A monad that can perform concurrent or parallel IO operations. Streams that can be composed concurrently require the underlying monad to be MonadAsync.

Since: 0.1.0

Deep serial composition or serial composition with depth first traversal. The Semigroup instance of SerialT appends two streams serially in a depth first manner, yielding all elements from the first stream, and then all elements from the second stream.

import Streamly
import qualified Streamly.Prelude as S

main = (toList . serially $ (fromFoldable [1,2]) <> (fromFoldable [3,4])) >>= print

[1,2,3,4]

The Monad instance runs the monadic continuation for each element of the stream, serially.

main = runStream . serially $ do
    x <- return 1 <> return 2
    S.yieldM $ print x

1
2

SerialT nests streams serially in a depth first manner.

main = runStream . serially $ do
    x <- return 1 <> return 2
    y <- return 3 <> return 4
    S.yieldM $ print (x, y)

(1,3)
(1,4)
(2,3)
(2,4)

This behavior of SerialT is exactly like a list transformer. We call the monadic code being run for each element of the stream a monadic continuation. In imperative paradigm we can think of this composition as nested for loops and the monadic continuation is the body of the loop. The loop iterates for all elements of the stream.

The serially combinator can be omitted as the default stream type is SerialT. Note that serial composition with depth first traversal can be used to combine an infinite number of streams as it explores only one stream at a time.

Since: 0.2.0

Wide serial composition or serial composition with a breadth first traversal. The Semigroup instance of WSerialT traverses the two streams in a breadth first manner. In other words, it interleaves two streams, yielding one element from each stream alternately.

import Streamly
import qualified Streamly.Prelude as S

main = (toList . wSerially $ (fromFoldable [1,2]) <> (fromFoldable [3,4])) >>= print

[1,3,2,4]

Similarly, the Monad instance interleaves the iterations of the inner and the outer loop, nesting loops in a breadth first manner.

main = runStream . wSerially $ do
    x <- return 1 <> return 2
    y <- return 3 <> return 4
    S.yieldM $ print (x, y)

(1,3)
(2,3)
(1,4)
(2,4)

Note that a serial composition with breadth first traversal can only combine a finite number of streams as it needs to retain state for each unfinished stream.

Since: 0.2.0

Deep ahead composition or ahead composition with depth first traversal. The semigroup composition of AheadT appends streams in a depth first manner just like SerialT except that it can produce elements concurrently ahead of time. It is like AsyncT except that AsyncT produces the output as it arrives whereas AheadT orders the output in the traversal order.

main = (toList . aheadly $ (fromFoldable [1,2]) <> (fromFoldable [3,4])) >>= print

[1,2,3,4]

Any exceptions generated by a constituent stream are propagated to the output stream.

Similarly, the monad instance of AheadT may run each iteration concurrently ahead of time but presents the results in the same order as SerialT.

import Streamly
import qualified Streamly.Prelude as S
import Control.Concurrent

main = runStream . aheadly $ do
    n <- return 3 <> return 2 <> return 1
    S.yieldM $ do
         threadDelay (n * 1000000)
         myThreadId >>= \tid -> putStrLn (show tid ++ ": Delay " ++ show n)

ThreadId 40: Delay 1
ThreadId 39: Delay 2
ThreadId 38: Delay 3

All iterations may run in the same thread if they do not block.

Note that ahead composition with depth first traversal can be used to combine infinite number of streams as it explores only a bounded number of streams at a time.

Since: 0.3.0

Deep async composition or async composition with depth first traversal. In a left to right Semigroup composition it tries to yield elements from the left stream as long as it can, but it can run the right stream in parallel if it needs to, based on demand. The right stream can be run if the left stream blocks on IO or cannot produce elements fast enough for the consumer.

main = (toList . asyncly $ (fromFoldable [1,2]) <> (fromFoldable [3,4])) >>= print

[1,2,3,4]

Any exceptions generated by a constituent stream are propagated to the output stream. The output and exceptions from a single stream are guaranteed to arrive in the same order in the resulting stream as they were generated in the input stream. However, the relative ordering of elements from different streams in the resulting stream can vary depending on scheduling and generation delays.

