transient-0.6.3: composing programs with multithreading, events and distributed computing

Transient.Base

Description

Transient provides high level concurrency allowing you to do concurrent processing without requiring any knowledge of threads or synchronization. From the programmer's perspective, the programming model is single threaded. Concurrent tasks are created and composed seamlessly resulting in highly modular and composable concurrent programs. Transient has diverse applications from simple concurrent applications to massively parallel and distributed map-reduce problems. If you are considering Apache Spark or Cloud Haskell then transient might be a simpler yet better solution for you (see transient-universe). Transient makes it easy to write composable event driven reactive UI applications. For example, Axiom is a transient based unified client and server side framework that provides a better programming model and composability compared to frameworks like ReactJS.

# Overview

The TransientIO monad allows you to:

• Split a problem into concurrent task sets
• Compose concurrent task sets using non-determinism
• Collect and combine results of concurrent tasks

You can think of TransientIO as a concurrent list transformer monad with many other features added on top e.g. backtracking, logging and recovery to move computations across machines for distributed processing.

## Non-determinism

In its non-concurrent form, the TransientIO monad behaves exactly like a list transformer monad. It is like a list whose elements are generated using IO effects. It composes in the same way as a list monad. Let's see an example:

import Control.Concurrent (threadDelay)
import System.Random (randomIO)

main = keep $threads 0$ do
x <- waitEvents (randomIO :: IO Int)
liftIO $threadDelay 1000000 liftIO$ putStrLn $show x  keep runs the TransientIO monad. The threads primitive limits the number of threads to force non-concurrent operation. The waitEvents primitive generates values (list elements) in a loop using the randomIO IO action. The above code behaves like a list monad as if we are drawing elements from a list generated by waitEvents. The sequence of actions following waitEvents is executed for each element of the list. We see a random value printed on the screen every second. As you can see this behavior is identical to a list transformer monad. ## Concurrency TransientIO monad is a concurrent list transformer i.e. each element of the generated list can be processed concurrently. In the previous example if we change the number of threads to 10 we can see concurrency in action: ... main = keep$ threads 10 $do ...  Now each element of the list is processed concurrently in a separate thread, up to 10 threads are used. Therefore we see 10 results printed every second instead of 1 in the previous version. In the above examples the list elements are generated using a synchronous IO action. These elements can also be asynchronous events, for example an interactive user input. In transient, the elements of the list are known as tasks. The tasks terminology is general and intuitive in the context of transient as tasks can be triggered by asynchronous events and multiple of them can run simultaneously in an unordered fashion. ## Composing Tasks The type TransientIO a represents a task set with each task in the set returning a value of type a. A task set could be finite or infinite; multiple tasks could run simultaneously. The absence of a task, a void task set or failure is denoted by a special value empty in an Alternative composition, or the stop primitive in a monadic composition. In the transient programming model the programmer thinks in terms of tasks and composes tasks. Whether the tasks run synchronously or concurrently does not matter; concurrency is hidden from the programmer for the most part. In the previous example the code written for a single threaded list transformer works concurrently as well. We have already seen that the Monad instance provides a way to compose the tasks in a sequential, non-deterministic and concurrent manner. When a void task set is encountered, the monad stops processing any further computations as we have nothing to do. The following example does not generate any output after "stop here": main = keep$ threads 0 $do x <- waitEvents (randomIO :: IO Int) liftIO$ threadDelay 1000000
liftIO $putStrLn$ "stop here"
stop
liftIO $putStrLn$ show x


When a task creation primitive creates a task concurrently in a new thread (e.g. waitEvents), it returns a void task set in the current thread making it stop further processing. However, processing resumes from the same point onwards with the same state in the new task threads as and when they are created; as if the current thread along with its state has branched into multiple threads, one for each new task. In the following example you can see that the thread id changes after the waitEvents call:

main = keep $threads 1$ do
liftIO $putStrLn$ "Main thread: " ++ show mainThread
x <- waitEvents (randomIO :: IO Int)

liftIO $threadDelay 1000000 evThread <- liftIO myThreadId liftIO$ putStrLn $"Event thread: " ++ show evThread  Note that if we use threads 0 then the new task thread is the same as the main thread because waitEvents falls back to synchronous non-concurrent mode, and therefore returns a non void task set. In an Alternative composition, when a computation results in empty the next alternative is tried. When a task creation primitive creates a concurrent task, it returns empty allowing tasks to run concurrently when composed with the <|> combinator. The following example combines two single concurrent tasks generated by async: main = keep$ do
x <- event 1 <|> event 2
liftIO $putStrLn$ show x
where event n = async (return n :: IO Int)


