Coroutines and Tasks¶

This section outlines high-level asyncio APIs to work with coroutines and Tasks.

Coroutines
Awaitables
Running an asyncio Program
Creating Tasks
Sleeping
Running Tasks Concurrently
Shielding From Cancellation
Timeouts
Waiting Primitives
Scheduling From Other Threads
Introspection
Task Object
Generator-based Coroutines

Coroutines ¶

Coroutines declared with async/await syntax is the preferred way of writing asyncio applications. For example, the following snippet of code (requires Python 3.7+) prints “hello”, waits 1 second, and then prints “world”:

>>> import asyncio

>>> async def main():
...     print('hello')
...     await asyncio.sleep(1)
...     print('world')

>>> asyncio.run(main())
hello
world

Note that simply calling a coroutine will not schedule it to be executed:

>>> main()
<coroutine object main at 0x1053bb7c8>

To actually run a coroutine asyncio provides three main mechanisms:

The asyncio.run() function to run the top-level entry point “main()” function (see the above example.)

Awaiting on a coroutine. The following snippet of code will print “hello” after waiting for 1 second, and then print “world” after waiting for another 2 seconds:

import asyncio
import time

async def say_after(delay, what):
    await asyncio.sleep(delay)
    print(what)

async def main():
    print(f"started at {time.strftime('%X')}")

    await say_after(1, 'hello')
    await say_after(2, 'world')

    print(f"finished at {time.strftime('%X')}")

asyncio.run(main())

Expected output:

started at 17:13:52
hello
world
finished at 17:13:55

The asyncio.create_task() function to run coroutines concurrently as asyncio Tasks.

Let’s modify the above example and run two say_after coroutines concurrently:

async def main():
    task1 = asyncio.create_task(
        say_after(1, 'hello'))

    task2 = asyncio.create_task(
        say_after(2, 'world'))

    print(f"started at {time.strftime('%X')}")

    # Wait until both tasks are completed (should take
    # around 2 seconds.)
    await task1
    await task2

    print(f"finished at {time.strftime('%X')}")

Note that expected output now shows that the snippet runs 1 second faster than before:

started at 17:14:32
hello
world
finished at 17:14:34

Awaitables ¶

We say that an object is an awaitable object if it can be used in an await expression. Many asyncio APIs are designed to accept awaitables.

There are three main types of awaitable objects: coroutines, Tasks, and Futures.

Coroutines

Python coroutines are awaitables and therefore can be awaited from other coroutines:

import asyncio

async def nested():
    return 42

async def main():
    # Nothing happens if we just call "nested()".
    # A coroutine object is created but not awaited,
    # so it *won't run at all*.
    nested()

    # Let's do it differently now and await it:
    print(await nested())  # will print "42".

asyncio.run(main())

Important

In this documentation the term “coroutine” can be used for two closely related concepts:

a coroutine function: an async def function;
a coroutine object: an object returned by calling a coroutine function.

asyncio also supports legacy generator-based coroutines.

Tasks

Tasks are used to schedule coroutines concurrently.

When a coroutine is wrapped into a Task with functions like asyncio.create_task() the coroutine is automatically scheduled to run soon:

import asyncio

async def nested():
    return 42

async def main():
    # Schedule nested() to run soon concurrently
    # with "main()".
    task = asyncio.create_task(nested())

    # "task" can now be used to cancel "nested()", or
    # can simply be awaited to wait until it is complete:
    await task

asyncio.run(main())

Futures

A Future is a special low-level awaitable object that represents an eventual result of an asynchronous operation.

When a Future object is awaited it means that the coroutine will wait until the Future is resolved in some other place.

Future objects in asyncio are needed to allow callback-based code to be used with async/await.

Normally there is no need to create Future objects at the application level code.

Future objects, sometimes exposed by libraries and some asyncio APIs, can be awaited:

async def main():
    await function_that_returns_a_future_object()

    # this is also valid:
    await asyncio.gather(
        function_that_returns_a_future_object(),
        some_python_coroutine()
    )

A good example of a low-level function that returns a Future object is loop.run_in_executor().

Running an asyncio Program ¶

asyncio.run(coro, *, debug=False)¶

This function runs the passed coroutine, taking care of managing the asyncio event loop and finalizing asynchronous generators.

This function cannot be called when another asyncio event loop is running in the same thread.

If debug is True, the event loop will be run in debug mode.

This function always creates a new event loop and closes it at the end. It should be used as a main entry point for asyncio programs, and should ideally only be called once.

