a -> m [a] Source #
toListRev = Stream.foldl' (flip (:)) []
Convert a stream into a list in reverse order in the underlying monad.
Warning! working on large lists accumulated as buffers in memory could be very inefficient, consider using Streamly.Array instead.
Pre-release
drainN :: Monad m => Int -> SerialT m a -> m () Source #
drainN n = Stream.drain . Stream.take n drainN n = Stream.fold (Fold.take n Fold.drain)
Run maximum up to n iterations of a stream.
Since: 0.7.0
findM :: Monad m => (a -> m Bool) -> SerialT m a -> m (Maybe a) Source #
Returns the first element that satisfies the given predicate.
findM = Stream.fold Fold.findM
Since: 0.6.0
parseD :: Monad m => Parser a m b -> SerialT m a -> m (Either ParseError b) Source #
Parse a stream using the supplied ParserD Parser.
Internal
headElse :: Monad m => a -> SerialT m a -> m a Source #
Extract the first element of the stream, if any, otherwise use the supplied default value. It can help avoid one branch in high performance code.
Pre-release
drainWhile :: Monad m => (a -> Bool) -> SerialT m a -> m () Source #
drainWhile p = Stream.drain . Stream.takeWhile p
Run a stream as long as the predicate holds true.
Since: 0.7.0
(|$.) :: (IsStream t, MonadAsync m) => (t m a -> m b) -> t m a -> m b infixr 0 Source #
Parallel fold application operator; applies a fold function t m a -> m b
to a stream t m a concurrently; The the input stream is evaluated
asynchronously in an independent thread yielding elements to a buffer and
the folding action runs in another thread consuming the input from the
buffer.
If you read the signature as (t m a -> m b) -> (t m a -> m b) you can look
at it as a transformation that converts a fold function to a buffered
concurrent fold function.
The . at the end of the operator is a mnemonic for termination of the
stream.
In the example below, each stage introduces a delay of 1 sec but output is printed every second because both stages are concurrent.
>>>import Control.Concurrent (threadDelay)>>>import Streamly.Prelude ((|$.))>>>:{Stream.foldlM' (\_ a -> threadDelay 1000000 >> print a) (return ()) |$. Stream.replicateM 3 (threadDelay 1000000 >> return 1) :} 1 1 1
Concurrent
Since: 0.3.0 (Streamly)
Since: 0.8.0
(|&.) :: (IsStream t, MonadAsync m) => t m a -> (t m a -> m b) -> m b infixl 1 Source #
foldx :: Monad m => (x -> a -> x) -> x -> (x -> b) -> SerialT m a -> m b Source #
Strict left fold with an extraction function. Like the standard strict
left fold, but applies a user supplied extraction function (the third
argument) to the folded value at the end. This is designed to work with the
foldl library. The suffix x is a mnemonic for extraction.
Since: 0.2.0
foldxM :: Monad m => (x -> a -> m x) -> m x -> (x -> m b) -> SerialT m a -> m b Source #
Like foldx, but with a monadic step function.
Since: 0.2.0
runStream :: Monad m => SerialT m a -> m () Source #
Run a stream, discarding the results. By default it interprets the stream
as SerialT, to run other types of streams use the type adapting
combinators for example runStream . .fromAsync
Since: 0.2.0
runN :: Monad m => Int -> SerialT m a -> m () Source #
runN n = runStream . take n
Run maximum up to n iterations of a stream.
Since: 0.6.0
runWhile :: Monad m => (a -> Bool) -> SerialT m a -> m () Source #
runWhile p = runStream . takeWhile p
Run a stream as long as the predicate holds true.
Since: 0.6.0
toHandle :: MonadIO m => Handle -> SerialT m String -> m () Source #
toHandle h = D.mapM_ $ hPutStrLn h
Write a stream of Strings to an IO Handle.
Since: 0.1.0
foldAsync :: (IsStream t, MonadAsync m) => (t m a -> m b) -> t m a -> m b Source #
Same as |$..
Internal
Piping
Pass through a Pipe.
transform :: (IsStream t, Monad m) => Pipe m a b -> t m a -> t m b Source #
Use a Pipe to transform a stream.
Pre-release
Folding
foldrS :: IsStream t => (a -> t m b -> t m b) -> t m b -> t m a -> t m b Source #
Right fold to a streaming monad.
foldrS Stream.cons Stream.nil === id
foldrS can be used to perform stateless stream to stream transformations
like map and filter in general. It can be coupled with a scan to perform
stateful transformations. However, note that the custom map and filter
routines can be much more efficient than this due to better stream fusion.
>>>Stream.toList $ Stream.foldrS Stream.cons Stream.nil $ Stream.fromList [1..5][1,2,3,4,5]
Find if any element in the stream is True:
>>>Stream.toList $ Stream.foldrS (\x xs -> if odd x then (Stream.fromPure True) else xs) (Stream.fromPure False) $ (Stream.fromList (2:4:5:undefined) :: Stream.SerialT IO Int)[True]
Map (+2) on odd elements and filter out the even elements:
>>>Stream.toList $ Stream.foldrS (\x xs -> if odd x then (x + 2) `Stream.cons` xs else xs) Stream.nil $ (Stream.fromList [1..5] :: Stream.SerialT IO Int)[3,5,7]
foldrM can also be represented in terms of foldrS, however, the former
is much more efficient:
foldrM f z s = runIdentityT $ foldrS (\x xs -> lift $ f x (runIdentityT xs)) (lift z) s
Pre-release
foldrSShared :: IsStream t => (a -> t m b -> t m b) -> t m b -> t m a -> t m b Source #
foldrT :: (IsStream t, Monad m, Monad (s m), MonadTrans s) => (a -> s m b -> s m b) -> s m b -> t m a -> s m b Source #
Right fold to a transformer monad. This is the most general right fold
function. foldrS is a special case of foldrT, however foldrS
implementation can be more efficient:
foldrS = foldrT foldrM f z s = runIdentityT $ foldrT (\x xs -> lift $ f x (runIdentityT xs)) (lift z) s
foldrT can be used to translate streamly streams to other transformer
monads e.g. to a different streaming type.
Pre-release
Mapping
Stateless one-to-one maps.
sequence :: (IsStream t, MonadAsync m) => t m (m a) -> t m a Source #
sequence = mapM id
Replace the elements of a stream of monadic actions with the outputs of those actions.
>>> drain $ Stream.sequence $ Stream.fromList [putStr "a", putStr "b", putStrLn "c"]
abc
>>> :{
drain $ Stream.replicateM 3 (return $ threadDelay 1000000 >> print 1)
& (fromSerial . Stream.sequence)
:}
1
1
1
>>> :{
drain $ Stream.replicateM 3 (return $ threadDelay 1000000 >> print 1)
& (fromAsync . Stream.sequence)
:}
1
1
1
Concurrent (do not use with fromParallel on infinite streams)
Since: 0.1.0
mapM :: forall t m a b. (IsStream t, MonadAsync m) => (a -> m b) -> t m a -> t m b Source #
mapM f = sequence . map f
Apply a monadic function to each element of the stream and replace it with the output of the resulting action.
>>> drain $ Stream.mapM putStr $ Stream.fromList ["a", "b", "c"]
abc
>>> :{
drain $ Stream.replicateM 10 (return 1)
& (fromSerial . Stream.mapM (x -> threadDelay 1000000 >> print x))
:}
1
...
1
> drain $ Stream.replicateM 10 (return 1)
& (fromAsync . Stream.mapM (x -> threadDelay 1000000 >> print x))
Concurrent (do not use with fromParallel on infinite streams)
Since: 0.1.0
smapM :: (IsStream t, Monad m) => (s -> a -> m (s, b)) -> m s -> t m a -> t m b Source #
A stateful mapM, equivalent to a left scan, more like mapAccumL.
Hopefully, this is a better alternative to scan. Separation of state from
the output makes it easier to think in terms of a shared state, and also
makes it easier to keep the state fully strict and the output lazy.
See also: scanlM'
Pre-release
Mapping Side Effects (Observation)
See also the intersperse*_ combinators.
trace :: (IsStream t, MonadAsync m) => (a -> m b) -> t m a -> t m a Source #
Apply a monadic function to each element flowing through the stream and discard the results.
>>>Stream.drain $ Stream.trace print (Stream.enumerateFromTo 1 2)1 2
Compare with tap.
Since: 0.7.0
trace_ :: (IsStream t, Monad m) => m b -> t m a -> t m a Source #
Perform a side effect before yielding each element of the stream and discard the results.
>>> Stream.drain $ Stream.trace_ (print "got here") (Stream.enumerateFromTo 1 2) "got here" "got here"
Same as intersperseMPrefix_ but always serial.
See also: trace
Pre-release
tap :: (IsStream t, Monad m) => Fold m a b -> t m a -> t m a Source #
Tap the data flowing through a stream into a Fold. For example, you may
add a tap to log the contents flowing through the stream. The fold is used
only for effects, its result is discarded.
Fold m a b
|
-----stream m a ---------------stream m a-----
>>>Stream.drain $ Stream.tap (Fold.drainBy print) (Stream.enumerateFromTo 1 2)1 2
Compare with trace.
Since: 0.7.0
tapOffsetEvery :: (IsStream t, Monad m) => Int -> Int -> Fold m a b -> t m a -> t m a Source #
tapOffsetEvery offset n taps every nth element in the stream
starting at offset. offset can be between 0 and n - 1. Offset 0
means start at the first element in the stream. If the offset is outside
this range then offset is used as offset.mod n
>>>Stream.drain $ Stream.tapOffsetEvery 0 2 (Fold.rmapM print Fold.toList) $ Stream.enumerateFromTo 0 10[0,2,4,6,8,10]
tapAsync :: (IsStream t, MonadAsync m) => Fold m a b -> t m a -> t m a Source #
Redirect a copy of the stream to a supplied fold and run it concurrently
in an independent thread. The fold may buffer some elements. The buffer size
is determined by the prevailing maxBuffer setting.
Stream m a -> m b
|
-----stream m a ---------------stream m a-----
>>> Stream.drain $ Stream.tapAsync (Fold.drainBy print) (Stream.enumerateFromTo 1 2) 1 2
Exceptions from the concurrently running fold are propagated to the current computation. Note that, because of buffering in the fold, exceptions may be delayed and may not correspond to the current element being processed in the parent stream, but we guarantee that before the parent stream stops the tap finishes and all exceptions from it are drained.
>>>tapAsync f = Stream.tapAsyncK (Stream.fold f . Stream.adapt)
Compare with tap.
Pre-release
tapAsyncK :: (IsStream t, MonadAsync m) => (t m a -> m b) -> t m a -> t m a Source #
Like tapAsyncF but uses a stream fold function instead of a Fold type.
Pre-release
distributeAsync_ :: (Foldable f, IsStream t, MonadAsync m) => f (t m a -> m b) -> t m a -> t m a Source #
Concurrently distribute a stream to a collection of fold functions, discarding the outputs of the folds.
> Stream.drain $ Stream.distributeAsync_ [Stream.mapM_ print, Stream.mapM_ print] (Stream.enumerateFromTo 1 2) 1 2 1 2
distributeAsync_ = flip (foldr tapAsync)
Pre-release
pollCounts :: (IsStream t, MonadAsync m) => (a -> Bool) -> (t m Int -> m b) -> t m a -> t m a Source #
pollCounts predicate transform fold stream counts those elements in the
stream that pass the predicate. The resulting count stream is sent to
another thread which transforms it using transform and then folds it using
fold. The thread is automatically cleaned up if the stream stops or
aborts due to exception.
For example, to print the count of elements processed every second:
> Stream.drain $ Stream.pollCounts (const True) (Stream.rollingMap (-) . Stream.delayPost 1) (FLold.drainBy print)
$ Stream.enumerateFrom 0
Note: This may not work correctly on 32-bit machines.
Pre-release
Scanning By Fold
scan :: (IsStream t, Monad m) => Fold m a b -> t m a -> t m b Source #
Scan a stream using the given monadic fold.
>>>Stream.toList $ Stream.takeWhile (< 10) $ Stream.scan Fold.sum (Stream.fromList [1..10])[0,1,3,6]
Since: 0.7.0
scanMany :: (IsStream t, Monad m) => Fold m a b -> t m a -> t m b Source #
Like scan but restarts scanning afresh when the scanning fold
terminates.
Pre-release
postscan :: (IsStream t, Monad m) => Fold m a b -> t m a -> t m b Source #
Postscan a stream using the given monadic fold.
The following example extracts the input stream up to a point where the running average of elements is no more than 10:
>>>import Data.Maybe (fromJust)>>>let avg = Fold.teeWith (/) Fold.sum (fmap fromIntegral Fold.length)>>>:{Stream.toList $ Stream.map (fromJust . fst) $ Stream.takeWhile (\(_,x) -> x <= 10) $ Stream.postscan (Fold.tee Fold.last avg) (Stream.enumerateFromTo 1.0 100.0) :} [1.0,2.0,3.0,4.0,5.0,6.0,7.0,8.0,9.0,10.0,11.0,12.0,13.0,14.0,15.0,16.0,17.0,18.0,19.0]
Since: 0.7.0
Scanning
Left scans. Stateful, mostly one-to-one maps.
scanl' :: (IsStream t, Monad m) => (b -> a -> b) -> b -> t m a -> t m b Source #
Strict left scan. Like map, scanl' too is a one to one transformation,
however it adds an extra element.
>>> Stream.toList $ Stream.scanl' (+) 0 $ fromList [1,2,3,4] [0,1,3,6,10]
>>> Stream.toList $ Stream.scanl' (flip (:)) [] $ Stream.fromList [1,2,3,4] [[],[1],[2,1],[3,2,1],[4,3,2,1]]
The output of scanl' is the initial value of the accumulator followed by
all the intermediate steps and the final result of foldl'.
By streaming the accumulated state after each fold step, we can share the state across multiple stages of stream composition. Each stage can modify or extend the state, do some processing with it and emit it for the next stage, thus modularizing the stream processing. This can be useful in stateful or event-driven programming.
Consider the following monolithic example, computing the sum and the product
of the elements in a stream in one go using a foldl':
>>> Stream.foldl' ((s, p) x -> (s + x, p * x)) (0,1) $ Stream.fromList 1,2,3,4
Using scanl' we can make it modular by computing the sum in the first
stage and passing it down to the next stage for computing the product:
>>> :{
Stream.foldl' ((_, p) (s, x) -> (s, p * x)) (0,1)
$ Stream.scanl' ((s, _) x -> (s + x, x)) (0,1)
$ Stream.fromList [1,2,3,4]
:}
(10,24)
IMPORTANT: scanl' evaluates the accumulator to WHNF. To avoid building
lazy expressions inside the accumulator, it is recommended that a strict
data structure is used for accumulator.
>>>scanl' step z = scan (Fold.foldl' step z)>>>scanl' f z xs = scanlM' (\a b -> return (f a b)) (return z) xs>>>scanl' f z xs = z `Stream.cons` postscanl' f z xs
See also: usingStateT
Since: 0.2.0
scanlM' :: (IsStream t, Monad m) => (b -> a -> m b) -> m b -> t m a -> t m b Source #
Like scanl' but with a monadic step function and a monadic seed.
Since: 0.4.0
Since: 0.8.0 (signature change)
scanlMAfter' :: (IsStream t, Monad m) => (b -> a -> m b) -> m b -> (b -> m b) -> t m a -> t m b Source #
scanlMAfter' accumulate initial done stream is like scanlM' except
that it provides an additional done function to be applied on the
accumulator when the stream stops. The result of done is also emitted in
the stream.
This function can be used to allocate a resource in the beginning of the scan and release it when the stream ends or to flush the internal state of the scan at the end.
Pre-release
postscanlMAfter' :: (IsStream t, Monad m) => (b -> a -> m b) -> m b -> (b -> m b) -> t m a -> t m b Source #
postscanl' :: (IsStream t, Monad m) => (b -> a -> b) -> b -> t m a -> t m b Source #
Like scanl' but does not stream the initial value of the accumulator.
>>>postscanl' step z = postscan (Fold.foldl' step z)>>>postscanl' f z = postscanlM' (\a b -> return (f a b)) (return z)>>>postscanl' f z xs = Stream.drop 1 $ Stream.scanl' f z xs
Since: 0.7.0
postscanlM' :: (IsStream t, Monad m) => (b -> a -> m b) -> m b -> t m a -> t m b Source #
Like postscanl' but with a monadic step function and a monadic seed.