Similarly, the monad instance of AsyncT may run each iteration concurrently based on demand. More concurrent iterations are started only if the previous iterations are not able to produce enough output for the consumer.

import Streamly
import qualified Streamly.Prelude as S
import Control.Concurrent

main = runStream . asyncly $ do
    n <- return 3 <> return 2 <> return 1
    S.yieldM $ do
         threadDelay (n * 1000000)
         myThreadId >>= \tid -> putStrLn (show tid ++ ": Delay " ++ show n)

ThreadId 40: Delay 1
ThreadId 39: Delay 2
ThreadId 38: Delay 3

All iterations may run in the same thread if they do not block.

Note that async composition with depth first traversal can be used to combine infinite number of streams as it explores only a bounded number of streams at a time.

Since: 0.1.0

Wide async composition or async composition with breadth first traversal. The Semigroup instance of WAsyncT concurrently traverses the composed streams using a depth first travesal or in a round robin fashion, yielding elements from both streams alternately.

main = (toList . wAsyncly $ (fromFoldable [1,2]) <> (fromFoldable [3,4])) >>= print

[1,3,2,4]

Any exceptions generated by a constituent stream are propagated to the output stream. The output and exceptions from a single stream are guaranteed to arrive in the same order in the resulting stream as they were generated in the input stream. However, the relative ordering of elements from different streams in the resulting stream can vary depending on scheduling and generation delays.

Similarly, the Monad instance of WAsyncT runs all iterations fairly concurrently using a round robin scheduling.

import Streamly
import qualified Streamly.Prelude as S
import Control.Concurrent

main = runStream . wAsyncly $ do
    n <- return 3 <> return 2 <> return 1
    S.yieldM $ do
         threadDelay (n * 1000000)
         myThreadId >>= \tid -> putStrLn (show tid ++ ": Delay " ++ show n)

ThreadId 40: Delay 1
ThreadId 39: Delay 2
ThreadId 38: Delay 3

Unlike AsyncT all iterations are guaranteed to run fairly concurrently, unconditionally.

Note that async composition with breadth first traversal can only combine a finite number of streams as it needs to retain state for each unfinished stream.

Since: 0.2.0

Async composition with simultaneous traversal of all streams.

The Semigroup instance of ParallelT concurrently merges two streams, running both strictly concurrently and yielding elements from both streams as they arrive. When multiple streams are combined using ParallelT each one is evaluated in its own thread and the results produced are presented in the combined stream on a first come first serve basis.

AsyncT and WAsyncT are concurrent lookahead streams each with a specific type of consumption pattern (depth first or breadth first). Since they are lookahead, they may introduce certain default latency in starting more concurrent tasks for efficiency reasons or may put a default limitation on the resource consumption (e.g. number of concurrent threads for lookahead). If we look at the implementation detail, they both can share a pool of worker threads to evaluate the streams in the desired pattern and at the desired rate. However, ParallelT uses a separate runtime thread to evaluate each stream.

WAsyncT is similar to ParallelT, as both of them evaluate the constituent streams fairly in a round robin fashion. However, the key difference is that WAsyncT is lazy or pull driven whereas ParallelT is strict or push driven. ParallelT immediately starts concurrent evaluation of both the streams (in separate threads) and later picks the results whereas WAsyncT may wait for a certain latency threshold before initiating concurrent evaluation of the next stream. The concurrent scheduling of the next stream or the degree of concurrency is driven by the feedback from the consumer. In case of ParallelT each stream is evaluated in a separate thread and results are pushed to a shared output buffer, the evaluation rate is controlled by blocking when the buffer is full.