Note that availability of threads can impact the behavior of an application. An infinite task set generator (e.g. waitEvents or sample) running synchronously (due to lack of threads) can block all other computations in an Alternative composition. The following example does not trigger the async task unless we increase the number of threads to make waitEvents asynchronous:

main = keep $threads 0$ do
x <- waitEvents (randomIO :: IO Int) <|> async (return 0 :: IO Int)
liftIO $threadDelay 1000000 liftIO$ putStrLn $show x  ## Parallel Map Reduce The following example uses choose to send the items in a list to parallel tasks for squaring and then folds the results of those tasks using collect. import Control.Monad.IO.Class (liftIO) import Data.List (sum) import Transient.Base (keep) import Transient.Indeterminism (choose, collect) main = keep$ do
collect 100 squares >>= liftIO . putStrLn . show . sum
where
squares = do
x <- choose [1..100]
return (x * x)


## State Isolation

State is inherited but never shared. A transient application is written as a composition of task sets. New concurrent tasks can be triggered from inside a task. A new task inherits the state of the monad at the point where it got started. However, the state of a task is always completely isolated from other tasks irrespective of whether it is started in a new thread or not. The state is referentially transparent i.e. any changes to the state creates a new copy of the state. Therefore a programmer does not have to worry about synchronization or unintended side effects.

The monad starts with an empty state. At any point you can add (setData), retrieve (getSData) or delete (delData) a data item to or from the current state. Creation of a task branches the computation, inheriting the previous state, and collapsing (e.g. collect) discards the state of the tasks being collapsed. If you want to use the state in the results you will have to pass it as part of the results of the tasks.

# Reactive Applications

A popular model to handle asynchronous events in imperative languages is the callback model. The control flow of the program is driven by events and callbacks; callbacks are event handlers that are hooked into the event generation code and are invoked every time an event happens. This model makes the overall control flow hard to understand resulting into a "callback hell" because the logic is distributed across various isolated callback handlers, and many different event threads work on the same global state.

Transient provides a better programming model for reactive applications. In contrast to the callback model, transient transparently moves the relevant state to the respective event threads and composes the results to arrive at the new state. The programmer is not aware of the threads, there is no shared state to worry about, and a seamless sequential flow enabling easy reasoning and composable application components. Axiom is a client and server side web UI and reactive application framework built using the transient programming model.