>>>postscanlM' f z xs = Stream.drop 1 $ Stream.scanlM' f z xs
Since: 0.7.0
Since: 0.8.0 (signature change)
prescanl' :: (IsStream t, Monad m) => (b -> a -> b) -> b -> t m a -> t m b Source #
Like scanl' but does not stream the final value of the accumulator.
Pre-release
prescanlM' :: (IsStream t, Monad m) => (b -> a -> m b) -> m b -> t m a -> t m b Source #
Like prescanl' but with a monadic step function and a monadic seed.
Pre-release
scanl1' :: (IsStream t, Monad m) => (a -> a -> a) -> t m a -> t m a Source #
Like scanl' but for a non-empty stream. The first element of the stream
is used as the initial value of the accumulator. Does nothing if the stream
is empty.
>>> Stream.toList $ Stream.scanl1' (+) $ fromList [1,2,3,4] [1,3,6,10]
Since: 0.6.0
scanl1M' :: (IsStream t, Monad m) => (a -> a -> m a) -> t m a -> t m a Source #
Like scanl1' but with a monadic step function.
Since: 0.6.0
Filtering
Produce a subset of the stream using criteria based on the values of the elements. We can use a concatMap and scan for filtering but these combinators are more efficient and convenient.
with :: forall (t :: (Type -> Type) -> Type -> Type) m a b s. Functor (t m) => (t m a -> t m (s, a)) -> (((s, a) -> b) -> t m (s, a) -> t m (s, a)) -> ((s, a) -> b) -> t m a -> t m a Source #
Modify a t m a -> t m a stream transformation that accepts a predicate
(a -> b) to accept ((s, a) -> b) instead, provided a transformation t m
a -> t m (s, a). Convenient to filter with index or time.
filterWithIndex = with indexed filter filterWithAbsTime = with timestamped filter filterWithRelTime = with timeIndexed filter
Pre-release
deleteBy :: (IsStream t, Monad m) => (a -> a -> Bool) -> a -> t m a -> t m a Source #
Deletes the first occurrence of the element in the stream that satisfies the given equality predicate.
>>> Stream.toList $ Stream.deleteBy (==) 3 $ Stream.fromList [1,3,3,5] [1,3,5]
Since: 0.6.0
filter :: (IsStream t, Monad m) => (a -> Bool) -> t m a -> t m a Source #
Include only those elements that pass a predicate.
Since: 0.1.0
filterM :: (IsStream t, Monad m) => (a -> m Bool) -> t m a -> t m a Source #
Same as filter but with a monadic predicate.
Since: 0.4.0
uniq :: (Eq a, IsStream t, Monad m) => t m a -> t m a Source #
Drop repeated elements that are adjacent to each other.
Since: 0.6.0
nubBy :: (a -> a -> Bool) -> t m a -> t m a Source #
Drop repeated elements anywhere in the stream.
Caution: not scalable for infinite streams
See also: nubWindowBy
Unimplemented
prune :: (a -> Bool) -> t m a -> t m a Source #
Strip all leading and trailing occurrences of an element passing a predicate and make all other consecutive occurrences uniq.
prune p = dropWhileAround p $ uniqBy (x y -> p x && p y)
> Stream.prune isSpace (Stream.fromList " hello world! ") "hello world!"
Space: O(1)
Unimplemented
Trimming
Produce a subset of the stream trimmed at ends.
take :: (IsStream t, Monad m) => Int -> t m a -> t m a Source #
Take first n elements from the stream and discard the rest.
Since: 0.1.0
takeLast :: Int -> t m a -> t m a Source #
Take n elements at the end of the stream.
O(n) space, where n is the number elements taken.
Unimplemented
takeLastInterval :: Double -> t m a -> t m a Source #
Take time interval i seconds at the end of the stream.
O(n) space, where n is the number elements taken.
Unimplemented
takeWhile :: (IsStream t, Monad m) => (a -> Bool) -> t m a -> t m a Source #
End the stream as soon as the predicate fails on an element.
Since: 0.1.0
takeWhileM :: (IsStream t, Monad m) => (a -> m Bool) -> t m a -> t m a Source #
Same as takeWhile but with a monadic predicate.
Since: 0.4.0
takeWhileLast :: (a -> Bool) -> t m a -> t m a Source #
Take all consecutive elements at the end of the stream for which the predicate is true.
O(n) space, where n is the number elements taken.
Unimplemented
takeWhileAround :: (a -> Bool) -> t m a -> t m a Source #
Like takeWhile and takeWhileLast combined.
O(n) space, where n is the number elements taken from the end.
Unimplemented
drop :: (IsStream t, Monad m) => Int -> t m a -> t m a Source #
Discard first n elements from the stream and take the rest.
Since: 0.1.0
dropLast :: Int -> t m a -> t m a Source #
Drop n elements at the end of the stream.
O(n) space, where n is the number elements dropped.
Unimplemented
dropLastInterval :: Int -> t m a -> t m a Source #
Drop time interval i seconds at the end of the stream.
O(n) space, where n is the number elements dropped.
Unimplemented
dropWhile :: (IsStream t, Monad m) => (a -> Bool) -> t m a -> t m a Source #
Drop elements in the stream as long as the predicate succeeds and then take the rest of the stream.
Since: 0.1.0
dropWhileM :: (IsStream t, Monad m) => (a -> m Bool) -> t m a -> t m a Source #
Same as dropWhile but with a monadic predicate.
Since: 0.4.0
dropWhileLast :: (a -> Bool) -> t m a -> t m a Source #
Drop all consecutive elements at the end of the stream for which the predicate is true.
O(n) space, where n is the number elements dropped.
Unimplemented
dropWhileAround :: (a -> Bool) -> t m a -> t m a Source #
Like dropWhile and dropWhileLast combined.
O(n) space, where n is the number elements dropped from the end.
Unimplemented
Inserting Elements
Produce a superset of the stream. This is the opposite of filtering/sampling. We can always use concatMap and scan for inserting but these combinators are more efficient and convenient.
intersperse :: (IsStream t, MonadAsync m) => a -> t m a -> t m a Source #
Insert a pure value between successive elements of a stream.
>>>Stream.toList $ Stream.intersperse ',' $ Stream.fromList "hello""h,e,l,l,o"
Since: 0.7.0
intersperseM :: (IsStream t, MonadAsync m) => m a -> t m a -> t m a Source #
Insert an effect and its output before consuming an element of a stream except the first one.
>>>Stream.toList $ Stream.trace putChar $ Stream.intersperseM (putChar '.' >> return ',') $ Stream.fromList "hello"h.,e.,l.,l.,o"h,e,l,l,o"
Be careful about the order of effects. In the above example we used trace after the intersperse, if we use it before the intersperse the output would be he.l.l.o."h,e,l,l,o".
>>>Stream.toList $ Stream.intersperseM (putChar '.' >> return ',') $ Stream.trace putChar $ Stream.fromList "hello"he.l.l.o."h,e,l,l,o"
Since: 0.5.0
intersperseMWith :: Int -> m a -> t m a -> t m a Source #
Intersperse a monadic action into the input stream after every n
elements.
> Stream.toList $ Stream.intersperseMWith 2 (return ',') $ Stream.fromList "hello" "he,ll,o"
Unimplemented
intersperseMSuffix :: (IsStream t, Monad m) => m a -> t m a -> t m a Source #
Insert an effect and its output after consuming an element of a stream.
>>>Stream.toList $ Stream.trace putChar $ intersperseMSuffix (putChar '.' >> return ',') $ Stream.fromList "hello"h.,e.,l.,l.,o.,"h,e,l,l,o,"
Pre-release
intersperseMSuffixWith :: (IsStream t, Monad m) => Int -> m a -> t m a -> t m a Source #
Like intersperseMSuffix but intersperses an effectful action into the
input stream after every n elements and after the last element.
>>>Stream.toList $ Stream.intersperseMSuffixWith 2 (return ',') $ Stream.fromList "hello""he,ll,o,"
Pre-release
interjectSuffix :: (IsStream t, MonadAsync m) => Double -> m a -> t m a -> t m a Source #
Intersperse a monadic action into the input stream after every n
seconds.
> import Control.Concurrent (threadDelay) > Stream.drain $ Stream.interjectSuffix 1 (putChar ',') $ Stream.mapM (x -> threadDelay 1000000 >> putChar x) $ Stream.fromList "hello" h,e,l,l,o
Pre-release
Inserting Side Effects/Time
intersperseM_ :: (IsStream t, Monad m) => m b -> t m a -> t m a Source #
Insert a side effect before consuming an element of a stream except the first one.
>>>Stream.drain $ Stream.trace putChar $ Stream.intersperseM_ (putChar '.') $ Stream.fromList "hello"h.e.l.l.o
Pre-release
delay :: (IsStream t, MonadIO m) => Double -> t m a -> t m a Source #
Introduce a delay of specified seconds before consuming an element of the stream except the first one.
>>>Stream.mapM_ print $ Stream.timestamped $ Stream.delay 1 $ Stream.enumerateFromTo 1 3(AbsTime (TimeSpec {sec = ..., nsec = ...}),1) (AbsTime (TimeSpec {sec = ..., nsec = ...}),2) (AbsTime (TimeSpec {sec = ..., nsec = ...}),3)
Since: 0.8.0
intersperseMSuffix_ :: (IsStream t, Monad m) => m b -> t m a -> t m a Source #
Insert a side effect after consuming an element of a stream.
>>> Stream.mapM_ putChar $ Stream.intersperseMSuffix_ (threadDelay 1000000) $ Stream.fromList "hello" hello
Pre-release
delayPost :: (IsStream t, MonadIO m) => Double -> t m a -> t m a Source #
Introduce a delay of specified seconds after consuming an element of a stream.
>>>Stream.mapM_ print $ Stream.timestamped $ Stream.delayPost 1 $ Stream.enumerateFromTo 1 3(AbsTime (TimeSpec {sec = ..., nsec = ...}),1) (AbsTime (TimeSpec {sec = ..., nsec = ...}),2) (AbsTime (TimeSpec {sec = ..., nsec = ...}),3)
Pre-release
intersperseMPrefix_ :: (IsStream t, MonadAsync m) => m b -> t m a -> t m a Source #
Insert a side effect before consuming an element of a stream.
>>>Stream.toList $ Stream.trace putChar $ Stream.intersperseMPrefix_ (putChar '.' >> return ',') $ Stream.fromList "hello".h.e.l.l.o"hello"
Same as trace_ but may be concurrent.
Concurrent
Pre-release
delayPre :: (IsStream t, MonadIO m) => Double -> t m a -> t m a Source #
Introduce a delay of specified seconds before consuming an element of a stream.
>>>Stream.mapM_ print $ Stream.timestamped $ Stream.delayPre 1 $ Stream.enumerateFromTo 1 3(AbsTime (TimeSpec {sec = ..., nsec = ...}),1) (AbsTime (TimeSpec {sec = ..., nsec = ...}),2) (AbsTime (TimeSpec {sec = ..., nsec = ...}),3)
Pre-release
Element Aware Insertion
Opposite of filtering
insertBy :: (IsStream t, Monad m) => (a -> a -> Ordering) -> a -> t m a -> t m a Source #
insertBy cmp elem stream inserts elem before the first element in
stream that is less than elem when compared using cmp.
insertBy cmp x =mergeBycmp (fromPurex)
>>> Stream.toList $ Stream.insertBy compare 2 $ Stream.fromList [1,3,5] [1,2,3,5]
Since: 0.6.0
Reordering
reverse :: (IsStream t, Monad m) => t m a -> t m a Source #
Returns the elements of the stream in reverse order. The stream must be finite. Note that this necessarily buffers the entire stream in memory.
>>>reverse = Stream.foldlT (flip Stream.cons) Stream.nil
Since 0.7.0 (Monad m constraint)
Since: 0.1.1
reassembleBy :: Fold m a b -> (a -> a -> Int) -> t m a -> t m b Source #
Buffer until the next element in sequence arrives. The function argument determines the difference in sequence numbers. This could be useful in implementing sequenced streams, for example, TCP reassembly.
Unimplemented
Position Indexing
indexed :: (IsStream t, Monad m) => t m a -> t m (Int, a) Source #
indexed = Stream.postscanl' (\(i, _) x -> (i + 1, x)) (-1,undefined) indexed = Stream.zipWith (,) (Stream.enumerateFrom 0)
Pair each element in a stream with its index, starting from index 0.
>>>Stream.toList $ Stream.indexed $ Stream.fromList "hello"[(0,'h'),(1,'e'),(2,'l'),(3,'l'),(4,'o')]
Since: 0.6.0
indexedR :: (IsStream t, Monad m) => Int -> t m a -> t m (Int, a) Source #
indexedR n = Stream.postscanl' (\(i, _) x -> (i - 1, x)) (n + 1,undefined) indexedR n = Stream.zipWith (,) (Stream.enumerateFromThen n (n - 1))
Pair each element in a stream with its index, starting from the
given index n and counting down.
>>>Stream.toList $ Stream.indexedR 10 $ Stream.fromList "hello"[(10,'h'),(9,'e'),(8,'l'),(7,'l'),(6,'o')]
Since: 0.6.0
Time Indexing
timestamped :: (IsStream t, MonadAsync m, Functor (t m)) => t m a -> t m (AbsTime, a) Source #
timestampWith :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m a -> t m (AbsTime, a) Source #
Pair each element in a stream with an absolute timestamp, using a clock of specified granularity. The timestamp is generated just before the element is consumed.
>>>Stream.mapM_ print $ Stream.timestampWith 0.01 $ Stream.delay 1 $ Stream.enumerateFromTo 1 3(AbsTime (TimeSpec {sec = ..., nsec = ...}),1) (AbsTime (TimeSpec {sec = ..., nsec = ...}),2) (AbsTime (TimeSpec {sec = ..., nsec = ...}),3)
Pre-release
timeIndexed :: (IsStream t, MonadAsync m, Functor (t m)) => t m a -> t m (RelTime64, a) Source #
Pair each element in a stream with relative times starting from 0, using a 10 ms granularity clock. The time is measured just before the element is consumed.
>>>Stream.mapM_ print $ Stream.timeIndexed $ Stream.delay 1 $ Stream.enumerateFromTo 1 3(RelTime64 (NanoSecond64 ...),1) (RelTime64 (NanoSecond64 ...),2) (RelTime64 (NanoSecond64 ...),3)
Pre-release
timeIndexWith :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m a -> t m (RelTime64, a) Source #
Pair each element in a stream with relative times starting from 0, using a clock with the specified granularity. The time is measured just before the element is consumed.
>>>Stream.mapM_ print $ Stream.timeIndexWith 0.01 $ Stream.delay 1 $ Stream.enumerateFromTo 1 3(RelTime64 (NanoSecond64 ...),1) (RelTime64 (NanoSecond64 ...),2) (RelTime64 (NanoSecond64 ...),3)
Pre-release
Searching
findIndices :: (IsStream t, Monad m) => (a -> Bool) -> t m a -> t m Int Source #
Find all the indices where the element in the stream satisfies the given predicate.
findIndices = fold Fold.findIndices
Since: 0.5.0
elemIndices :: (IsStream t, Eq a, Monad m) => a -> t m a -> t m Int Source #
Find all the indices where the value of the element in the stream is equal to the given value.
elemIndices a = findIndices (== a)
Since: 0.5.0
Rolling map
Map using the previous element.
rollingMapM :: (IsStream t, Monad m) => (Maybe a -> a -> m b) -> t m a -> t m b Source #
Like rollingMap but with an effectful map function.
Pre-release
rollingMap :: (IsStream t, Monad m) => (Maybe a -> a -> b) -> t m a -> t m b Source #
Apply a function on every two successive elements of a stream. The first
argument of the map function is the previous element and the second argument
is the current element. When the current element is the first element, the
previous element is Nothing.
Pre-release
rollingMap2 :: (IsStream t, Monad m) => (a -> a -> b) -> t m a -> t m b Source #
Like rollingMap but requires at least two elements in the stream,
returns an empty stream otherwise.
This is the stream equivalent of the list idiom zipWith f xs (tail xs).
Pre-release
Maybe Streams
mapMaybeM :: (IsStream t, MonadAsync m, Functor (t m)) => (a -> m (Maybe b)) -> t m a -> t m b Source #
Either Streams
both :: Functor (t m) => t m (Either a a) -> t m a Source #
Remove the either wrapper and flatten both lefts and as well as rights in the output stream.
Pre-release
Concurrent Evaluation
Concurrent Pipelines
Run streaming stages concurrently.
mkAsync :: (IsStream t, MonadAsync m) => t m a -> t m a Source #
Make the stream producer and consumer run concurrently by introducing a buffer between them. The producer thread evaluates the input stream until the buffer fills, it terminates if the buffer is full and a worker thread is kicked off again to evaluate the remaining stream when there is space in the buffer. The consumer consumes the stream lazily from the buffer.