New in version 3.7: Important: this function has been added to asyncio in Python 3.7 on a provisional basis.

Creating Tasks ¶

asyncio.create_task(coro)¶

Wrap the coro coroutine into a Task and schedule its execution. Return the Task object.

The task is executed in the loop returned by get_running_loop(), RuntimeError is raised if there is no running loop in current thread.

This function has been added in Python 3.7. Prior to Python 3.7, the low-level asyncio.ensure_future() function can be used instead:

async def coro():
    ...

# In Python 3.7+
task = asyncio.create_task(coro())
...

# This works in all Python versions but is less readable
task = asyncio.ensure_future(coro())
...

New in version 3.7.

Sleeping ¶

coroutine asyncio.sleep(delay, result=None, *, loop=None)¶

Block for delay seconds.

If result is provided, it is returned to the caller when the coroutine completes.

sleep() always suspends the current task, allowing other tasks to run.

The loop argument is deprecated and scheduled for removal in Python 3.10.

Example of coroutine displaying the current date every second for 5 seconds:

import asyncio
import datetime

async def display_date():
    loop = asyncio.get_running_loop()
    end_time = loop.time() + 5.0
    while True:
        print(datetime.datetime.now())
        if (loop.time() + 1.0) >= end_time:
            break
        await asyncio.sleep(1)

asyncio.run(display_date())

Running Tasks Concurrently ¶

awaitable asyncio.gather(*aws, loop=None, return_exceptions=False)¶

Run awaitable objects in the aws sequence concurrently.

If any awaitable in aws is a coroutine, it is automatically scheduled as a Task.

If all awaitables are completed successfully, the result is an aggregate list of returned values. The order of result values corresponds to the order of awaitables in aws.

If return_exceptions is False (default), the first raised exception is immediately propagated to the task that awaits on gather(). Other awaitables in the aws sequence won’t be cancelled and will continue to run.

If return_exceptions is True, exceptions are treated the same as successful results, and aggregated in the result list.

If gather() is cancelled, all submitted awaitables (that have not completed yet) are also cancelled.

If any Task or Future from the aws sequence is cancelled, it is treated as if it raised CancelledError – the gather() call is not cancelled in this case. This is to prevent the cancellation of one submitted Task/Future to cause other Tasks/Futures to be cancelled.

Example:

import asyncio

async def factorial(name, number):
    f = 1
    for i in range(2, number + 1):
        print(f"Task {name}: Compute factorial({i})...")
        await asyncio.sleep(1)
        f *= i
    print(f"Task {name}: factorial({number}) = {f}")

async def main():
    # Schedule three calls *concurrently*:
    await asyncio.gather(
        factorial("A", 2),
        factorial("B", 3),
        factorial("C", 4),
    )

asyncio.run(main())

# Expected output:
#
#     Task A: Compute factorial(2)...
#     Task B: Compute factorial(2)...
#     Task C: Compute factorial(2)...
#     Task A: factorial(2) = 2
#     Task B: Compute factorial(3)...
#     Task C: Compute factorial(3)...
#     Task B: factorial(3) = 6
#     Task C: Compute factorial(4)...
#     Task C: factorial(4) = 24

Changed in version 3.7: If the gather itself is cancelled, the cancellation is propagated regardless of return_exceptions.

Shielding From Cancellation ¶

awaitable asyncio.shield(aw, *, loop=None)¶

Protect an awaitable object from being cancelled.

If aw is a coroutine it is automatically scheduled as a Task.

The statement:

res = await shield(something())

is equivalent to:

res = await something()

except that if the coroutine containing it is cancelled, the Task running in something() is not cancelled. From the point of view of something(), the cancellation did not happen. Although its caller is still cancelled, so the “await” expression still raises a CancelledError.

If something() is cancelled by other means (i.e. from within itself) that would also cancel shield().

If it is desired to completely ignore cancellation (not recommended) the shield() function should be combined with a try/except clause, as follows:

try:
    res = await shield(something())
except CancelledError:
    res = None

Timeouts ¶

coroutine asyncio.wait_for(aw, timeout, *, loop=None)¶

Wait for the aw awaitable to complete with a timeout.

If aw is a coroutine it is automatically scheduled as a Task.

timeout can either be None or a float or int number of seconds to wait for. If timeout is None, block until the future completes.

If a timeout occurs, it cancels the task and raises asyncio.TimeoutError.

To avoid the task cancellation, wrap it in shield().