Synopsis

data TransIO a Source #

Instances
 Source # Instance detailsDefined in Transient.Internals Methods(>>=) :: TransIO a -> (a -> TransIO b) -> TransIO b #(>>) :: TransIO a -> TransIO b -> TransIO b #return :: a -> TransIO a #fail :: String -> TransIO a # Source # Instance detailsDefined in Transient.Internals Methodsfmap :: (a -> b) -> TransIO a -> TransIO b #(<$) :: a -> TransIO b -> TransIO a # Source # Instance detailsDefined in Transient.Internals Methodspure :: a -> TransIO a #(<*>) :: TransIO (a -> b) -> TransIO a -> TransIO b #liftA2 :: (a -> b -> c) -> TransIO a -> TransIO b -> TransIO c #(*>) :: TransIO a -> TransIO b -> TransIO b #(<*) :: TransIO a -> TransIO b -> TransIO a # Source # Instance detailsDefined in Transient.Internals MethodsliftIO :: IO a -> TransIO a # Source # Instance detailsDefined in Transient.Internals Methods(<|>) :: TransIO a -> TransIO a -> TransIO a #some :: TransIO a -> TransIO [a] #many :: TransIO a -> TransIO [a] # Source # Instance detailsDefined in Transient.Internals Methodsmplus :: TransIO a -> TransIO a -> TransIO a # Source # Instance detailsDefined in Transient.Internals Methods(**>) :: TransIO a -> TransIO b -> TransIO b Source #(<**) :: TransIO a -> TransIO b -> TransIO a Source #atEnd' :: TransIO a -> TransIO b -> TransIO a Source #(<***) :: TransIO a -> TransIO b -> TransIO a Source #atEnd :: TransIO a -> TransIO b -> TransIO a Source # Source # Instance detailsDefined in Transient.Internals Methodsput :: EventF -> TransIO () #state :: (EventF -> (a, EventF)) -> TransIO a # (Num a, Eq a, Fractional a) => Fractional (TransIO a) Source # Instance detailsDefined in Transient.Internals Methods(/) :: TransIO a -> TransIO a -> TransIO a #recip :: TransIO a -> TransIO a # (Num a, Eq a) => Num (TransIO a) Source # Instance detailsDefined in Transient.Internals Methods(+) :: TransIO a -> TransIO a -> TransIO a #(-) :: TransIO a -> TransIO a -> TransIO a #(*) :: TransIO a -> TransIO a -> TransIO a #negate :: TransIO a -> TransIO a #abs :: TransIO a -> TransIO a #signum :: TransIO a -> TransIO a # Monoid a => Semigroup (TransIO a) Source # Instance detailsDefined in Transient.Internals Methods(<>) :: TransIO a -> TransIO a -> TransIO a #sconcat :: NonEmpty (TransIO a) -> TransIO a #stimes :: Integral b => b -> TransIO a -> TransIO a # Monoid a => Monoid (TransIO a) Source # Instance detailsDefined in Transient.Internals Methodsmappend :: TransIO a -> TransIO a -> TransIO a #mconcat :: [TransIO a] -> TransIO a # # Task Composition Operators (**>) :: AdditionalOperators m => m a -> m b -> m b infixr 1 Source # Run m a discarding its result before running m b. (<**) :: AdditionalOperators m => m a -> m b -> m a infixr 1 Source # Run m b discarding its result, after the whole task set m a is done. (<***) :: AdditionalOperators m => m a -> m b -> m a infixr 1 Source # Run m b discarding its result, once after each task in m a, and once again after the whole task set is done. # Running the monad keep :: Typeable a => TransIO a -> IO (Maybe a) Source # Runs the transient computation in a child thread and keeps the main thread running until all the user threads exit or some thread exit. The main thread provides facilities for accepting keyboard input in a non-blocking but line-oriented manner. The program reads the standard input and feeds it to all the async input consumers (e.g. option and input). All async input consumers contend for each line entered on the standard input and try to read it atomically. When a consumer consumes the input others do not get to see it, otherwise it is left in the buffer for others to consume. If nobody consumes the input, it is discarded. A / in the input line is treated as a newline. When using asynchronous input, regular synchronous IO APIs like getLine cannot be used as they will contend for the standard input along with the asynchronous input thread. Instead you can use the asynchronous input APIs provided by transient. A built-in interactive command handler also reads the stdin asynchronously. All available options waiting for input are displayed when the program is run. The following commands are available: 1. ps: show threads 2. log: inspect the log of a thread 3. end, exit: terminate the program An input not handled by the command handler can be handled by the program. The program's command line is scanned for -p or --path command line options. The arguments to these options are injected into the async input channel as keyboard input to the program. Each line of input is separated by a /. For example:  foo -p ps/end keep' :: Typeable a => TransIO a -> IO (Maybe a) Source # Same as keep but does not read from the standard input, and therefore the async input APIs (option and input) cannot be used in the monad. However, keyboard input can still be passed via command line arguments as described in keep. Useful for debugging or for creating background tasks, as well as to embed the Transient monad inside another computation. It returns either the value returned by exit. or Nothing, when there are no more threads running stop :: Alternative m => m stopped Source # A synonym of empty that can be used in a monadic expression. It stops the computation, which allows the next computation in an Alternative (<|>) composition to run. exit :: Typeable a => a -> TransIO a Source # Exit the main thread with a result, and thus all the Transient threads (and the application if there is no more code) # Asynchronous console IO option :: (Typeable b, Show b, Read b, Eq b) => b -> String -> TransIO b Source # listen stdin and triggers a new task every time the input data matches the first parameter. The value contained by the task is the matched value i.e. the first argument itself. The second parameter is a message to the user for the user. The label is displayed in the console when the option match. input :: (Typeable a, Read a, Show a) => (a -> Bool) -> String -> TransIO a Source # Waits on stdin and return a value when a console input matches the predicate specified in the first argument. The second parameter is a string to be displayed on the console before waiting. input' :: (Typeable a, Read a, Show a) => Maybe a -> (a -> Bool) -> String -> TransIO a Source # input with a default value # Task Creation These primitives are used to create asynchronous and concurrent tasks from an IO action. data StreamData a Source # StreamData represents a task in a task stream being generated. Constructors  SMore a More tasks to come SLast a This is the last task SDone No more tasks, we are done SError SomeException An error occurred Instances  Source # Instance detailsDefined in Transient.Internals Methodsfmap :: (a -> b) -> StreamData a -> StreamData b #(<$) :: a -> StreamData b -> StreamData a # Read a => Read (StreamData a) Source # Instance detailsDefined in Transient.Internals MethodsreadsPrec :: Int -> ReadS (StreamData a) # Show a => Show (StreamData a) Source # Instance detailsDefined in Transient.Internals MethodsshowsPrec :: Int -> StreamData a -> ShowS #show :: StreamData a -> String #showList :: [StreamData a] -> ShowS #