Since: 0.2.0 (Streamly)
Since: 0.8.0
mkParallel :: (IsStream t, MonadAsync m) => t m a -> t m a Source #
Make the stream producer and consumer run concurrently by introducing a buffer between them. The producer thread evaluates the input stream until the buffer fills, it blocks if the buffer is full until there is space in the buffer. The consumer consumes the stream lazily from the buffer.
mkParallel = IsStream.fromStreamD . mkParallelD . IsStream.toStreamD
Pre-release
applyAsync :: (IsStream t, MonadAsync m) => (t m a -> t m b) -> t m a -> t m b Source #
Same as |$.
Internal
(|$) :: (IsStream t, MonadAsync m) => (t m a -> t m b) -> t m a -> t m b infixr 0 Source #
Parallel transform application operator; applies a stream transformation
function t m a -> t m b to a stream t m a concurrently; the input stream
is evaluated asynchronously in an independent thread yielding elements to a
buffer and the transformation function runs in another thread consuming the
input from the buffer. |$ is just like regular function application
operator $ except that it is concurrent.
If you read the signature as (t m a -> t m b) -> (t m a -> t m b) you can
look at it as a transformation that converts a transform function to a
buffered concurrent transform function.
The following code prints a value every second even though each stage adds a 1 second delay.
>>>:{Stream.drain $ Stream.mapM (\x -> threadDelay 1000000 >> print x) |$ Stream.replicateM 3 (threadDelay 1000000 >> return 1) :} 1 1 1
Concurrent
Since: 0.3.0 (Streamly)
Since: 0.8.0
(|&) :: (IsStream t, MonadAsync m) => t m a -> (t m a -> t m b) -> t m b infixl 1 Source #
Concurrency Control
maxThreads :: IsStream t => Int -> t m a -> t m a Source #
Specify the maximum number of threads that can be spawned concurrently for
any concurrent combinator in a stream.
A value of 0 resets the thread limit to default, a negative value means
there is no limit. The default value is 1500. maxThreads does not affect
ParallelT streams as they can use unbounded number of threads.
When the actions in a stream are IO bound, having blocking IO calls, this option can be used to control the maximum number of in-flight IO requests. When the actions are CPU bound this option can be used to control the amount of CPU used by the stream.
Since: 0.4.0 (Streamly)
Since: 0.8.0
Buffering and Sampling
Evaluate strictly using a buffer of results. When the buffer becomes full we can block, drop the new elements, drop the oldest element and insert the new at the end or keep dropping elements uniformly to match the rate of the consumer.
maxBuffer :: IsStream t => Int -> t m a -> t m a Source #
Specify the maximum size of the buffer for storing the results from concurrent computations. If the buffer becomes full we stop spawning more concurrent tasks until there is space in the buffer. A value of 0 resets the buffer size to default, a negative value means there is no limit. The default value is 1500.
CAUTION! using an unbounded maxBuffer value (i.e. a negative value)
coupled with an unbounded maxThreads value is a recipe for disaster in
presence of infinite streams, or very large streams. Especially, it must
not be used when pure is used in ZipAsyncM streams as pure in
applicative zip streams generates an infinite stream causing unbounded
concurrent generation with no limit on the buffer or threads.
Since: 0.4.0 (Streamly)
Since: 0.8.0
sampleOld :: Int -> t m a -> t m a Source #
Evaluate the input stream continuously and keep only the oldest n
elements in the buffer, discard the new ones when the buffer is full. When
the output stream is evaluated it consumes the values from the buffer in a
FIFO manner.
Unimplemented
sampleNew :: Int -> t m a -> t m a Source #
Evaluate the input stream continuously and keep only the latest n
elements in a ring buffer, keep discarding the older ones to make space for
the new ones. When the output stream is evaluated it consumes the values
from the buffer in a FIFO manner.
Unimplemented
sampleRate :: Double -> t m a -> t m a Source #
Rate Limiting
Evaluate the stream at uniform intervals to maintain a specified evaluation rate.
Specifies the stream yield rate in yields per second (Hertz).
We keep accumulating yield credits at rateGoal. At any point of time we
allow only as many yields as we have accumulated as per rateGoal since the
start of time. If the consumer or the producer is slower or faster, the
actual rate may fall behind or exceed rateGoal. We try to recover the gap
between the two by increasing or decreasing the pull rate from the producer.
However, if the gap becomes more than rateBuffer we try to recover only as
much as rateBuffer.
rateLow puts a bound on how low the instantaneous rate can go when
recovering the rate gap. In other words, it determines the maximum yield
latency. Similarly, rateHigh puts a bound on how high the instantaneous
rate can go when recovering the rate gap. In other words, it determines the
minimum yield latency. We reduce the latency by increasing concurrency,
therefore we can say that it puts an upper bound on concurrency.
If the rateGoal is 0 or negative the stream never yields a value.
If the rateBuffer is 0 or negative we do not attempt to recover.
Since: 0.5.0 (Streamly)
Since: streamly-core-0.8.0
rate :: IsStream t => Maybe Rate -> t m a -> t m a Source #
Specify the pull rate of a stream.
A Nothing value resets the rate to default which is unlimited. When the
rate is specified, concurrent production may be ramped up or down
automatically to achieve the specified yield rate. The specific behavior for
different styles of Rate specifications is documented under Rate. The
effective maximum production rate achieved by a stream is governed by:
- The
maxThreadslimit - The
maxBufferlimit - The maximum rate that the stream producer can achieve
- The maximum rate that the stream consumer can achieve
Since: 0.5.0 (Streamly)
Since: 0.8.0
avgRate :: IsStream t => Double -> t m a -> t m a Source #
Same as rate (Just $ Rate (r/2) r (2*r) maxBound)
Specifies the average production rate of a stream in number of yields
per second (i.e. Hertz). Concurrent production is ramped up or down
automatically to achieve the specified average yield rate. The rate can
go down to half of the specified rate on the lower side and double of
the specified rate on the higher side.
Since: 0.5.0 (Streamly)
Since: 0.8.0
minRate :: IsStream t => Double -> t m a -> t m a Source #
Same as rate (Just $ Rate r r (2*r) maxBound)
Specifies the minimum rate at which the stream should yield values. As far as possible the yield rate would never be allowed to go below the specified rate, even though it may possibly go above it at times, the upper limit is double of the specified rate.
Since: 0.5.0 (Streamly)
Since: 0.8.0
maxRate :: IsStream t => Double -> t m a -> t m a Source #
Same as rate (Just $ Rate (r/2) r r maxBound)
Specifies the maximum rate at which the stream should yield values. As far as possible the yield rate would never be allowed to go above the specified rate, even though it may possibly go below it at times, the lower limit is half of the specified rate. This can be useful in applications where certain resource usage must not be allowed to go beyond certain limits.
Since: 0.5.0 (Streamly)
Since: 0.8.0
constRate :: IsStream t => Double -> t m a -> t m a Source #
Same as rate (Just $ Rate r r r 0)
Specifies a constant yield rate. If for some reason the actual rate goes above or below the specified rate we do not try to recover it by increasing or decreasing the rate in future. This can be useful in applications like graphics frame refresh where we need to maintain a constant refresh rate.
Since: 0.5.0 (Streamly)
Since: 0.8.0
Diagnostics
inspectMode :: IsStream t => t m a -> t m a Source #
Print debug information about an SVar when the stream ends
Pre-release
Deprecated
scanx :: (IsStream t, Monad m) => (x -> a -> x) -> x -> (x -> b) -> t m a -> t m b Source #
Strict left scan with an extraction function. Like scanl', but applies a
user supplied extraction function (the third argument) at each step. This is
designed to work with the foldl library. The suffix x is a mnemonic for
extraction.
Since 0.2.0
Since: 0.7.0 (Monad m constraint)
Binary Combinators (Linear)
Functions ending in the shape:
t m a -> t m a -> t m a.
The functions in this section have a linear or flat n-ary combining
characterstics. It means that when combined n times (e.g. a ) the resulting expression will have an serial
b serial c ...O(n)
complexity (instead O(n^2) for pair wise combinators described in the
next section. These functions can be used efficiently with
concatMapWith et. al. combinators that combine streams in a linear
fashion (contrast with concatPairsWith which combines streams as a
binary tree).
serial :: IsStream t => t m a -> t m a -> t m a infixr 6 Source #
Appends two streams sequentially, yielding all elements from the first stream, and then all elements from the second stream.
>>>import Streamly.Prelude (serial)>>>stream1 = Stream.fromList [1,2]>>>stream2 = Stream.fromList [3,4]>>>Stream.toList $ stream1 `serial` stream2[1,2,3,4]
This operation can be used to fold an infinite lazy container of streams.
Since: 0.2.0 (Streamly)
Since: 0.8.0
ahead :: (IsStream t, MonadAsync m) => t m a -> t m a -> t m a infixr 6 Source #
Appends two streams, both the streams may be evaluated concurrently but the outputs are used in the same order as the corresponding actions in the original streams, side effects will happen in the order in which the streams are evaluated:
>>>import Streamly.Prelude (ahead, SerialT)>>>stream1 = Stream.fromEffect (delay 4) :: SerialT IO Int>>>stream2 = Stream.fromEffect (delay 2) :: SerialT IO Int>>>Stream.toList $ stream1 `ahead` stream2 :: IO [Int]2 sec 4 sec [4,2]
Multiple streams can be combined. With enough threads, all of them can be scheduled simultaneously:
>>>stream3 = Stream.fromEffect (delay 1)>>>Stream.toList $ stream1 `ahead` stream2 `ahead` stream31 sec 2 sec 4 sec [4,2,1]
With 2 threads, only two can be scheduled at a time, when one of those finishes, the third one gets scheduled:
>>>Stream.toList $ Stream.maxThreads 2 $ stream1 `ahead` stream2 `ahead` stream32 sec 1 sec 4 sec [4,2,1]
Only streams are scheduled for ahead evaluation, how actions within a stream
are evaluated depends on the stream type. If it is a concurrent stream they
will be evaluated concurrently. It may not make much sense combining serial
streams using ahead.
ahead can be safely used to fold an infinite lazy container of streams.
Since: 0.3.0 (Streamly)
Since: 0.8.0
async :: (IsStream t, MonadAsync m) => t m a -> t m a -> t m a infixr 6 Source #
Merges two streams, both the streams may be evaluated concurrently, outputs from both are used as they arrive:
>>>import Streamly.Prelude (async)>>>stream1 = Stream.fromEffect (delay 4)>>>stream2 = Stream.fromEffect (delay 2)>>>Stream.toList $ stream1 `async` stream22 sec 4 sec [2,4]
Multiple streams can be combined. With enough threads, all of them can be scheduled simultaneously:
>>>stream3 = Stream.fromEffect (delay 1)>>>Stream.toList $ stream1 `async` stream2 `async` stream3... [1,2,4]
With 2 threads, only two can be scheduled at a time, when one of those finishes, the third one gets scheduled:
>>>Stream.toList $ Stream.maxThreads 2 $ stream1 `async` stream2 `async` stream3... [2,1,4]
With a single thread, it becomes serial:
>>>Stream.toList $ Stream.maxThreads 1 $ stream1 `async` stream2 `async` stream3... [4,2,1]
Only streams are scheduled for async evaluation, how actions within a stream are evaluated depends on the stream type. If it is a concurrent stream they will be evaluated concurrently.
In the following example, both the streams are scheduled for concurrent evaluation but each individual stream is evaluated serially:
>>>stream1 = Stream.fromListM $ Prelude.map delay [3,3] -- SerialT IO Int>>>stream2 = Stream.fromListM $ Prelude.map delay [1,1] -- SerialT IO Int>>>Stream.toList $ stream1 `async` stream2 -- IO [Int]... [1,1,3,3]
If total threads are 2, the third stream is scheduled only after one of the first two has finished:
stream3 = Stream.fromListM $ Prelude.map delay [2,2] -- SerialT IO Int Stream.toList $ Stream.maxThreads 2 $ stream1 `async` stream2 `async` stream3 -- IO [Int]
... [1,1,3,2,3,2]
Thus async goes deep in first few streams rather than going wide in all
streams. It prefers to evaluate the leftmost streams as much as possible.
Because of this behavior, async can be safely used to fold an infinite
lazy container of streams.
Since: 0.2.0 (Streamly)
Since: 0.8.0
wAsync :: (IsStream t, MonadAsync m) => t m a -> t m a -> t m a infixr 6 Source #
For singleton streams, wAsync is the same as async. See async for
singleton stream behavior. For multi-element streams, while async is left
biased i.e. it tries to evaluate the left side stream as much as possible,
wAsync tries to schedule them both fairly. In other words, async goes
deep while wAsync goes wide. However, outputs are always used as they
arrive.
With a single thread, async starts behaving like serial while wAsync
starts behaving like wSerial.
>>>import Streamly.Prelude (async, wAsync)>>>stream1 = Stream.fromList [1,2,3]>>>stream2 = Stream.fromList [4,5,6]>>>Stream.toList $ Stream.fromAsync $ Stream.maxThreads 1 $ stream1 `async` stream2[1,2,3,4,5,6]
>>>Stream.toList $ Stream.fromWAsync $ Stream.maxThreads 1 $ stream1 `wAsync` stream2[1,4,2,5,3,6]
With two threads available, and combining three streams:
>>>stream3 = Stream.fromList [7,8,9]>>>Stream.toList $ Stream.fromAsync $ Stream.maxThreads 2 $ stream1 `async` stream2 `async` stream3[1,2,3,4,5,6,7,8,9]
>>>Stream.toList $ Stream.fromWAsync $ Stream.maxThreads 2 $ stream1 `wAsync` stream2 `wAsync` stream3[1,4,2,7,5,3,8,6,9]
This operation cannot be used to fold an infinite lazy container of streams, because it schedules all the streams in a round robin manner.
Note that WSerialT and single threaded WAsyncT both interleave streams
but the exact scheduling is slightly different in both cases.
Since: 0.2.0 (Streamly)
Since: 0.8.0
parallel :: (IsStream t, MonadAsync m) => t m a -> t m a -> t m a infixr 6 Source #
Like async except that the execution is much more
strict. There is no limit on the number of threads. While
async may not schedule a stream if there is no demand
from the consumer, parallel always evaluates both the streams immediately.
The only limit that applies to parallel is maxBuffer.
Evaluation may block if the output buffer becomes full.
>>>import Streamly.Prelude (parallel)>>>stream = Stream.fromEffect (delay 2) `parallel` Stream.fromEffect (delay 1)>>>Stream.toList stream -- IO [Int]1 sec 2 sec [1,2]
parallel guarantees that all the streams are scheduled for execution
immediately, therefore, we could use things like starting timers inside the
streams and relying on the fact that all timers were started at the same
time.
Unlike async this operation cannot be used to fold an infinite lazy
container of streams, because it schedules all the streams strictly
concurrently.
Since: 0.2.0 (Streamly)
Since: 0.8.0
parallelFst :: (IsStream t, MonadAsync m) => t m a -> t m a -> t m a Source #
Like parallel but stops the output as soon as the first stream stops.
Pre-release
parallelMin :: (IsStream t, MonadAsync m) => t m a -> t m a -> t m a Source #
Like parallel but stops the output as soon as any of the two streams
stops.
Pre-release
Binary Combinators (Pair Wise)
Like the functions in the section above these functions also combine
two streams into a single stream but when used n times linearly they
exhibit O(n^2) complexity. They are best combined in a binary tree
fashion using concatPairsWith giving a n * log n complexity. Avoid
using these with concatMapWith when combining a large or infinite
number of streams.
Append
append :: (IsStream t, Monad m) => t m b -> t m b -> t m b Source #
Append the outputs of two streams, yielding all the elements from the first stream and then yielding all the elements from the second stream.
IMPORTANT NOTE: This could be 100x faster than serial/<> for appending a
few (say 100) streams because it can fuse via stream fusion. However, it
does not scale for a large number of streams (say 1000s) and becomes
qudartically slow. Therefore use this for custom appending of a few streams
but use concatMap or 'concatMapWith serial' for appending n streams or
infinite containers of streams.
Pre-release
wSerial
wSerial is a CPS based stream interleaving functions. Use
'concatPairsWith wSerial' to interleave n streams uniformly. It can be
used with concatMapWith as well, however, the interleaving behavior of
n streams would be asymmetric giving exponentially more weightage to
streams that come earlier in the composition.
wSerial :: IsStream t => t m a -> t m a -> t m a infixr 6 Source #
Interleaves two streams, yielding one element from each stream alternately. When one stream stops the rest of the other stream is used in the output stream.