The function will wait until the future is actually cancelled, so the total wait time may exceed the timeout.

If the wait is cancelled, the future aw is also cancelled.

The loop argument is deprecated and scheduled for removal in Python 3.10.

Example:

async def eternity():
    # Sleep for one hour
    await asyncio.sleep(3600)
    print('yay!')

async def main():
    # Wait for at most 1 second
    try:
        await asyncio.wait_for(eternity(), timeout=1.0)
    except asyncio.TimeoutError:
        print('timeout!')

asyncio.run(main())

# Expected output:
#
#     timeout!

Changed in version 3.7: When aw is cancelled due to a timeout, wait_for waits for aw to be cancelled. Previously, it raised asyncio.TimeoutError immediately.

Waiting Primitives ¶

coroutine asyncio.wait(aws, *, loop=None, timeout=None, return_when=ALL_COMPLETED)¶

Run awaitable objects in the aws set concurrently and block until the condition specified by return_when.

If any awaitable in aws is a coroutine, it is automatically scheduled as a Task. Passing coroutines objects to wait() directly is deprecated as it leads to confusing behavior.

Returns two sets of Tasks/Futures: (done, pending).

Usage:

done, pending = await asyncio.wait(aws)

The loop argument is deprecated and scheduled for removal in Python 3.10.

timeout (a float or int), if specified, can be used to control the maximum number of seconds to wait before returning.

Note that this function does not raise asyncio.TimeoutError. Futures or Tasks that aren’t done when the timeout occurs are simply returned in the second set.

return_when indicates when this function should return. It must be one of the following constants:

Constant	Description
`FIRST_COMPLETED`	The function will return when any future finishes or is cancelled.
`FIRST_EXCEPTION`	The function will return when any future finishes by raising an exception. If no future raises an exception then it is equivalent to `ALL_COMPLETED`.
`ALL_COMPLETED`	The function will return when all futures finish or are cancelled.

Unlike wait_for(), wait() does not cancel the futures when a timeout occurs.

Note

wait() schedules coroutines as Tasks automatically and later returns those implicitly created Task objects in (done, pending) sets. Therefore the following code won’t work as expected:

async def foo():
    return 42

coro = foo()
done, pending = await asyncio.wait({coro})

if coro in done:
    # This branch will never be run!

Here is how the above snippet can be fixed:

async def foo():
    return 42

task = asyncio.create_task(foo())
done, pending = await asyncio.wait({task})

if task in done:
    # Everything will work as expected now.

Passing coroutine objects to wait() directly is deprecated.

asyncio.as_completed(aws, *, loop=None, timeout=None)¶

Run awaitable objects in the aws set concurrently. Return an iterator of Future objects. Each Future object returned represents the earliest result from the set of the remaining awaitables.

Raises asyncio.TimeoutError if the timeout occurs before all Futures are done.

Example:

for f in as_completed(aws):
    earliest_result = await f
    # ...

Scheduling From Other Threads ¶

asyncio.run_coroutine_threadsafe(coro, loop)¶

Submit a coroutine to the given event loop. Thread-safe.

Return a concurrent.futures.Future to wait for the result from another OS thread.

This function is meant to be called from a different OS thread than the one where the event loop is running. Example:

# Create a coroutine
coro = asyncio.sleep(1, result=3)

# Submit the coroutine to a given loop
future = asyncio.run_coroutine_threadsafe(coro, loop)

# Wait for the result with an optional timeout argument
assert future.result(timeout) == 3

If an exception is raised in the coroutine, the returned Future will be notified. It can also be used to cancel the task in the event loop:

try:
    result = future.result(timeout)
except asyncio.TimeoutError:
    print('The coroutine took too long, cancelling the task...')
    future.cancel()
except Exception as exc:
    print(f'The coroutine raised an exception: {exc!r}')
else:
    print(f'The coroutine returned: {result!r}')

See the concurrency and multithreading section of the documentation.

Unlike other asyncio functions this function requires the loop argument to be passed explicitly.

New in version 3.5.1.

Introspection ¶

asyncio.current_task(loop=None)¶

Return the currently running Task instance, or None if no task is running.

If loop is None get_running_loop() is used to get the current loop.

New in version 3.7.

asyncio.all_tasks(loop=None)¶

Return a set of not yet finished Task objects run by the loop.

If loop is None, get_running_loop() is used for getting current loop.

New in version 3.7.