parallel :: IO (StreamData b) -> TransIO (StreamData b) Source #

Run an IO action one or more times to generate a stream of tasks. The IO action returns a StreamData. When it returns an SMore or SLast a new result is returned with the result value. If there are threads available, the res of the computation is executed in a new thread. If the return value is SMore, the action is run again to generate the next result, otherwise task creation stop.

Unless the maximum number of threads (set with threads) has been reached, the task is generated in a new thread and the current thread returns a void task.

async :: IO a -> TransIO a Source #

Run an IO computation asynchronously carrying the result of the computation in a new thread when it completes. If there are no threads available, the async computation and his continuation is executed before any alternative computation. See parallel for notes on the return value.

waitEvents :: IO a -> TransIO a Source #

A task stream generator that produces an infinite stream of tasks by running an IO computation in a loop. A task is triggered carrying the output of the computation. See parallel for notes on the return value.

sample :: Eq a => IO a -> Int -> TransIO a Source #

An stream generator that run an IO computation periodically at the specified time interval. The task carries the result of the computation. A new result is generated only if the output of the computation is different from the previous one. See parallel for notes on the return value.

spawn :: IO a -> TransIO a Source #

spawn = freeThreads . waitEvents

react :: Typeable eventdata => ((eventdata -> IO response) -> IO ()) -> IO response -> TransIO eventdata Source #

Make a transient task generator from an asynchronous callback handler.

The first parameter is a callback. The second parameter is a value to be returned to the callback; if the callback expects no return value it can just be a return (). The callback expects a setter function taking the eventdata as an argument and returning a value to the callback; this function is supplied by react.

Callbacks from foreign code can be wrapped into such a handler and hooked into the transient monad using react. Every time the callback is called it generates a new task for the transient monad.

Runs the rest of the computation in a new thread. Returns empty to the current thread

# State management

setData :: (MonadState EventF m, Typeable a) => a -> m () Source #

setData stores a data item in the monad state which can be retrieved later using getData or getSData. Stored data items are keyed by their data type, and therefore only one item of a given type can be stored. A newtype wrapper can be used to distinguish two data items of the same type.

import Control.Monad.IO.Class (liftIO)
import Transient.Base
import Data.Typeable