>>>import Streamly.Prelude (wSerial)>>>stream1 = Stream.fromList [1,2]>>>stream2 = Stream.fromList [3,4]>>>Stream.toList $ Stream.fromWSerial $ stream1 `wSerial` stream2[1,3,2,4]
Note, for singleton streams wSerial and serial are identical.
Note that this operation cannot be used to fold a container of infinite streams but it can be used for very large streams as the state that it needs to maintain is proportional to the logarithm of the number of streams.
Since: 0.2.0 (Streamly)
Since: 0.8.0
Interleave
interleave is like wSerial but using a direct style
implementation instead of CPS. It is faster than wSerial due to stream
fusion but has worse efficiency when used with concatMapWith for large
number of streams.
interleave :: (IsStream t, Monad m) => t m b -> t m b -> t m b Source #
Interleaves the outputs of two streams, yielding elements from each stream alternately, starting from the first stream. If any of the streams finishes early the other stream continues alone until it too finishes.
>>>:set -XOverloadedStrings>>>import Data.Functor.Identity (Identity)>>>Stream.interleave "ab" ",,,," :: Stream.SerialT Identity CharfromList "a,b,,,"
>>>Stream.interleave "abcd" ",," :: Stream.SerialT Identity CharfromList "a,b,cd"
interleave is dual to interleaveMin, it can be called interleaveMax.
Do not use at scale in concatMapWith.
Pre-release
interleaveMin :: (IsStream t, Monad m) => t m b -> t m b -> t m b Source #
Interleaves the outputs of two streams, yielding elements from each stream alternately, starting from the first stream. The output stops as soon as any of the two streams finishes, discarding the remaining part of the other stream. The last element of the resulting stream would be from the longer stream.
>>>:set -XOverloadedStrings>>>import Data.Functor.Identity (Identity)>>>Stream.interleaveMin "ab" ",,,," :: Stream.SerialT Identity CharfromList "a,b,">>>Stream.interleaveMin "abcd" ",," :: Stream.SerialT Identity CharfromList "a,b,c"
interleaveMin is dual to interleave.
Do not use at scale in concatMapWith.
Pre-release
interleaveSuffix :: (IsStream t, Monad m) => t m b -> t m b -> t m b Source #
Interleaves the outputs of two streams, yielding elements from each stream alternately, starting from the first stream. As soon as the first stream finishes, the output stops, discarding the remaining part of the second stream. In this case, the last element in the resulting stream would be from the second stream. If the second stream finishes early then the first stream still continues to yield elements until it finishes.
>>>:set -XOverloadedStrings>>>import Data.Functor.Identity (Identity)>>>Stream.interleaveSuffix "abc" ",,,," :: Stream.SerialT Identity CharfromList "a,b,c,">>>Stream.interleaveSuffix "abc" "," :: Stream.SerialT Identity CharfromList "a,bc"
interleaveSuffix is a dual of interleaveInfix.
Do not use at scale in concatMapWith.
Pre-release
interleaveInfix :: (IsStream t, Monad m) => t m b -> t m b -> t m b Source #
Interleaves the outputs of two streams, yielding elements from each stream alternately, starting from the first stream and ending at the first stream. If the second stream is longer than the first, elements from the second stream are infixed with elements from the first stream. If the first stream is longer then it continues yielding elements even after the second stream has finished.
>>>:set -XOverloadedStrings>>>import Data.Functor.Identity (Identity)>>>Stream.interleaveInfix "abc" ",,,," :: Stream.SerialT Identity CharfromList "a,b,c">>>Stream.interleaveInfix "abc" "," :: Stream.SerialT Identity CharfromList "a,bc"
interleaveInfix is a dual of interleaveSuffix.
Do not use at scale in concatMapWith.
Pre-release
Round Robin
roundrobin :: (IsStream t, Monad m) => t m b -> t m b -> t m b Source #
Schedule the execution of two streams in a fair round-robin manner,
executing each stream once, alternately. Execution of a stream may not
necessarily result in an output, a stream may chose to Skip producing an
element until later giving the other stream a chance to run. Therefore, this
combinator fairly interleaves the execution of two streams rather than
fairly interleaving the output of the two streams. This can be useful in
co-operative multitasking without using explicit threads. This can be used
as an alternative to async.
Do not use at scale in concatMapWith.
Pre-release
Zip
zipWith :: (IsStream t, Monad m) => (a -> b -> c) -> t m a -> t m b -> t m c Source #
Stream a is evaluated first, followed by stream b, the resulting
elements a and b are then zipped using the supplied zip function and the
result c is yielded to the consumer.
If stream a or stream b ends, the zipped stream ends. If stream b ends
first, the element a from previous evaluation of stream a is discarded.
> D.toList $ D.zipWith (+) (D.fromList [1,2,3]) (D.fromList [4,5,6]) [5,7,9]
Since: 0.1.0
zipWithM :: (IsStream t, Monad m) => (a -> b -> m c) -> t m a -> t m b -> t m c Source #
Like zipWith but using a monadic zipping function.
Since: 0.4.0
zipAsyncWith :: (IsStream t, MonadAsync m) => (a -> b -> c) -> t m a -> t m b -> t m c Source #
Like zipWith but zips concurrently i.e. both the streams being zipped
are evaluated concurrently using the ParallelT concurrent evaluation
style. The maximum number of elements of each stream evaluated in advance
can be controlled by maxBuffer.
The stream ends if stream a or stream b ends. However, if stream b
ends while we are still evaluating stream a and waiting for a result then
stream will not end until after the evaluation of stream a finishes. This
behavior can potentially be changed in future to end the stream immediately
as soon as any of the stream end is detected.
Since: 0.1.0
zipAsyncWithM :: (IsStream t, MonadAsync m) => (a -> b -> m c) -> t m a -> t m b -> t m c Source #
Like zipAsyncWith but with a monadic zipping function.
Since: 0.4.0
Merge
mergeBy :: IsStream t => (a -> a -> Ordering) -> t m a -> t m a -> t m a Source #
Merge two streams using a comparison function. The head elements of both the streams are compared and the smaller of the two elements is emitted, if both elements are equal then the element from the first stream is used first.
If the streams are sorted in ascending order, the resulting stream would also remain sorted in ascending order.
>>> Stream.toList $ Stream.mergeBy compare (Stream.fromList [1,3,5]) (Stream.fromList [2,4,6,8]) [1,2,3,4,5,6,8]
See also: mergeByMFused
Since: 0.6.0
mergeByM :: (IsStream t, Monad m) => (a -> a -> m Ordering) -> t m a -> t m a -> t m a Source #
Like mergeBy but with a monadic comparison function.
Merge two streams randomly:
> randomly _ _ = randomIO >>= x -> return $ if x then LT else GT > Stream.toList $ Stream.mergeByM randomly (Stream.fromList [1,1,1,1]) (Stream.fromList [2,2,2,2]) [2,1,2,2,2,1,1,1]
Merge two streams in a proportion of 2:1:
>>> :{
do
let proportionately m n = do
ref <- newIORef $ cycle $ Prelude.concat [Prelude.replicate m LT, Prelude.replicate n GT]
return $ _ _ -> do
r <- readIORef ref
writeIORef ref $ Prelude.tail r
return $ Prelude.head r
f <- proportionately 2 1
xs <- Stream.toList $ Stream.mergeByM f (Stream.fromList [1,1,1,1,1,1]) (Stream.fromList [2,2,2])
print xs
:}
[1,1,2,1,1,2,1,1,2]
See also: mergeByMFused
Since: 0.6.0
mergeByMFused :: (IsStream t, Monad m) => (a -> a -> m Ordering) -> t m a -> t m a -> t m a Source #
Like mergeByM but much faster, works best when merging statically known
number of streams. When merging more than two streams try to merge pairs and
pair pf pairs in a tree like structure.mergeByM works better with variable
number of streams being merged using concatPairsWith.
Internal
mergeAsyncBy :: (IsStream t, MonadAsync m) => (a -> a -> Ordering) -> t m a -> t m a -> t m a Source #
Like mergeBy but merges concurrently (i.e. both the elements being
merged are generated concurrently).
Since: 0.6.0
mergeAsyncByM :: (IsStream t, MonadAsync m) => (a -> a -> m Ordering) -> t m a -> t m a -> t m a Source #
Like mergeByM but merges concurrently (i.e. both the elements being
merged are generated concurrently).
Since: 0.6.0
mergeMinBy :: (a -> a -> m Ordering) -> t m a -> t m a -> t m a Source #
Like mergeByM but stops merging as soon as any of the two streams stops.
Unimplemented
mergeFstBy :: (a -> a -> m Ordering) -> t m a -> t m a -> t m a Source #
Like mergeByM but stops merging as soon as the first stream stops.
Unimplemented
Combine Streams and Unfolds
Expand a stream by repeatedly using an unfold and merging the resulting streams. Functions generally ending in the shape:
Unfold m a b -> t m a -> t m b
Append Many (Unfold)
Unfold and flatten streams.
unfoldManyInterleave :: (IsStream t, Monad m) => Unfold m a b -> t m a -> t m b Source #
Like unfoldMany but interleaves the streams in the same way as
interleave behaves instead of appending them.
Pre-release
unfoldManyRoundRobin :: (IsStream t, Monad m) => Unfold m a b -> t m a -> t m b Source #
Like unfoldMany but executes the streams in the same way as
roundrobin.
Pre-release
Interpose
Insert effects between streams. Like unfoldMany but intersperses an effect between the streams. A special case of gintercalate.
interpose :: (IsStream t, Monad m) => c -> Unfold m b c -> t m b -> t m c Source #
Unfold the elements of a stream, intersperse the given element between the unfolded streams and then concat them into a single stream.
unwords = S.interpose ' '
Pre-release
interposeSuffix :: (IsStream t, Monad m) => c -> Unfold m b c -> t m b -> t m c Source #
Unfold the elements of a stream, append the given element after each unfolded stream and then concat them into a single stream.
unlines = S.interposeSuffix '\n'
Pre-release
Intercalate
Insert Streams between Streams. Like unfoldMany but intersperses streams from another source between the streams from the first source.
intercalate :: (IsStream t, Monad m) => Unfold m b c -> b -> t m b -> t m c Source #
intersperse followed by unfold and concat.
intercalate unf a str = unfoldMany unf $ intersperse a str intersperse = intercalate (Unfold.function id) unwords = intercalate Unfold.fromList " "
>>>Stream.toList $ Stream.intercalate Unfold.fromList " " $ Stream.fromList ["abc", "def", "ghi"]"abc def ghi"
Since: 0.8.0
intercalateSuffix :: (IsStream t, Monad m) => Unfold m b c -> b -> t m b -> t m c Source #
intersperseMSuffix followed by unfold and concat.
intercalateSuffix unf a str = unfoldMany unf $ intersperseMSuffix a str intersperseMSuffix = intercalateSuffix (Unfold.function id) unlines = intercalateSuffix Unfold.fromList "\n"
>>>Stream.toList $ Stream.intercalateSuffix Unfold.fromList "\n" $ Stream.fromList ["abc", "def", "ghi"]"abc\ndef\nghi\n"
Since: 0.8.0
gintercalate :: (IsStream t, Monad m) => Unfold m a c -> t m a -> Unfold m b c -> t m b -> t m c Source #
interleaveInfix followed by unfold and concat.
Pre-release
gintercalateSuffix :: (IsStream t, Monad m) => Unfold m a c -> t m a -> Unfold m b c -> t m b -> t m c Source #
interleaveSuffix followed by unfold and concat.
Pre-release
Append Many (concatMap)
Map and serially append streams. concatMapM is a generalization of
the binary append operation to append many streams.
concatMapM :: (IsStream t, Monad m) => (a -> m (t m b)) -> t m a -> t m b Source #
Map a stream producing monadic function on each element of the stream
and then flatten the results into a single stream. Since the stream
generation function is monadic, unlike concatMap, it can produce an
effect at the beginning of each iteration of the inner loop.
Since: 0.6.0
concatMap :: (IsStream t, Monad m) => (a -> t m b) -> t m a -> t m b Source #
Map a stream producing function on each element of the stream and then flatten the results into a single stream.
>>>concatMap f = Stream.concatMapM (return . f)>>>concatMap f = Stream.concatMapWith Stream.serial f>>>concatMap f = Stream.concat . Stream.map f
Since: 0.6.0
concatM :: (IsStream t, Monad m) => m (t m a) -> t m a Source #
Given a stream value in the underlying monad, lift and join the underlying monad with the stream monad.
>>>concatM = Stream.concat . Stream.fromEffect>>>concatM = Stream.concat . lift -- requires (MonadTrans t)>>>concatM = join . lift -- requires (MonadTrans t, Monad (t m))
Internal
concat :: (IsStream t, Monad m) => t m (t m a) -> t m a Source #
Flatten a stream of streams to a single stream.
concat = concatMap id
Pre-release
Flatten Containers
Flatten Foldable containers using the binary stream merging
operations.
concatFoldableWith :: (IsStream t, Foldable f) => (t m a -> t m a -> t m a) -> f (t m a) -> t m a Source #
A variant of fold that allows you to fold a Foldable
container of streams using the specified stream sum operation.
concatFoldableWith async $ map return [1..3]Equivalent to:
concatFoldableWith f = Prelude.foldr f D.nil concatFoldableWith f = D.concatMapFoldableWith f id
Since: 0.8.0 (Renamed foldWith to concatFoldableWith)
Since: 0.1.0 (Streamly)
concatMapFoldableWith :: (IsStream t, Foldable f) => (t m b -> t m b -> t m b) -> (a -> t m b) -> f a -> t m b Source #
A variant of foldMap that allows you to map a monadic streaming action
on a Foldable container and then fold it using the specified stream merge
operation.
concatMapFoldableWith async return [1..3]Equivalent to:
concatMapFoldableWith f g = Prelude.foldr (f . g) S.nil concatMapFoldableWith f g xs = S.concatMapWith f g (S.fromFoldable xs)
Since: 0.8.0 (Renamed foldMapWith to concatMapFoldableWith)
Since: 0.1.0 (Streamly)
concatForFoldableWith :: (IsStream t, Foldable f) => (t m b -> t m b -> t m b) -> f a -> (a -> t m b) -> t m b Source #
Like concatMapFoldableWith but with the last two arguments reversed i.e. the
monadic streaming function is the last argument.
Equivalent to:
concatForFoldableWith f xs g = Prelude.foldr (f . g) D.nil xs concatForFoldableWith f = flip (D.concatMapFoldableWith f)
Since: 0.8.0 (Renamed forEachWith to concatForFoldableWith)
Since: 0.1.0 (Streamly)
ConcatMapWith
Map and flatten a stream like concatMap but using a custom binary
stream merging combinator instead of just appending the streams. The
merging occurs sequentially, it works efficiently for serial, async,
ahead like merge operations where we consume one stream before the
next or in case of wAsync or parallel where we consume all streams
simultaneously anyway.
However, in cases where the merging consumes streams in a round robin
fashion, a pair wise merging using concatPairsWith would be more
efficient. These cases include operations like mergeBy or zipWith.
concatMapWith :: IsStream t => (t m b -> t m b -> t m b) -> (a -> t m b) -> t m a -> t m b Source #
concatMapWith mixer generator stream is a two dimensional looping
combinator. The generator function is used to generate streams from the
elements in the input stream and the mixer function is used to merge
those streams.
Note we can merge streams concurrently by using a concurrent merge function.
Since: 0.7.0
Since: 0.8.0 (signature change)
concatSmapMWith :: (IsStream t, Monad m) => (t m b -> t m b -> t m b) -> (s -> a -> m (s, t m b)) -> m s -> t m a -> t m b Source #
Like concatMapWith but carries a state which can be used to share
information across multiple steps of concat.
concatSmapMWith combine f initial = concatMapWith combine id . smapM f initial
Pre-release
ConcatPairsWith
See the notes about suitable merge functions in the concatMapWith
section.
concatPairsWith :: IsStream t => (t m b -> t m b -> t m b) -> (a -> t m b) -> t m a -> t m b Source #
Combine streams in pairs using a binary stream combinator, then combine the resulting streams in pairs recursively until we get to a single combined stream.