Concurrent lookahead streams are generally more efficient than ParallelT and can work pretty efficiently even for smaller tasks because they do not necessarily use a separate thread for each task. So they should be preferred over ParallelT especially when efficiency is a concern and simultaneous strict evaluation is not a requirement. ParallelT is useful for cases when the streams are required to be evaluated simultaneously irrespective of how the consumer consumes them e.g. when we want to race two tasks and want to start both strictly at the same time or if we have timers in the parallel tasks and our results depend on the timers being started at the same time. We can say that ParallelT is almost the same (modulo some implementation differences) as WAsyncT when the latter is used with unlimited lookahead and zero latency in initiating lookahead.

main = (toList . parallely $ (fromFoldable [1,2]) <> (fromFoldable [3,4])) >>= print

[1,3,2,4]

When streams with more than one element are merged, it yields whichever stream yields first without any bias, unlike the Async style streams.

Any exceptions generated by a constituent stream are propagated to the output stream. The output and exceptions from a single stream are guaranteed to arrive in the same order in the resulting stream as they were generated in the input stream. However, the relative ordering of elements from different streams in the resulting stream can vary depending on scheduling and generation delays.

Similarly, the Monad instance of ParallelT runs all iterations of the loop concurrently.

import Streamly
import qualified Streamly.Prelude as S
import Control.Concurrent

main = runStream . parallely $ do
    n <- return 3 <> return 2 <> return 1
    S.yieldM $ do
         threadDelay (n * 1000000)
         myThreadId >>= \tid -> putStrLn (show tid ++ ": Delay " ++ show n)

ThreadId 40: Delay 1
ThreadId 39: Delay 2
ThreadId 38: Delay 3

Note that parallel composition can only combine a finite number of streams as it needs to retain state for each unfinished stream.

Since: 0.1.0

The applicative instance of ZipSerialM zips a number of streams serially i.e. it produces one element from each stream serially and then zips all those elements.

main = (toList . zipSerially $ (,,) <$> s1 <*> s2 <*> s3) >>= print
    where s1 = fromFoldable [1, 2]
          s2 = fromFoldable [3, 4]
          s3 = fromFoldable [5, 6]

[(1,3,5),(2,4,6)]

The Semigroup instance of this type works the same way as that of SerialT.

Since: 0.2.0

Like ZipSerialM but zips in parallel, it generates all the elements to be zipped concurrently.

main = (toList . zipAsyncly $ (,,) <$> s1 <*> s2 <*> s3) >>= print
    where s1 = fromFoldable [1, 2]
          s2 = fromFoldable [3, 4]
          s3 = fromFoldable [5, 6]

[(1,3,5),(2,4,6)]

The Semigroup instance of this type works the same way as that of SerialT.

Since: 0.2.0

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 . asyncly.

Since: 0.2.0

Parallel function application operator for streams; just like the regular function application operator $ except that it is concurrent. The following code prints a value every second even though each stage adds a 1 second delay.

runStream $
   S.mapM (\x -> threadDelay 1000000 >> print x)
     |$ S.repeatM (threadDelay 1000000 >> return 1)

Concurrent

Since: 0.3.0

Parallel reverse function application operator for streams; just like the regular reverse function application operator & except that it is concurrent.

runStream $
      S.repeatM (threadDelay 1000000 >> return 1)
   |& S.mapM (\x -> threadDelay 1000000 >> print x)

Concurrent

Since: 0.3.0

Parallel function application operator; applies a run or fold function to a stream such that the fold consumer and the stream producer run in parallel. A run or fold function reduces the stream to a value in the underlying monad. The . at the end of the operator is a mnemonic for termination of the stream.

   S.foldlM' (\_ a -> threadDelay 1000000 >> print a) ()
      |$. S.repeatM (threadDelay 1000000 >> return 1)

Concurrent

Since: 0.3.0

Parallel reverse function application operator for applying a run or fold functions to a stream. Just like |$. except that the operands are reversed.