data Person = Person
{ name :: String
, age :: Int
} deriving Typeable

main = keep $do setData$ Person Alberto  55
Person name age <- getSData
liftIO $print (name, age)  Retrieve a previously stored data item of the given data type from the monad state. The data type to retrieve is implicitly determined by the data type. If the data item is not found, empty is executed, so the alternative computation will be executed, if any, or Otherwise, the computation will stop.. If you want to print an error message or a default value, you can use an Alternative composition. For example: getSData <|> error "no data of the type desired" getInt = getSData <|> return (0 :: Int) getData :: (MonadState EventF m, Typeable a) => m (Maybe a) Source # Same as getSData but with a more general type. If the data is found, a Just value is returned. Otherwise, a Nothing value is returned. delData :: (MonadState EventF m, Typeable a) => a -> m () Source # Delete the data item of the given type from the monad state. modifyData :: (MonadState EventF m, Typeable a) => (Maybe a -> Maybe a) -> m () Source # Accepts a function which takes the current value of the stored data type and returns the modified value. If the function returns Nothing the value is deleted otherwise updated. modifyData' :: (MonadState EventF m, Typeable a) => (a -> a) -> a -> m a Source # Either modify according with the first parameter or insert according with the second, depending on if the data exist or not. It returns the old value or the new value accordingly. runTransient$ do                   modifyData' (\h -> h ++ " world") "hello new" ;  r <- getSData ; liftIO $putStrLn r -- > "hello new" runTransient$ do setData "hello" ; modifyData' (\h -> h ++ " world") "hello new" ;  r <- getSData ; liftIO $putStrLn r -- > "hello world" try :: TransIO a -> TransIO a Source # Run an action, if it does not succeed, undo any state changes that it might have caused and allow aternative actions to run with the original state setState :: (MonadState EventF m, Typeable a) => a -> m () Source # Same as setData Same as getSData delState :: (MonadState EventF m, Typeable a) => a -> m () Source # Same as delData setRState :: (MonadIO m, MonadState EventF m, Typeable a) => a -> m () Source # mutable state reference that can be updated (similar to STRef in the state monad) They are identified by his type. Initialized the first time it is set. modifyState :: (MonadState EventF m, Typeable a) => (Maybe a -> Maybe a) -> m () Source # Same as modifyData # Thread management threads :: Int -> TransIO a -> TransIO a Source # Sets the maximum number of threads that can be created for the given task set. When set to 0, new tasks start synchronously in the current thread. New threads are created by parallel, and APIs that use parallel. Ensure that at least n threads are available for the current task set. Disable tracking and therefore the ability to terminate the child threads. By default, child threads are terminated automatically when the parent thread dies, or they can be terminated using the kill primitives. Disabling it may improve performance a bit, however, all threads must be well-behaved to exit on their own to avoid a leak. Enable tracking and therefore the ability to terminate the child threads. This is the default but can be used to re-enable tracking if it was previously disabled with freeThreads. Terminate all the child threads in the given task set and continue execution in the current thread. Useful to reap the children when a task is done. Kill all the child threads of the current thread. # Exceptions Exception handlers are implemented using the backtracking mechanism. (see back). Several exception handlers can be installed using onException; handlers are run in reverse order when an exception is raised. The following example prints "3" and then "2". {-# LANGUAGE ScopedTypeVariables #-} import Transient.Base (keep, onException, cutExceptions) import Control.Monad.IO.Class (liftIO) import Control.Exception (ErrorCall) main = keep$ do
onException $\(e:: ErrorCall) -> liftIO$ putStrLn "1"
cutExceptions
onException $\(e:: ErrorCall) -> liftIO$ putStrLn "2"
onException $\(e:: ErrorCall) -> liftIO$ putStrLn "3"
liftIO $error "Raised ErrorCall exception" >> return ()  onException :: Exception e => (e -> TransIO ()) -> TransIO () Source # Install an exception handler. Handlers are executed in reverse (i.e. last in, first out) order when such exception happens in the continuation. Note that multiple handlers can be installed for the same exception type. The semantic is, thus, very different than the one of onException onException' :: Exception e => TransIO a -> (e -> TransIO a) -> TransIO a Source # Delete all the exception handlers registered till now. Use it inside an exception handler. it stop executing any further exception handlers and resume normal execution from this point on. catcht :: Exception e => TransIO b -> (e -> TransIO b) -> TransIO b Source # catch an exception in a Transient block The semantic is the same than catch but the computation and the exception handler can be multirhreaded throwt :: Exception e => e -> TransIO a Source # throw an exception in the Transient monad there is a difference between throw and throwt since the latter preserves the state, while the former does not. Any exception not thrown with throwt does not preserve the state. main= keep$ do
onException $\(e:: SomeException) -> do v <- getState <|> return "hello" liftIO$ print v
setState "world"
throw \$ ErrorCall "asdasd"

the latter print "hello". If you use throwt instead, it prints "world"

# Utilities

genId :: MonadState EventF m => m Int Source #

Generator of identifiers that are unique within the current monadic sequence They are not unique in the whole program.