For example, you can sort a stream using merge sort like this:
>>>Stream.toList $ Stream.concatPairsWith (Stream.mergeBy compare) Stream.fromPure $ Stream.fromList [5,1,7,9,2][1,2,5,7,9]
Caution: the stream of streams must be finite
Pre-release
IterateMap
Map and flatten Trees of Streams
iterateMapWith :: IsStream t => (t m a -> t m a -> t m a) -> (a -> t m a) -> t m a -> t m a Source #
Like iterateM but iterates after mapping a stream generator on the
output.
Yield an input element in the output stream, map a stream generator on it and then do the same on the resulting stream. This can be used for a depth first traversal of a tree like structure.
Note that iterateM is a special case of iterateMapWith:
iterateM f = iterateMapWith serial (fromEffect . f) . fromEffect
It can be used to traverse a tree structure. For example, to list a directory tree:
Stream.iterateMapWith Stream.serial
(either Dir.toEither (const nil))
(fromPure (Left "tmp"))
Pre-release
iterateSmapMWith :: (IsStream t, Monad m) => (t m a -> t m a -> t m a) -> (b -> a -> m (b, t m a)) -> m b -> t m a -> t m a Source #
Like iterateMap but carries a state in the stream generation function.
This can be used to traverse graph like structures, we can remember the
visited nodes in the state to avoid cycles.
Note that a combination of iterateMap and usingState can also be used to
traverse graphs. However, this function provides a more localized state
instead of using a global state.
See also: mfix
Pre-release
iterateMapLeftsWith :: (IsStream t, b ~ Either a c) => (t m b -> t m b -> t m b) -> (a -> t m b) -> t m b -> t m b Source #
In an Either stream iterate on Lefts. This is a special case of
iterateMapWith:
iterateMapLeftsWith combine f = iterateMapWith combine (either f (const nil))
To traverse a directory tree:
iterateMapLeftsWith serial Dir.toEither (fromPure (Left "tmp"))
Pre-release
iterateUnfold :: Unfold m a a -> t m a -> t m a Source #
Same as iterateMapWith Stream.serial but more efficient due to stream
fusion.
Unimplemented
Deprecated
Reduce By Streams
dropPrefix :: t m a -> t m a -> t m a Source #
Drop prefix from the input stream if present.
Space: O(1)
Unimplemented
dropInfix :: t m a -> t m a -> t m a Source #
Drop all matching infix from the input stream if present. Infix stream may be consumed multiple times.
Space: O(n) where n is the length of the infix.
Unimplemented
dropSuffix :: t m a -> t m a -> t m a Source #
Drop suffix from the input stream if present. Suffix stream may be consumed multiple times.
Space: O(n) where n is the length of the suffix.
Unimplemented
Reduce By Folds
Reduce a stream by folding or parsing chunks of the stream. Functions generally ending in these shapes:
f (Fold m a b) -> t m a -> t m b f (Parser a m b) -> t m a -> t m b
Generic Folding
Apply folds on a stream.
foldMany :: (IsStream t, Monad m) => Fold m a b -> t m a -> t m b Source #
Apply a Fold repeatedly on a stream and emit the fold outputs in the
output stream.
To sum every two contiguous elements in a stream:
>>>f = Fold.take 2 Fold.sum>>>Stream.toList $ Stream.foldMany f $ Stream.fromList [1..10][3,7,11,15,19]
On an empty stream the output is empty:
>>>Stream.toList $ Stream.foldMany f $ Stream.fromList [][]
Note Stream.foldMany (Fold.take 0) would result in an infinite loop in a
non-empty stream.
Since: 0.8.0
foldManyPost :: (IsStream t, Monad m) => Fold m a b -> t m a -> t m b Source #
Like foldMany but appends empty fold output if the fold and stream
termination aligns:
>>>f = Fold.take 2 Fold.sum>>>Stream.toList $ Stream.foldManyPost f $ Stream.fromList [][0]>>>Stream.toList $ Stream.foldManyPost f $ Stream.fromList [1..9][3,7,11,15,9]>>>Stream.toList $ Stream.foldManyPost f $ Stream.fromList [1..10][3,7,11,15,19,0]
Pre-release
foldSequence :: t m (Fold m a b) -> t m a -> t m b Source #
Apply a stream of folds to an input stream and emit the results in the output stream.
Unimplemented
foldIterateM :: (IsStream t, Monad m) => (b -> m (Fold m a b)) -> m b -> t m a -> t m b Source #
Iterate a fold generator on a stream. The initial value b is used to
generate the first fold, the fold is applied on the stream and the result of
the fold is used to generate the next fold and so on.
>>> import Data.Monoid (Sum(..)) >>> f x = return (Fold.take 2 (Fold.sconcat x)) >>> s = Stream.map Sum $ Stream.fromList [1..10] >>> Stream.toList $ Stream.map getSum $ Stream.foldIterateM f (pure 0) s [3,10,21,36,55,55]
This is the streaming equivalent of monad like sequenced application of folds where next fold is dependent on the previous fold.
Pre-release
refoldIterateM :: (IsStream t, Monad m) => Refold m b a b -> m b -> t m a -> t m b Source #
Like foldIterateM but using the Refold type instead. This could be
much more efficient due to stream fusion.
Internal
Chunking
Element unaware grouping.
chunksOf :: (IsStream t, Monad m) => Int -> Fold m a b -> t m a -> t m b Source #
Group the input stream into groups of n elements each and then fold each
group using the provided fold function.
>>>Stream.toList $ Stream.chunksOf 2 Fold.sum (Stream.enumerateFromTo 1 10)[3,7,11,15,19]
This can be considered as an n-fold version of take where we apply
take repeatedly on the leftover stream until the stream exhausts.
chunksOf n f = foldMany (FL.take n f)
Since: 0.7.0
arraysOf :: (IsStream t, MonadIO m, Unbox a) => Int -> t m a -> t m (Array a) Source #
arraysOf n stream groups the elements in the input stream into arrays of
n elements each.
Same as the following but may be more efficient:
arraysOf n = Stream.foldMany (A.writeN n)
Pre-release
intervalsOf :: (IsStream t, MonadAsync m) => Double -> Fold m a b -> t m a -> t m b Source #
Group the input stream into windows of n second each and then fold each
group using the provided fold function.
>>>Stream.toList $ Stream.take 5 $ Stream.intervalsOf 1 Fold.sum $ Stream.constRate 2 $ Stream.enumerateFrom 1[...,...,...,...,...]
Since: 0.7.0
chunksOfTimeout :: (IsStream t, MonadAsync m, Functor (t m)) => Int -> Double -> Fold m a b -> t m a -> t m b Source #
Like chunksOf but if the chunk is not completed within the specified
time interval then emit whatever we have collected till now. The chunk
timeout is reset whenever a chunk is emitted. The granularity of the clock
is 100 ms.
>>>s = Stream.delayPost 0.3 $ Stream.fromList [1..1000]>>>f = Stream.mapM_ print $ Stream.chunksOfTimeout 5 1 Fold.toList s
Pre-release
Splitting
Streams can be sliced into segments in space or in time. We use the
term chunk to refer to a spatial length of the stream (spatial window)
and the term session to refer to a length in time (time window).
splitOn :: (IsStream t, Monad m) => (a -> Bool) -> Fold m a b -> t m a -> t m b Source #
Split on an infixed separator element, dropping the separator. The
supplied Fold is applied on the split segments. Splits the stream on
separator elements determined by the supplied predicate, separator is
considered as infixed between two segments:
>>>splitOn' p xs = Stream.toList $ Stream.splitOn p Fold.toList (Stream.fromList xs)>>>splitOn' (== '.') "a.b"["a","b"]
An empty stream is folded to the default value of the fold:
>>>splitOn' (== '.') ""[""]
If one or both sides of the separator are missing then the empty segment on that side is folded to the default output of the fold:
>>>splitOn' (== '.') "."["",""]
>>>splitOn' (== '.') ".a"["","a"]
>>>splitOn' (== '.') "a."["a",""]
>>>splitOn' (== '.') "a..b"["a","","b"]
splitOn is an inverse of intercalating single element:
Stream.intercalate (Stream.fromPure '.') Unfold.fromList . Stream.splitOn (== '.') Fold.toList === id
Assuming the input stream does not contain the separator:
Stream.splitOn (== '.') Fold.toList . Stream.intercalate (Stream.fromPure '.') Unfold.fromList === id
Since: 0.7.0
splitOnSuffix :: (IsStream t, Monad m) => (a -> Bool) -> Fold m a b -> t m a -> t m b Source #
Split on a suffixed separator element, dropping the separator. The
supplied Fold is applied on the split segments.
>>>splitOnSuffix' p xs = Stream.toList $ Stream.splitOnSuffix p Fold.toList (Stream.fromList xs)>>>splitOnSuffix' (== '.') "a.b."["a","b"]
>>>splitOnSuffix' (== '.') "a."["a"]
An empty stream results in an empty output stream:
>>>splitOnSuffix' (== '.') ""[]
An empty segment consisting of only a suffix is folded to the default output of the fold:
>>>splitOnSuffix' (== '.') "."[""]
>>>splitOnSuffix' (== '.') "a..b.."["a","","b",""]
A suffix is optional at the end of the stream:
>>>splitOnSuffix' (== '.') "a"["a"]
>>>splitOnSuffix' (== '.') ".a"["","a"]
>>>splitOnSuffix' (== '.') "a.b"["a","b"]
lines = splitOnSuffix (== '\n')
splitOnSuffix is an inverse of intercalateSuffix with a single element:
Stream.intercalateSuffix (Stream.fromPure '.') Unfold.fromList . Stream.splitOnSuffix (== '.') Fold.toList === id
Assuming the input stream does not contain the separator:
Stream.splitOnSuffix (== '.') Fold.toList . Stream.intercalateSuffix (Stream.fromPure '.') Unfold.fromList === id
Since: 0.7.0
splitOnPrefix :: (a -> Bool) -> Fold m a b -> t m a -> t m b Source #
Split on a prefixed separator element, dropping the separator. The
supplied Fold is applied on the split segments.
> splitOnPrefix' p xs = Stream.toList $ Stream.splitOnPrefix p (Fold.toList) (Stream.fromList xs)
> splitOnPrefix' (== .) ".a.b"
["a","b"]
An empty stream results in an empty output stream:
> splitOnPrefix' (== .) ""
[]
An empty segment consisting of only a prefix is folded to the default output of the fold:
> splitOnPrefix' (==.) "." [""] > splitOnPrefix' (==.) ".a.b." ["a","b",""] > splitOnPrefix' (==.) ".a..b" ["a","","b"]
A prefix is optional at the beginning of the stream:
> splitOnPrefix' (==.) "a" ["a"] > splitOnPrefix' (==.) "a.b" ["a","b"]
splitOnPrefix is an inverse of intercalatePrefix with a single element:
Stream.intercalatePrefix (Stream.fromPure '.') Unfold.fromList . Stream.splitOnPrefix (== '.') Fold.toList === id
Assuming the input stream does not contain the separator:
Stream.splitOnPrefix (== '.') Fold.toList . Stream.intercalatePrefix (Stream.fromPure '.') Unfold.fromList === id
Unimplemented
splitOnAny :: [Array a] -> Fold m a b -> t m a -> t m b Source #
Split on any one of the given patterns.
Unimplemented
splitWithSuffix :: (IsStream t, Monad m) => (a -> Bool) -> Fold m a b -> t m a -> t m b Source #
Like splitOnSuffix but keeps the suffix attached to the resulting
splits.
>>>splitWithSuffix' p xs = Stream.toList $ splitWithSuffix p Fold.toList (Stream.fromList xs)
>>>splitWithSuffix' (== '.') ""[]
>>>splitWithSuffix' (== '.') "."["."]
>>>splitWithSuffix' (== '.') "a"["a"]
>>>splitWithSuffix' (== '.') ".a"[".","a"]
>>>splitWithSuffix' (== '.') "a."["a."]
>>>splitWithSuffix' (== '.') "a.b"["a.","b"]
>>>splitWithSuffix' (== '.') "a.b."["a.","b."]
>>>splitWithSuffix' (== '.') "a..b.."["a.",".","b.","."]
Since: 0.7.0
splitBySeq :: (IsStream t, MonadAsync m, Storable a, Unbox a, Enum a, Eq a) => Array a -> Fold m a b -> t m a -> t m b Source #
Like splitOnSeq but splits the separator as well, as an infix token.
>>>splitOn'_ pat xs = Stream.toList $ Stream.splitBySeq (Array.fromList pat) Fold.toList (Stream.fromList xs)
>>>splitOn'_ "" "hello"["h","","e","","l","","l","","o"]
>>>splitOn'_ "hello" ""[""]
>>>splitOn'_ "hello" "hello"["","hello",""]
>>>splitOn'_ "x" "hello"["hello"]
>>>splitOn'_ "h" "hello"["","h","ello"]
>>>splitOn'_ "o" "hello"["hell","o",""]
>>>splitOn'_ "e" "hello"["h","e","llo"]
>>>splitOn'_ "l" "hello"["he","l","","l","o"]
>>>splitOn'_ "ll" "hello"["he","ll","o"]
Pre-release
splitOnSeq :: (IsStream t, MonadIO m, Storable a, Unbox a, Enum a, Eq a) => Array a -> Fold m a b -> t m a -> t m b Source #
Like splitOn but the separator is a sequence of elements instead of a
single element.
For illustration, let's define a function that operates on pure lists:
>>>splitOnSeq' pat xs = Stream.toList $ Stream.splitOnSeq (Array.fromList pat) Fold.toList (Stream.fromList xs)
>>>splitOnSeq' "" "hello"["h","e","l","l","o"]
>>>splitOnSeq' "hello" ""[""]
>>>splitOnSeq' "hello" "hello"["",""]
>>>splitOnSeq' "x" "hello"["hello"]
>>>splitOnSeq' "h" "hello"["","ello"]
>>>splitOnSeq' "o" "hello"["hell",""]
>>>splitOnSeq' "e" "hello"["h","llo"]
>>>splitOnSeq' "l" "hello"["he","","o"]
>>>splitOnSeq' "ll" "hello"["he","o"]
splitOnSeq is an inverse of intercalate. The following law always holds:
intercalate . splitOnSeq == id
The following law holds when the separator is non-empty and contains none of the elements present in the input lists:
splitOnSeq . intercalate == id
>>>splitOnSeq pat f = Stream.foldManyPost (Fold.takeEndBySeq_ pat f)
Pre-release
splitOnSuffixSeq :: (IsStream t, MonadIO m, Storable a, Unbox a, Enum a, Eq a) => Array a -> Fold m a b -> t m a -> t m b Source #
Like splitSuffixBy but the separator is a sequence of elements, instead
of a predicate for a single element.
>>>splitOnSuffixSeq_ pat xs = Stream.toList $ Stream.splitOnSuffixSeq (Array.fromList pat) Fold.toList (Stream.fromList xs)
>>>splitOnSuffixSeq_ "." ""[]
>>>splitOnSuffixSeq_ "." "."[""]
>>>splitOnSuffixSeq_ "." "a"["a"]
>>>splitOnSuffixSeq_ "." ".a"["","a"]
>>>splitOnSuffixSeq_ "." "a."["a"]
>>>splitOnSuffixSeq_ "." "a.b"["a","b"]
>>>splitOnSuffixSeq_ "." "a.b."["a","b"]
>>>splitOnSuffixSeq_ "." "a..b.."["a","","b",""]
lines = splitOnSuffixSeq "\n"
splitOnSuffixSeq is an inverse of intercalateSuffix. The following law
always holds:
intercalateSuffix . splitOnSuffixSeq == id
The following law holds when the separator is non-empty and contains none of the elements present in the input lists:
splitSuffixOn . intercalateSuffix == id
>>>splitOnSuffixSeq pat f = Stream.foldMany (Fold.takeEndBySeq_ pat f)
Pre-release
splitWithSuffixSeq :: (IsStream t, MonadIO m, Storable a, Unbox a, Enum a, Eq a) => Array a -> Fold m a b -> t m a -> t m b Source #
Like splitOnSuffixSeq but keeps the suffix intact in the splits.
>>>splitWithSuffixSeq' pat xs = Stream.toList $ Stream.splitWithSuffixSeq (Array.fromList pat) Fold.toList (Stream.fromList xs)
>>>splitWithSuffixSeq' "." ""[]
>>>splitWithSuffixSeq' "." "."["."]
>>>splitWithSuffixSeq' "." "a"["a"]
>>>splitWithSuffixSeq' "." ".a"[".","a"]
>>>splitWithSuffixSeq' "." "a."["a."]
>>>splitWithSuffixSeq' "." "a.b"["a.","b"]
>>>splitWithSuffixSeq' "." "a.b."["a.","b."]