       S.repeatM (threadDelay 1000000 >> return 1)
   |&. S.foldlM' (\_ a -> threadDelay 1000000 >> print a) ()

Concurrent

Since: 0.3.0

Make a stream asynchronous, triggers the computation and returns a stream in the underlying monad representing the output generated by the original computation. The returned action is exhaustible and must be drained once. If not drained fully we may have a thread blocked forever and once exhausted it will always return empty.

Since: 0.2.0

Polymorphic version of the Semigroup operation <> of SerialT. Appends two streams sequentially, yielding all elements from the first stream, and then all elements from the second stream.

Since: 0.2.0

Polymorphic version of the Semigroup operation <> of WSerialT. Interleaves two streams, yielding one element from each stream alternately.

Since: 0.2.0

Polymorphic version of the Semigroup operation <> of AheadT. Merges two streams sequentially but with concurrent lookahead.

Since: 0.3.0

Polymorphic version of the Semigroup operation <> of AsyncT. Merges two streams possibly concurrently, preferring the elements from the left one when available.

Since: 0.2.0

Polymorphic version of the Semigroup operation <> of WAsyncT. Merges two streams concurrently choosing elements from both fairly.

Since: 0.2.0

Polymorphic version of the Semigroup operation <> of ParallelT Merges two streams concurrently.

Since: 0.2.0

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.

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

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

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

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 maxThreads limit
• The maxBuffer limit
• The maximum rate that the stream producer can achieve
• The maximum rate that the stream consumer can achieve

Since: 0.5.0

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

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

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

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

A variant of fold that allows you to fold a Foldable container of streams using the specified stream sum operation.

foldWith async $ map return [1..3]

Since: 0.1.0

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 sum operation.

foldMapWith async return [1..3]

Since: 0.1.0

Like foldMapWith but with the last two arguments reversed i.e. the monadic streaming function is the last argument.

Since: 0.1.0

Class of types that can represent a stream of elements of some type a in some monad m.

Since: 0.2.0

Fix the type of a polymorphic stream as SerialT.

Since: 0.1.0

Fix the type of a polymorphic stream as WSerialT.

Since: 0.2.0

Fix the type of a polymorphic stream as AsyncT.

Since: 0.1.0

Fix the type of a polymorphic stream as AheadT.

Since: 0.3.0

Fix the type of a polymorphic stream as WAsyncT.

Since: 0.2.0

Fix the type of a polymorphic stream as ParallelT.

Since: 0.1.0

Fix the type of a polymorphic stream as ZipSerialM.

Since: 0.2.0

Fix the type of a polymorphic stream as ZipAsyncM.

Since: 0.2.0

Adapt any specific stream type to any other specific stream type.

Since: 0.1.0

A serial IO stream of elements of type a. See SerialT documentation for more details.

Since: 0.2.0

An interleaving serial IO stream of elements of type a. See WSerialT documentation for more details.

Since: 0.2.0

A serial IO stream of elements of type a with concurrent lookahead. See AheadT documentation for more details.

Since: 0.3.0

A demand driven left biased parallely composing IO stream of elements of type a. See AsyncT documentation for more details.

Since: 0.2.0

A round robin parallely composing IO stream of elements of type a. See WAsyncT documentation for more details.

Since: 0.2.0

A parallely composing IO stream of elements of type a. See ParallelT documentation for more details.

Since: 0.2.0

An IO stream whose applicative instance zips streams serially.

Since: 0.2.0

An IO stream whose applicative instance zips streams wAsyncly.

Since: 0.2.0

The class of semigroups (types with an associative binary operation).

Instances should satisfy the associativity law:

• x <> (y <> z) = (x <> y) <> z

Since: base-4.9.0.0

Same as IsStream.

Since: 0.1.0

Same as runStream

Since: 0.1.0

Same as runStream.

Since: 0.1.0

Same as runStream . wSerially.

Since: 0.1.0

Same as runStream . asyncly.

Since: 0.1.0

Same as runStream . parallely.

Since: 0.1.0

Same as runStream . zipping.

Since: 0.1.0

Same as runStream . zippingAsync.

Since: 0.1.0

Since: 0.1.0