>>>splitWithSuffixSeq' "." "a..b.."["a.",".","b.","."]
>>>splitWithSuffixSeq pat f = Stream.foldMany (Fold.takeEndBySeq pat f)
Pre-release
splitOnSuffixSeqAny :: [Array a] -> Fold m a b -> t m a -> t m b Source #
Split post any one of the given patterns.
Unimplemented
Keyed Window Classification
Split the stream into chunks or windows by position or time. Each window can be associated with a key, all events associated with a particular key in the window can be folded to a single result. The window termination can be dynamically controlled by the fold.
The term "chunk" is used for a window defined by position of elements and the term "session" is used for a time window.
Tumbling Windows
A new window starts after the previous window is finished.
classifySessionsByGeneric Source #
Arguments
| :: forall t m f a b. (IsStream t, MonadAsync m, IsMap f) | |
| => Proxy (f :: Type -> Type) | |
| -> Double | timer tick in seconds |
| -> Bool | reset the timer when an event is received |
| -> (Int -> m Bool) | predicate to eject sessions based on session count |
| -> Double | session timeout in seconds |
| -> Fold m a b | Fold to be applied to session data |
| -> t m (AbsTime, (Key f, a)) | timestamp, (session key, session data) |
| -> t m (Key f, b) | session key, fold result |
Arguments
| :: (IsStream t, MonadAsync m, Ord k) | |
| => Double | timer tick in seconds |
| -> Bool | reset the timer when an event is received |
| -> (Int -> m Bool) | predicate to eject sessions based on session count |
| -> Double | session timeout in seconds |
| -> Fold m a b | Fold to be applied to session data |
| -> t m (AbsTime, (k, a)) | timestamp, (session key, session data) |
| -> t m (k, b) | session key, fold result |
classifySessionsBy tick keepalive predicate timeout fold stream
classifies an input event stream consisting of (timestamp, (key,
value)) into sessions based on the key, folding all the values
corresponding to the same key into a session using the supplied fold.
When the fold terminates or a timeout occurs, a tuple consisting of the
session key and the folded value is emitted in the output stream. The
timeout is measured from the first event in the session. If the keepalive
option is set to True the timeout is reset to 0 whenever an event is
received.
The timestamp in the input stream is an absolute time from some epoch,
characterizing the time when the input event was generated. The notion of
current time is maintained by a monotonic event time clock using the
timestamps seen in the input stream. The latest timestamp seen till now is
used as the base for the current time. When no new events are seen, a timer
is started with a clock resolution of tick seconds. This timer is used to
detect session timeouts in the absence of new events.
To ensure an upper bound on the memory used the number of sessions can be
limited to an upper bound. If the ejection predicate returns True, the
oldest session is ejected before inserting a new session.
When the stream ends any buffered sessions are ejected immediately.
If a session key is received even after a session has finished, another session is created for that key.
>>>:{Stream.mapM_ print $ Stream.classifySessionsBy 1 False (const (return False)) 3 (Fold.take 3 Fold.toList) $ Stream.timestamped $ Stream.delay 0.1 $ Stream.fromList ((,) <$> [1,2,3] <*> ['a','b','c']) :} (1,"abc") (2,"abc") (3,"abc")
Pre-release
Arguments
| :: (IsStream t, MonadAsync m, Ord k) | |
| => (Int -> m Bool) | predicate to eject sessions on session count |
| -> Double | time window size |
| -> Fold m a b | Fold to be applied to session data |
| -> t m (AbsTime, (k, a)) | timestamp, (session key, session data) |
| -> t m (k, b) |
Same as classifySessionsBy with a timer tick of 1 second and keepalive
option set to False.
classifySessionsOf = classifySessionsBy 1 False
Pre-release
Keep Alive Windows
The window size is extended if an event arrives within the specified window size. This can represent sessions with idle or inactive timeout.
classifyKeepAliveSessions Source #
Arguments
| :: (IsStream t, MonadAsync m, Ord k) | |
| => (Int -> m Bool) | predicate to eject sessions on session count |
| -> Double | session inactive timeout |
| -> Fold m a b | Fold to be applied to session payload data |
| -> t m (AbsTime, (k, a)) | timestamp, (session key, session data) |
| -> t m (k, b) |
Same as classifySessionsBy with a timer tick of 1 second and keepalive
option set to True.
classifyKeepAliveSessions = classifySessionsBy 1 True
Pre-release
Reduce By Parsers
Generic Parsing
Apply parsers on a stream.
parseMany :: (IsStream t, Monad m) => Parser a m b -> t m a -> t m (Either ParseError b) Source #
Apply a Parser repeatedly on a stream and emit the parsed values in the
output stream.
This is the streaming equivalent of the many
parse combinator.
>>>Stream.toList $ Stream.parseMany (Parser.takeBetween 0 2 Fold.sum) $ Stream.fromList [1..10][Right 3,Right 7,Right 11,Right 15,Right 19]
> Stream.toList $ Stream.parseMany (Parser.line Fold.toList) $ Stream.fromList "hello\nworld" ["hello\n","world"]
foldMany f = parseMany (fromFold f)
Known Issues: When the parser fails there is no way to get the remaining stream.
Pre-release
parseManyD :: (IsStream t, Monad m) => Parser a m b -> t m a -> t m (Either ParseError b) Source #
Same as parseMany but for StreamD streams.
Internal
parseManyTill :: Parser a m b -> Parser a m x -> t m a -> t m b Source #
parseManyTill collect test stream tries the parser test on the input,
if test fails it backtracks and tries collect, after collect succeeds
test is tried again and so on. The parser stops when test succeeds. The
output of test is discarded and the output of collect is emitted in the
output stream. The parser fails if collect fails.
Unimplemented
parseSequence :: t m (Parser a m b) -> t m a -> t m b Source #
Apply a stream of parsers to an input stream and emit the results in the output stream.
Unimplemented
parseIterate :: (IsStream t, Monad m) => (b -> Parser a m b) -> b -> t m a -> t m (Either ParseError b) Source #
Iterate a parser generating function on a stream. The initial value b is
used to generate the first parser, the parser is applied on the stream and
the result is used to generate the next parser and so on.
>>>import Data.Monoid (Sum(..))>>>Stream.toList $ fmap getSum $ Stream.rights $ Stream.parseIterate (\b -> Parser.takeBetween 0 2 (Fold.sconcat b)) (Sum 0) $ fmap Sum $ Stream.fromList [1..10][3,10,21,36,55,55]
This is the streaming equivalent of monad like sequenced application of parsers where next parser is dependent on the previous parser.
Pre-release
Grouping
wordsBy :: (IsStream t, Monad m) => (a -> Bool) -> Fold m a b -> t m a -> t m b Source #
Like splitOn after stripping leading, trailing, and repeated separators.
Therefore, ".a..b." with . as the separator would be parsed as
["a","b"]. In other words, its like parsing words from whitespace
separated text.
>>>wordsBy' p xs = Stream.toList $ Stream.wordsBy p Fold.toList (Stream.fromList xs)
>>>wordsBy' (== ',') ""[]
>>>wordsBy' (== ',') ","[]
>>>wordsBy' (== ',') ",a,,b,"["a","b"]
words = wordsBy isSpace
Since: 0.7.0
wordsOn :: Array a -> Fold m a b -> t m a -> t m b Source #
Like splitOn but drops any empty splits.
Unimplemented
groups :: (IsStream t, Monad m, Eq a) => Fold m a b -> t m a -> t m b Source #
groups = groupsBy (==) groups = groupsByRolling (==)
Groups contiguous spans of equal elements together in individual groups.
>>>Stream.toList $ Stream.groups Fold.toList $ Stream.fromList [1,1,2,2][[1,1],[2,2]]
Since: 0.7.0
groupsBy :: (IsStream t, Monad m) => (a -> a -> Bool) -> Fold m a b -> t m a -> t m b Source #
groupsBy cmp f $ S.fromList [a,b,c,...] assigns the element a to the
first group, if b `cmp` a is True then b is also assigned to the same
group. If c `cmp` a is True then c is also assigned to the same
group and so on. When the comparison fails a new group is started. Each
group is folded using the fold f and the result of the fold is emitted in
the output stream.
>>>Stream.toList $ Stream.groupsBy (>) Fold.toList $ Stream.fromList [1,3,7,0,2,5][[1,3,7],[0,2,5]]
Since: 0.7.0
groupsByRolling :: (IsStream t, Monad m) => (a -> a -> Bool) -> Fold m a b -> t m a -> t m b Source #
Unlike groupsBy this function performs a rolling comparison of two
successive elements in the input stream. groupsByRolling cmp f $ S.fromList
[a,b,c,...] assigns the element a to the first group, if a `cmp` b is
True then b is also assigned to the same group. If b `cmp` c is
True then c is also assigned to the same group and so on. When the
comparison fails a new group is started. Each group is folded using the fold
f.
>>>Stream.toList $ Stream.groupsByRolling (\a b -> a + 1 == b) Fold.toList $ Stream.fromList [1,2,3,7,8,9][[1,2,3],[7,8,9]]
Since: 0.7.0
Nested splitting
splitInnerBy :: (IsStream t, Monad m) => (f a -> m (f a, Maybe (f a))) -> (f a -> f a -> m (f a)) -> t m (f a) -> t m (f a) Source #
splitInnerBy splitter joiner stream splits the inner containers f a of
an input stream t m (f a) using the splitter function. Container
elements f a are collected until a split occurs, then all the elements
before the split are joined using the joiner function.
For example, if we have a stream of Array Word8, we may want to split the
stream into arrays representing lines separated by 'n' byte such that the
resulting stream after a split would be one array for each line.
CAUTION! This is not a true streaming function as the container size after the split and merge may not be bounded.
Pre-release
splitInnerBySuffix :: (IsStream t, Monad m, Eq (f a), Monoid (f a)) => (f a -> m (f a, Maybe (f a))) -> (f a -> f a -> m (f a)) -> t m (f a) -> t m (f a) Source #
Like splitInnerBy but splits assuming the separator joins the segment in
a suffix style.
Pre-release
before :: (IsStream t, Monad m) => m b -> t m a -> t m a Source #
Run the action m b before the stream yields its first element.
Same as the following but more efficient due to fusion:
>>>before action xs = Stream.nilM action <> xs>>>before action xs = Stream.concatMap (const xs) (Stream.fromEffect action)
Since: 0.7.0
after_ :: (IsStream t, Monad m) => m b -> t m a -> t m a Source #
Like after, with following differences:
- action
m bwon't run if the stream is garbage collected after partial evaluation. - Monad
mdoes not require any other constraints. - has slightly better performance than
after.
Same as the following, but with stream fusion:
after_ action xs = xs <> 'nilM' action
Pre-release
after :: (IsStream t, MonadRunInIO m) => m b -> t m a -> t m a Source #
bracket_ :: (IsStream t, MonadCatch m) => m b -> (b -> m c) -> (b -> t m a) -> t m a Source #
Like bracket but with following differences:
- alloc action
m bruns with async exceptions enabled - cleanup action
b -> m cwon't run if the stream is garbage collected after partial evaluation. - does not require a
MonadAsyncconstraint. - has slightly better performance than
bracket.
Inhibits stream fusion
Pre-release
bracket :: (IsStream t, MonadAsync m, MonadCatch m) => m b -> (b -> m c) -> (b -> t m a) -> t m a Source #
Run the alloc action m b with async exceptions disabled but keeping
blocking operations interruptible (see mask). Use the
output b as input to b -> t m a to generate an output stream.
b is usually a resource under the state of monad m, e.g. a file
handle, that requires a cleanup after use. The cleanup action b -> m c,
runs whenever the stream ends normally, due to a sync or async exception or
if it gets garbage collected after a partial lazy evaluation.
bracket only guarantees that the cleanup action runs, and it runs with
async exceptions enabled. The action must ensure that it can successfully
cleanup the resource in the face of sync or async exceptions.
When the stream ends normally or on a sync exception, cleanup action runs immediately in the current thread context, whereas in other cases it runs in the GC context, therefore, cleanup may be delayed until the GC gets to run.
See also: bracket_
Inhibits stream fusion
Since: 0.7.0
bracket' :: (IsStream t, MonadAsync m, MonadCatch m) => m b -> (b -> m c) -> (b -> m d) -> (b -> m e) -> (b -> t m a) -> t m a Source #
Like bracket but can use separate cleanup actions depending on the mode
of termination. bracket' before onStop onGC onException action runs
action using the result of before. If the stream stops, onStop action
is executed, if the stream is abandoned onGC is executed, if the stream
encounters an exception onException is executed.
Pre-release
onException :: (IsStream t, MonadCatch m) => m b -> t m a -> t m a Source #
Run the action m b if the stream aborts due to an exception. The
exception is not caught, simply rethrown.
Inhibits stream fusion
Since: 0.7.0
finally_ :: (IsStream t, MonadCatch m) => m b -> t m a -> t m a Source #
Like finally with following differences:
- action
m bwon't run if the stream is garbage collected after partial evaluation. - does not require a
MonadAsyncconstraint. - has slightly better performance than
finally.
Inhibits stream fusion
Pre-release
finally :: (IsStream t, MonadAsync m, MonadCatch m) => m b -> t m a -> t m a Source #
Run the action m b whenever the stream t m a stops normally, aborts
due to an exception or if it is garbage collected after a partial lazy
evaluation.
The semantics of running the action m b are similar to the cleanup action
semantics described in bracket.
See also finally_
Inhibits stream fusion
Since: 0.7.0
ghandle :: (IsStream t, MonadCatch m, Exception e) => (e -> t m a -> t m a) -> t m a -> t m a Source #
Like handle but the exception handler is also provided with the stream
that generated the exception as input. The exception handler can thus
re-evaluate the stream to retry the action that failed. The exception
handler can again call ghandle on it to retry the action multiple times.
This is highly experimental. In a stream of actions we can map the stream with a retry combinator to retry each action on failure.
Inhibits stream fusion
Pre-release
handle :: (IsStream t, MonadCatch m, Exception e) => (e -> t m a) -> t m a -> t m a Source #
When evaluating a stream if an exception occurs, stream evaluation aborts and the specified exception handler is run with the exception as argument.
Inhibits stream fusion
Since: 0.7.0
Arguments
| :: (IsStream t, MonadCatch m, Exception e, Ord e) | |
| => Map e Int | map from exception to retry count |
| -> (e -> t m a) | default handler for those exceptions that are not in the map |
| -> t m a | |
| -> t m a |
retry takes 3 arguments
- A map
mwhose keys are exceptions and values are the number of times to retry the action given that the exception occurs. - A handler
hanthat decides how to handle an exception when the exception cannot be retried. - The stream itself that we want to run this mechanism on.
When evaluating a stream if an exception occurs,
- The stream evaluation aborts
- The exception is looked up in
m
a. If the exception exists and the mapped value is > 0 then,
i. The value is decreased by 1.
ii. The stream is resumed from where the exception was called, retrying the action.
b. If the exception exists and the mapped value is == 0 then the stream evaluation stops.
c. If the exception does not exist then we handle the exception using
han.
Internal
Generalize Inner Monad
hoist :: (Monad m, Monad n) => (forall x. m x -> n x) -> SerialT m a -> SerialT n a Source #
Transform the inner monad of a stream using a natural transformation.
Internal
generally :: (IsStream t, Monad m) => t Identity a -> t m a Source #
Generalize the inner monad of the stream from Identity to any monad.
Internal
Transform Inner Monad
liftInner :: (Monad m, IsStream t, MonadTrans tr, Monad (tr m)) => t m a -> t (tr m) a Source #
Lift the inner monad m of a stream t m a to tr m using the monad
transformer tr.
Since: 0.8.0
usingReaderT :: (Monad m, IsStream t) => m r -> (t (ReaderT r m) a -> t (ReaderT r m) a) -> t m a -> t m a Source #
runReaderT :: (IsStream t, Monad m) => m s -> t (ReaderT s m) a -> t m a Source #
Evaluate the inner monad of a stream as ReaderT.
Since: 0.8.0
usingStateT :: Monad m => m s -> (SerialT (StateT s m) a -> SerialT (StateT s m) a) -> SerialT m a -> SerialT m a Source #
Run a stateful (StateT) stream transformation using a given state.
This is supported only for SerialT as concurrent state updation may not be
safe.
usingStateT s f = evalStateT s . f . liftInner
See also: scanl'
Internal
Transformation
Sampling
Value agnostic filtering.
sampleFromThen :: (IsStream t, Monad m, Functor (t m)) => Int -> Int -> t m a -> t m a Source #
sampleFromthen offset stride samples the element at offset index and
then every element at strides of stride.
>>>Stream.toList $ Stream.sampleFromThen 2 3 $ Stream.enumerateFromTo 0 10[2,5,8]
Pre-release
sampleIntervalStart :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m a -> t m a Source #
Like sampleInterval but samples at the beginning of the time window.
sampleIntervalStart n = Stream.catMaybes . Stream.intervalsOf n Fold.one
Pre-release
sampleIntervalEnd :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m a -> t m a Source #
Continuously evaluate the input stream and sample the last event in time
window of n seconds.
This is also known as throttle in some libraries.
sampleIntervalEnd n = Stream.catMaybes . Stream.intervalsOf n Fold.last
Pre-release
sampleBurstStart :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m a -> t m a Source #
Like sampleBurstEnd but samples the event at the beginning of the burst
instead of at the end of it.
Pre-release
sampleBurstEnd :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m a -> t m a Source #
Sample one event at the end of each burst of events. A burst is a group of events close together in time, it ends when an event is spaced by more than the specified time interval (in seconds) from the previous event.
This is known as debounce in some libraries.
The clock granularity is 10 ms.
Pre-release
Reordering
sortBy :: MonadCatch m => (a -> a -> Ordering) -> SerialT m a -> SerialT m a Source #
Sort the input stream using a supplied comparison function.
O(n) space
Note: this is not the fastest possible implementation as of now.
Pre-release
Nesting
Set like operations
These are not exactly set operations because streams are not necessarily sets, they may have duplicated elements.
intersectBy :: (IsStream t, Monad m) => (a -> a -> Bool) -> t m a -> t m a -> t m a Source #
intersectBy is essentially a filtering operation that retains only those
elements in the first stream that are present in the second stream.
>>>Stream.toList $ Stream.intersectBy (==) (Stream.fromList [1,2,2,4]) (Stream.fromList [2,1,1,3])[1,2,2]
>>>Stream.toList $ Stream.intersectBy (==) (Stream.fromList [2,1,1,3]) (Stream.fromList [1,2,2,4])[2,1,1]
intersectBy is similar to but not the same as joinInner:
>>>Stream.toList $ fmap fst $ Stream.joinInner (==) (Stream.fromList [1,2,2,4]) (Stream.fromList [2,1,1,3])[1,1,2,2]
Space: O(n) where n is the number of elements in the second stream.
Time: O(m x n) where m is the number of elements in the first stream and
n is the number of elements in the second stream.
Pre-release
intersectBySorted :: (IsStream t, Monad m) => (a -> a -> Ordering) -> t m a -> t m a -> t m a Source #
Like intersectBy but works only on streams sorted in ascending order.
Space: O(1)
Time: O(m+n)
Pre-release
differenceBy :: (IsStream t, Monad m) => (a -> a -> Bool) -> t m a -> t m a -> t m a Source #
Delete first occurrences of those elements from the first stream that are present in the second stream. If an element occurs multiple times in the second stream as many occurrences of it are deleted from the first stream.
>>>Stream.toList $ Stream.differenceBy (==) (Stream.fromList [1,2,2]) (Stream.fromList [1,2,3])[2]
The following laws hold:
(s1serials2) `differenceBy eq` s1 === s2 (s1wSerials2) `differenceBy eq` s1 === s2
Same as the list // operation.
Space: O(m) where m is the number of elements in the first stream.
Time: O(m x n) where m is the number of elements in the first stream and
n is the number of elements in the second stream.
Pre-release
mergeDifferenceBy :: (a -> a -> Ordering) -> t m a -> t m a -> t m a Source #
unionBy :: (IsStream t, MonadAsync m, Semigroup (t m a)) => (a -> a -> Bool) -> t m a -> t m a -> t m a Source #
This is essentially an append operation that appends all the extra occurrences of elements from the second stream that are not already present in the first stream.
>>>Stream.toList $ Stream.unionBy (==) (Stream.fromList [1,2,2,4]) (Stream.fromList [1,1,2,3])[1,2,2,4,3]
Equivalent to the following except that s1 is evaluated only once:
unionBy eq s1 s2 = s1 `serial` (s2 `differenceBy eq` s1)
Similar to joinOuter but not the same.
Space: O(n)
Time: O(m x n)
Pre-release
mergeUnionBy :: (a -> a -> Ordering) -> t m a -> t m a -> t m a Source #
Join operations
crossJoin :: Monad (t m) => t m a -> t m b -> t m (a, b) Source #
This is the same as outerProduct but less
efficient.
The second stream is evaluated multiple times. If the second stream is
consume-once stream then it can be cached in an Array before
calling this function. Caching may also improve performance if the stream is
expensive to evaluate.
Time: O(m x n)
Pre-release
joinInner :: forall (t :: (Type -> Type) -> Type -> Type) m a b. (IsStream t, Monad m) => (a -> b -> Bool) -> t m a -> t m b -> t m (a, b) Source #
For all elements in t m a, for all elements in t m b if a and b
are equal by the given equality pedicate then return the tuple (a, b).
The second stream is evaluated multiple times. If the stream is a
consume-once stream then the caller should cache it (e.g. in a
Array) before calling this function. Caching may also improve
performance if the stream is expensive to evaluate.
For space efficiency use the smaller stream as the second stream.
You should almost always use joinInnerMap instead of joinInner. joinInnerMap is an order of magnitude faster. joinInner may be used when the second stream is generated from a seed, therefore, need not be stored in memory and the amount of memory it takes is a concern.
Space: O(n) assuming the second stream is cached in memory.
Time: O(m x n)
Pre-release
joinInnerMap :: (IsStream t, Monad m, Ord k) => t m (k, a) -> t m (k, b) -> t m (k, a, b) Source #
Like joinInner but uses a Map for efficiency.
If the input streams have duplicate keys, the behavior is undefined.
For space efficiency use the smaller stream as the second stream.
Space: O(n)
Time: O(m + n)
Pre-release
joinInnerMerge :: (a -> b -> Ordering) -> t m a -> t m b -> t m (a, b) Source #
mergeLeftJoin :: (a -> b -> Ordering) -> t m a -> t m b -> t m (a, Maybe b) Source #
Like joinLeft but works only on sorted streams.
Space: O(1)
Time: O(m + n)
Unimplemented
joinLeftMap :: (IsStream t, Ord k, Monad m) => t m (k, a) -> t m (k, b) -> t m (k, a, Maybe b) Source #
Like joinLeft but uses a hashmap for efficiency.
Space: O(n)
Time: O(m + n)
Pre-release
mergeOuterJoin :: (a -> b -> Ordering) -> t m a -> t m b -> t m (Maybe a, Maybe b) Source #
Like joinOuter but works only on sorted streams.
Space: O(1)
Time: O(m + n)
Unimplemented
joinOuterMap :: (IsStream t, Ord k, MonadIO m) => t m (k, a) -> t m (k, b) -> t m (k, Maybe a, Maybe b) Source #
Like joinOuter but uses a Map for efficiency.
Space: O(m + n)
Time: O(m + n)
Pre-release
maxThreads :: IsStream t => Int -> t m a -> t m a Source #
Specify the maximum number of threads that can be spawned concurrently for
any concurrent combinator in a stream.
A value of 0 resets the thread limit to default, a negative value means
there is no limit. The default value is 1500. maxThreads does not affect
ParallelT streams as they can use unbounded number of threads.
When the actions in a stream are IO bound, having blocking IO calls, this option can be used to control the maximum number of in-flight IO requests. When the actions are CPU bound this option can be used to control the amount of CPU used by the stream.
Since: 0.4.0 (Streamly)
Since: 0.8.0
maxBuffer :: IsStream t => Int -> t m a -> t m a Source #
Specify the maximum size of the buffer for storing the results from concurrent computations. If the buffer becomes full we stop spawning more concurrent tasks until there is space in the buffer. A value of 0 resets the buffer size to default, a negative value means there is no limit. The default value is 1500.
CAUTION! using an unbounded maxBuffer value (i.e. a negative value)
coupled with an unbounded maxThreads value is a recipe for disaster in
presence of infinite streams, or very large streams. Especially, it must
not be used when pure is used in ZipAsyncM streams as pure in
applicative zip streams generates an infinite stream causing unbounded
concurrent generation with no limit on the buffer or threads.
Since: 0.4.0 (Streamly)
Since: 0.8.0
rate :: IsStream t => Maybe Rate -> t m a -> t m a Source #
Specify the pull rate of a stream.
A Nothing value resets the rate to default which is unlimited. When the
rate is specified, concurrent production may be ramped up or down
automatically to achieve the specified yield rate. The specific behavior for
different styles of Rate specifications is documented under Rate. The
effective maximum production rate achieved by a stream is governed by:
- The
maxThreadslimit - The
maxBufferlimit - The maximum rate that the stream producer can achieve
- The maximum rate that the stream consumer can achieve
Since: 0.5.0 (Streamly)
Since: 0.8.0
avgRate :: IsStream t => Double -> t m a -> t m a Source #
Same as rate (Just $ Rate (r/2) r (2*r) maxBound)
Specifies the average production rate of a stream in number of yields
per second (i.e. Hertz). Concurrent production is ramped up or down
automatically to achieve the specified average yield rate. The rate can
go down to half of the specified rate on the lower side and double of
the specified rate on the higher side.
Since: 0.5.0 (Streamly)
Since: 0.8.0
minRate :: IsStream t => Double -> t m a -> t m a Source #
Same as rate (Just $ Rate r r (2*r) maxBound)
Specifies the minimum rate at which the stream should yield values. As far as possible the yield rate would never be allowed to go below the specified rate, even though it may possibly go above it at times, the upper limit is double of the specified rate.
Since: 0.5.0 (Streamly)
Since: 0.8.0
maxRate :: IsStream t => Double -> t m a -> t m a Source #
Same as rate (Just $ Rate (r/2) r r maxBound)
Specifies the maximum rate at which the stream should yield values. As far as possible the yield rate would never be allowed to go above the specified rate, even though it may possibly go below it at times, the lower limit is half of the specified rate. This can be useful in applications where certain resource usage must not be allowed to go beyond certain limits.
Since: 0.5.0 (Streamly)
Since: 0.8.0
constRate :: IsStream t => Double -> t m a -> t m a Source #
Same as rate (Just $ Rate r r r 0)
Specifies a constant yield rate. If for some reason the actual rate goes above or below the specified rate we do not try to recover it by increasing or decreasing the rate in future. This can be useful in applications like graphics frame refresh where we need to maintain a constant refresh rate.
Since: 0.5.0 (Streamly)
Since: 0.8.0
inspectMode :: IsStream t => t m a -> t m a Source #
Print debug information about an SVar when the stream ends
Pre-release
Generation
fromPure :: IsStream t => a -> t m a Source #
fromPure a = a `cons` nil
Create a singleton stream from a pure value.
The following holds in monadic streams, but not in Zip streams:
fromPure = pure fromPure = fromEffect . pure
In Zip applicative streams fromPure is not the same as pure because in that
case pure is equivalent to repeat instead. fromPure and pure are
equally efficient, in other cases fromPure may be slightly more efficient
than the other equivalent definitions.
Since: 0.8.0 (Renamed yield to fromPure)
fromEffect :: (Monad m, IsStream t) => m a -> t m a Source #
fromEffect m = m `consM` nil
Create a singleton stream from a monadic action.
> Stream.toList $ Stream.fromEffect getLine hello ["hello"]
Since: 0.8.0 (Renamed yieldM to fromEffect)
repeatM :: (IsStream t, MonadAsync m) => m a -> t m a Source #
>>>repeatM = fix . consM>>>repeatM = cycle1 . fromEffect
Generate a stream by repeatedly executing a monadic action forever.
>>>:{repeatAsync = Stream.repeatM (threadDelay 1000000 >> print 1) & Stream.take 10 & Stream.fromAsync & Stream.drain :}
Concurrent, infinite (do not use with fromParallel)
Since: 0.2.0
timesWith :: (IsStream t, MonadAsync m) => Double -> t m (AbsTime, RelTime64) Source #
timesWith g returns a stream of time value tuples. The first component
of the tuple is an absolute time reference (epoch) denoting the start of the
stream and the second component is a time relative to the reference.
The argument g specifies the granularity of the relative time in seconds.
A lower granularity clock gives higher precision but is more expensive in
terms of CPU usage. Any granularity lower than 1 ms is treated as 1 ms.
>>>import Control.Concurrent (threadDelay)>>>import Streamly.Internal.Data.Stream.IsStream.Common as Stream (timesWith)>>>Stream.mapM_ (\x -> print x >> threadDelay 1000000) $ Stream.take 3 $ Stream.timesWith 0.01(AbsTime (TimeSpec {sec = ..., nsec = ...}),RelTime64 (NanoSecond64 ...)) (AbsTime (TimeSpec {sec = ..., nsec = ...}),RelTime64 (NanoSecond64 ...)) (AbsTime (TimeSpec {sec = ..., nsec = ...}),RelTime64 (NanoSecond64 ...))
Note: This API is not safe on 32-bit machines.
Pre-release
absTimesWith :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m AbsTime Source #
absTimesWith g returns a stream of absolute timestamps using a clock of
granularity g specified in seconds. A low granularity clock is more
expensive in terms of CPU usage. Any granularity lower than 1 ms is treated
as 1 ms.
>>>Stream.mapM_ print $ Stream.delayPre 1 $ Stream.take 3 $ absTimesWith 0.01AbsTime (TimeSpec {sec = ..., nsec = ...}) AbsTime (TimeSpec {sec = ..., nsec = ...}) AbsTime (TimeSpec {sec = ..., nsec = ...})
Note: This API is not safe on 32-bit machines.
Pre-release
relTimesWith :: (IsStream t, MonadAsync m, Functor (t m)) => Double -> t m RelTime64 Source #
relTimesWith g returns a stream of relative time values starting from 0,
using a clock of granularity g specified in seconds. A low granularity
clock is more expensive in terms of CPU usage. Any granularity lower than 1
ms is treated as 1 ms.
>>>Stream.mapM_ print $ Stream.delayPre 1 $ Stream.take 3 $ Stream.relTimesWith 0.01RelTime64 (NanoSecond64 ...) RelTime64 (NanoSecond64 ...) RelTime64 (NanoSecond64 ...)
Note: This API is not safe on 32-bit machines.
Pre-release
Elimination
foldContinue :: Monad m => Fold m a b -> SerialT m a -> Fold m a b Source #
We can create higher order folds using foldContinue. We can fold a
number of streams to a given fold efficiently with full stream fusion. For
example, to fold a list of streams on the same sum fold:
concatFold = Prelude.foldl Stream.foldContinue Fold.sum
fold f = Fold.extractM . Stream.foldContinue f
Internal
fold :: Monad m => Fold m a b -> SerialT m a -> m b Source #
Fold a stream using the supplied left Fold and reducing the resulting
expression strictly at each step. The behavior is similar to foldl'. A
Fold can terminate early without consuming the full stream. See the
documentation of individual Folds for termination behavior.
>>>Stream.fold Fold.sum (Stream.enumerateFromTo 1 100)5050
Folds never fail, therefore, they produce a default value even when no input is provided. It means we can always fold an empty stream and get a valid result. For example:
>>>Stream.fold Fold.sum Stream.nil0
However, foldMany on an empty stream results in an empty stream.
Therefore, Stream.fold f is not the same as Stream.head . Stream.foldMany
f.
fold f = Stream.parse (Parser.fromFold f)
Since: 0.7.0
Transformation
scanlMAfter' :: (IsStream t, Monad m) => (b -> a -> m b) -> m b -> (b -> m b) -> t m a -> t m b Source #
scanlMAfter' accumulate initial done stream is like scanlM' except
that it provides an additional done function to be applied on the
accumulator when the stream stops. The result of done is also emitted in
the stream.
This function can be used to allocate a resource in the beginning of the scan and release it when the stream ends or to flush the internal state of the scan at the end.
Pre-release
postscanlMAfter' :: (IsStream t, Monad m) => (b -> a -> m b) -> m b -> (b -> m b) -> t m a -> t m b Source #
postscanlM' :: (IsStream t, Monad m) => (b -> a -> m b) -> m b -> t m a -> t m b Source #
Like postscanl' but with a monadic step function and a monadic seed.
>>>postscanlM' f z xs = Stream.drop 1 $ Stream.scanlM' f z xs
Since: 0.7.0
Since: 0.8.0 (signature change)
smapM :: (IsStream t, Monad m) => (s -> a -> m (s, b)) -> m s -> t m a -> t m b Source #
A stateful mapM, equivalent to a left scan, more like mapAccumL.
Hopefully, this is a better alternative to scan. Separation of state from
the output makes it easier to think in terms of a shared state, and also
makes it easier to keep the state fully strict and the output lazy.
See also: scanlM'
Pre-release
foldManyPost :: (IsStream t, Monad m) => Fold m a b -> t m a -> t m b Source #
Like foldMany but appends empty fold output if the fold and stream
termination aligns:
>>>f = Fold.take 2 Fold.sum>>>Stream.toList $ Stream.foldManyPost f $ Stream.fromList [][0]>>>Stream.toList $ Stream.foldManyPost f $ Stream.fromList [1..9][3,7,11,15,9]>>>Stream.toList $ Stream.foldManyPost f $ Stream.fromList [1..10][3,7,11,15,19,0]
Pre-release
The stateful step function can be simplified to (s -> a -> m b) to provide
a read-only environment. However, that would just be mapM.
The initial action could be m (s, Maybe b), and we can also add a final
action s -> m (Maybe b). This can be used to get pre/post scan like
functionality and also to flush the state in the end like scanlMAfter'.
We can also use it along with a fusible version of bracket to get
scanlMAfter' like functionality. See issue #677.
This can be further generalized to a type similar to Fold/Parser, giving it filtering and parsing capability as well (this is in fact equivalent to parseMany):
smapM :: (s -> a -> m (Step s b)) -> m s -> t m a -> t m b
take :: (IsStream t, Monad m) => Int -> t m a -> t m a Source #
Take first n elements from the stream and discard the rest.
Since: 0.1.0
takeWhile :: (IsStream t, Monad m) => (a -> Bool) -> t m a -> t m a Source #
End the stream as soon as the predicate fails on an element.
Since: 0.1.0
drop :: (IsStream t, Monad m) => Int -> t m a -> t m a Source #
Discard first n elements from the stream and take the rest.
Since: 0.1.0
findIndices :: (IsStream t, Monad m) => (a -> Bool) -> t m a -> t m Int Source #
Find all the indices where the element in the stream satisfies the given predicate.
findIndices = fold Fold.findIndices
Since: 0.5.0
intersperseM :: (IsStream t, MonadAsync m) => m a -> t m a -> t m a Source #
Insert an effect and its output before consuming an element of a stream except the first one.
>>>Stream.toList $ Stream.trace putChar $ Stream.intersperseM (putChar '.' >> return ',') $ Stream.fromList "hello"h.,e.,l.,l.,o"h,e,l,l,o"
Be careful about the order of effects. In the above example we used trace after the intersperse, if we use it before the intersperse the output would be he.l.l.o."h,e,l,l,o".
>>>Stream.toList $ Stream.intersperseM (putChar '.' >> return ',') $ Stream.trace putChar $ Stream.fromList "hello"he.l.l.o."h,e,l,l,o"
Since: 0.5.0
interjectSuffix :: (IsStream t, MonadAsync m) => Double -> m a -> t m a -> t m a Source #
Intersperse a monadic action into the input stream after every n
seconds.
> import Control.Concurrent (threadDelay) > Stream.drain $ Stream.interjectSuffix 1 (putChar ',') $ Stream.mapM (x -> threadDelay 1000000 >> putChar x) $ Stream.fromList "hello" h,e,l,l,o
Pre-release
reverse :: (IsStream t, Monad m) => t m a -> t m a Source #
Returns the elements of the stream in reverse order. The stream must be finite. Note that this necessarily buffers the entire stream in memory.
>>>reverse = Stream.foldlT (flip Stream.cons) Stream.nil
Since 0.7.0 (Monad m constraint)
Since: 0.1.1
Concurrent
mkAsync :: (IsStream t, MonadAsync m) => t m a -> t m a Source #
Make the stream producer and consumer run concurrently by introducing a buffer between them. The producer thread evaluates the input stream until the buffer fills, it terminates if the buffer is full and a worker thread is kicked off again to evaluate the remaining stream when there is space in the buffer. The consumer consumes the stream lazily from the buffer.
Since: 0.2.0 (Streamly)
Since: 0.8.0
mkParallel :: (IsStream t, MonadAsync m) => t m a -> t m a Source #
Make the stream producer and consumer run concurrently by introducing a buffer between them. The producer thread evaluates the input stream until the buffer fills, it blocks if the buffer is full until there is space in the buffer. The consumer consumes the stream lazily from the buffer.
mkParallel = IsStream.fromStreamD . mkParallelD . IsStream.toStreamD
Pre-release
parallelFst :: (IsStream t, MonadAsync m) => t m a -> t m a -> t m a Source #
Like parallel but stops the output as soon as the first stream stops.
Pre-release
Nesting
concatM :: (IsStream t, Monad m) => m (t m a) -> t m a Source #
Given a stream value in the underlying monad, lift and join the underlying monad with the stream monad.
>>>concatM = Stream.concat . Stream.fromEffect>>>concatM = Stream.concat . lift -- requires (MonadTrans t)>>>concatM = join . lift -- requires (MonadTrans t, Monad (t m))
Internal
concatMapM :: (IsStream t, Monad m) => (a -> m (t m b)) -> t m a -> t m b Source #
Map a stream producing monadic function on each element of the stream
and then flatten the results into a single stream. Since the stream
generation function is monadic, unlike concatMap, it can produce an
effect at the beginning of each iteration of the inner loop.
Since: 0.6.0
concatMap :: (IsStream t, Monad m) => (a -> t m b) -> t m a -> t m b Source #
Map a stream producing function on each element of the stream and then flatten the results into a single stream.
>>>concatMap f = Stream.concatMapM (return . f)>>>concatMap f = Stream.concatMapWith Stream.serial f>>>concatMap f = Stream.concat . Stream.map f
Since: 0.6.0
splitOnSeq :: (IsStream t, MonadIO m, Storable a, Unbox a, Enum a, Eq a) => Array a -> Fold m a b -> t m a -> t m b Source #
Like splitOn but the separator is a sequence of elements instead of a
single element.
For illustration, let's define a function that operates on pure lists:
>>>splitOnSeq' pat xs = Stream.toList $ Stream.splitOnSeq (Array.fromList pat) Fold.toList (Stream.fromList xs)
>>>splitOnSeq' "" "hello"["h","e","l","l","o"]
>>>splitOnSeq' "hello" ""[""]
>>>splitOnSeq' "hello" "hello"["",""]
>>>splitOnSeq' "x" "hello"["hello"]
>>>splitOnSeq' "h" "hello"["","ello"]
>>>splitOnSeq' "o" "hello"["hell",""]
>>>splitOnSeq' "e" "hello"["h","llo"]
>>>splitOnSeq' "l" "hello"["he","","o"]
>>>splitOnSeq' "ll" "hello"["he","o"]
splitOnSeq is an inverse of intercalate. The following law always holds:
intercalate . splitOnSeq == id
The following law holds when the separator is non-empty and contains none of the elements present in the input lists:
splitOnSeq . intercalate == id
>>>splitOnSeq pat f = Stream.foldManyPost (Fold.takeEndBySeq_ pat f)
Pre-release
Zipping
zipWithM :: (IsStream t, Monad m) => (a -> b -> m c) -> t m a -> t m b -> t m c Source #
Like zipWith but using a monadic zipping function.
Since: 0.4.0
zipWith :: (IsStream t, Monad m) => (a -> b -> c) -> t m a -> t m b -> t m c Source #
Stream a is evaluated first, followed by stream b, the resulting
elements a and b are then zipped using the supplied zip function and the
result c is yielded to the consumer.
If stream a or stream b ends, the zipped stream ends. If stream b ends
first, the element a from previous evaluation of stream a is discarded.
> D.toList $ D.zipWith (+) (D.fromList [1,2,3]) (D.fromList [4,5,6]) [5,7,9]
Since: 0.1.0
Deprecated
class Enum a => Enumerable a where Source #
Types that can be enumerated as a stream. The operations in this type
class are equivalent to those in the Enum type class, except that these
generate a stream instead of a list. Use the functions in
Streamly.Internal.Data.Stream.Enumeration module to define new instances.
Since: 0.6.0
Methods
enumerateFrom :: (IsStream t, Monad m) => a -> t m a Source #
enumerateFrom from generates a stream starting with the element
from, enumerating up to maxBound when the type is Bounded or
generating an infinite stream when the type is not Bounded.
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFrom (0 :: Int) [0,1,2,3]
For Fractional types, enumeration is numerically stable. However, no
overflow or underflow checks are performed.
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFrom 1.1 [1.1,2.1,3.1,4.1]
Since: 0.6.0
enumerateFromTo :: (IsStream t, Monad m) => a -> a -> t m a Source #
Generate a finite stream starting with the element from, enumerating
the type up to the value to. If to is smaller than from then an
empty stream is returned.
>>> Stream.toList $ Stream.enumerateFromTo 0 4 [0,1,2,3,4]
For Fractional types, the last element is equal to the specified to
value after rounding to the nearest integral value.
>>> Stream.toList $ Stream.enumerateFromTo 1.1 4 [1.1,2.1,3.1,4.1] >>> Stream.toList $ Stream.enumerateFromTo 1.1 4.6 [1.1,2.1,3.1,4.1,5.1]
Since: 0.6.0
enumerateFromThen :: (IsStream t, Monad m) => a -> a -> t m a Source #
enumerateFromThen from then generates a stream whose first element
is from, the second element is then and the successive elements are
in increments of then - from. Enumeration can occur downwards or
upwards depending on whether then comes before or after from. For
Bounded types the stream ends when maxBound is reached, for
unbounded types it keeps enumerating infinitely.
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromThen 0 2 [0,2,4,6] >>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromThen 0 (-2) [0,-2,-4,-6]
Since: 0.6.0
enumerateFromThenTo :: (IsStream t, Monad m) => a -> a -> a -> t m a Source #
enumerateFromThenTo from then to generates a finite stream whose
first element is from, the second element is then and the successive
elements are in increments of then - from up to to. Enumeration can
occur downwards or upwards depending on whether then comes before or
after from.
>>> Stream.toList $ Stream.enumerateFromThenTo 0 2 6 [0,2,4,6] >>> Stream.toList $ Stream.enumerateFromThenTo 0 (-2) (-6) [0,-2,-4,-6]
Since: 0.6.0
Instances
Enumerating Bounded Enum Types
enumerateTo :: (IsStream t, Monad m, Bounded a, Enumerable a) => a -> t m a Source #
enumerateFromBounded :: (IsStream t, Monad m, Enumerable a, Bounded a) => a -> t m a Source #
enumerateFromBounded = enumerateFromTo from maxBound
enumerateFrom for Bounded Enum types.
Since: 0.6.0
Enumerating Enum Types not larger than Int
enumerateFromToSmall :: (IsStream t, Monad m, Enum a) => a -> a -> t m a Source #
enumerateFromTo for Enum types not larger than Int.
Since: 0.6.0
enumerateFromThenToSmall :: (IsStream t, Monad m, Enum a) => a -> a -> a -> t m a Source #
enumerateFromThenTo for Enum types not larger than Int.
Since: 0.6.0
enumerateFromThenSmallBounded :: (IsStream t, Monad m, Enumerable a, Bounded a) => a -> a -> t m a Source #
enumerateFromThen for Enum types not larger than Int.
Note: We convert the Enum to Int and enumerate the Int. If a
type is bounded but does not have a Bounded instance then we can go on
enumerating it beyond the legal values of the type, resulting in the failure
of toEnum when converting back to Enum. Therefore we require a Bounded
instance for this function to be safely used.
Since: 0.6.0
Enumerating Bounded Integral Types
enumerateFromIntegral :: (IsStream t, Monad m, Integral a, Bounded a) => a -> t m a Source #
Enumerate an Integral type. enumerateFromIntegral from generates a
stream whose first element is from and the successive elements are in
increments of 1. The stream is bounded by the size of the Integral type.
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromIntegral (0 :: Int) [0,1,2,3]
Since: 0.6.0
enumerateFromThenIntegral :: (IsStream t, Monad m, Integral a, Bounded a) => a -> a -> t m a Source #
Enumerate an Integral type in steps. enumerateFromThenIntegral from
then generates a stream whose first element is from, the second element
is then and the successive elements are in increments of then - from.
The stream is bounded by the size of the Integral type.
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromThenIntegral (0 :: Int) 2 [0,2,4,6] >>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromThenIntegral (0 :: Int) (-2) [0,-2,-4,-6]
Since: 0.6.0
Enumerating Integral Types
enumerateFromToIntegral :: (IsStream t, Monad m, Integral a) => a -> a -> t m a Source #
Enumerate an Integral type up to a given limit.
enumerateFromToIntegral from to generates a finite stream whose first
element is from and successive elements are in increments of 1 up to
to.
>>> Stream.toList $ Stream.enumerateFromToIntegral 0 4 [0,1,2,3,4]
Since: 0.6.0
enumerateFromThenToIntegral :: (IsStream t, Monad m, Integral a) => a -> a -> a -> t m a Source #
Enumerate an Integral type in steps up to a given limit.
enumerateFromThenToIntegral from then to generates a finite stream whose
first element is from, the second element is then and the successive
elements are in increments of then - from up to to.
>>> Stream.toList $ Stream.enumerateFromThenToIntegral 0 2 6 [0,2,4,6] >>> Stream.toList $ Stream.enumerateFromThenToIntegral 0 (-2) (-6) [0,-2,-4,-6]
Since: 0.6.0
Enumerating unbounded Integral Types
enumerateFromStepIntegral :: (IsStream t, Monad m, Integral a) => a -> a -> t m a Source #
enumerateFromStepIntegral from step generates an infinite stream whose
first element is from and the successive elements are in increments of
step.
CAUTION: This function is not safe for finite integral types. It does not check for overflow, underflow or bounds.
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromStepIntegral 0 2 [0,2,4,6] >>> Stream.toList $ Stream.take 3 $ Stream.enumerateFromStepIntegral 0 (-2) [0,-2,-4]
Since: 0.6.0
Enumerating Fractional Types
enumerateFromFractional :: (IsStream t, Monad m, Fractional a) => a -> t m a Source #
Numerically stable enumeration from a Fractional number in steps of size
1. enumerateFromFractional from generates a stream whose first element
is from and the successive elements are in increments of 1. No overflow
or underflow checks are performed.
This is the equivalent to enumFrom for Fractional types. For example:
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromFractional 1.1 [1.1,2.1,3.1,4.1]
Since: 0.6.0
enumerateFromToFractional :: (IsStream t, Monad m, Fractional a, Ord a) => a -> a -> t m a Source #
Numerically stable enumeration from a Fractional number to a given
limit. enumerateFromToFractional from to generates a finite stream whose
first element is from and successive elements are in increments of 1 up
to to.
This is the equivalent of enumFromTo for Fractional types. For
example:
>>> Stream.toList $ Stream.enumerateFromToFractional 1.1 4 [1.1,2.1,3.1,4.1] >>> Stream.toList $ Stream.enumerateFromToFractional 1.1 4.6 [1.1,2.1,3.1,4.1,5.1]
Notice that the last element is equal to the specified to value after
rounding to the nearest integer.
Since: 0.6.0
enumerateFromThenFractional :: (IsStream t, Monad m, Fractional a) => a -> a -> t m a Source #
Numerically stable enumeration from a Fractional number in steps.
enumerateFromThenFractional from then generates a stream whose first
element is from, the second element is then and the successive elements
are in increments of then - from. No overflow or underflow checks are
performed.
This is the equivalent of enumFromThen for Fractional types. For
example:
>>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromThenFractional 1.1 2.1 [1.1,2.1,3.1,4.1] >>> Stream.toList $ Stream.take 4 $ Stream.enumerateFromThenFractional 1.1 (-2.1) [1.1,-2.1,-5.300000000000001,-8.500000000000002]
Since: 0.6.0
enumerateFromThenToFractional :: (IsStream t, Monad m, Fractional a, Ord a) => a -> a -> a -> t m a Source #
Numerically stable enumeration from a Fractional number in steps up to a
given limit. enumerateFromThenToFractional from then to generates a
finite stream whose first element is from, the second element is then
and the successive elements are in increments of then - from up to to.
This is the equivalent of enumFromThenTo for Fractional types. For
example:
>>> Stream.toList $ Stream.enumerateFromThenToFractional 0.1 2 6 [0.1,2.0,3.9,5.799999999999999] >>> Stream.toList $ Stream.enumerateFromThenToFractional 0.1 (-2) (-6) [0.1,-2.0,-4.1000000000000005,-6.200000000000001]
Since: 0.6.0