Task Object ¶

class asyncio.Task(coro, *, loop=None)¶

A Future-like object that runs a Python coroutine. Not thread-safe.

Tasks are used to run coroutines in event loops. If a coroutine awaits on a Future, the Task suspends the execution of the coroutine and waits for the completion of the Future. When the Future is done, the execution of the wrapped coroutine resumes.

Event loops use cooperative scheduling: an event loop runs one Task at a time. While a Task awaits for the completion of a Future, the event loop runs other Tasks, callbacks, or performs IO operations.

Use the high-level asyncio.create_task() function to create Tasks, or the low-level loop.create_task() or ensure_future() functions. Manual instantiation of Tasks is discouraged.

To cancel a running Task use the cancel() method. Calling it will cause the Task to throw a CancelledError exception into the wrapped coroutine. If a coroutine is awaiting on a Future object during cancellation, the Future object will be cancelled.

cancelled() can be used to check if the Task was cancelled. The method returns True if the wrapped coroutine did not suppress the CancelledError exception and was actually cancelled.

asyncio.Task inherits from Future all of its APIs except Future.set_result() and Future.set_exception().

Tasks support the contextvars module. When a Task is created it copies the current context and later runs its coroutine in the copied context.

Changed in version 3.7: Added support for the contextvars module.

cancel()¶

Request the Task to be cancelled.

This arranges for a CancelledError exception to be thrown into the wrapped coroutine on the next cycle of the event loop.

The coroutine then has a chance to clean up or even deny the request by suppressing the exception with a try … … except CancelledError … finally block. Therefore, unlike Future.cancel(), Task.cancel() does not guarantee that the Task will be cancelled, although suppressing cancellation completely is not common and is actively discouraged.

The following example illustrates how coroutines can intercept the cancellation request:

async def cancel_me():
    print('cancel_me(): before sleep')

    try:
        # Wait for 1 hour
        await asyncio.sleep(3600)
    except asyncio.CancelledError:
        print('cancel_me(): cancel sleep')
        raise
    finally:
        print('cancel_me(): after sleep')

async def main():
    # Create a "cancel_me" Task
    task = asyncio.create_task(cancel_me())

    # Wait for 1 second
    await asyncio.sleep(1)

    task.cancel()
    try:
        await task
    except asyncio.CancelledError:
        print("main(): cancel_me is cancelled now")

asyncio.run(main())

# Expected output:
#
#     cancel_me(): before sleep
#     cancel_me(): cancel sleep
#     cancel_me(): after sleep
#     main(): cancel_me is cancelled now

cancelled()¶

Return True if the Task is cancelled.

The Task is cancelled when the cancellation was requested with cancel() and the wrapped coroutine propagated the CancelledError exception thrown into it.

done()¶

Return True if the Task is done.

A Task is done when the wrapped coroutine either returned a value, raised an exception, or the Task was cancelled.

result()¶

Return the result of the Task.

If the Task is done, the result of the wrapped coroutine is returned (or if the coroutine raised an exception, that exception is re-raised.)

If the Task has been cancelled, this method raises a CancelledError exception.

If the Task’s result isn’t yet available, this method raises a InvalidStateError exception.

exception()¶

Return the exception of the Task.

If the wrapped coroutine raised an exception that exception is returned. If the wrapped coroutine returned normally this method returns None.

If the Task has been cancelled, this method raises a CancelledError exception.

If the Task isn’t done yet, this method raises an InvalidStateError exception.

add_done_callback(callback, *, context=None)¶

Add a callback to be run when the Task is done.

This method should only be used in low-level callback-based code.

See the documentation of Future.add_done_callback() for more details.

remove_done_callback(callback)¶

Remove callback from the callbacks list.

This method should only be used in low-level callback-based code.

See the documentation of Future.remove_done_callback() for more details.

get_stack(*, limit=None)¶

Return the list of stack frames for this Task.

If the wrapped coroutine is not done, this returns the stack where it is suspended. If the coroutine has completed successfully or was cancelled, this returns an empty list. If the coroutine was terminated by an exception, this returns the list of traceback frames.

The frames are always ordered from oldest to newest.

Only one stack frame is returned for a suspended coroutine.

The optional limit argument sets the maximum number of frames to return; by default all available frames are returned. The ordering of the returned list differs depending on whether a stack or a traceback is returned: the newest frames of a stack are returned, but the oldest frames of a traceback are returned. (This matches the behavior of the traceback module.)

print_stack(*, limit=None, file=None)¶

Print the stack or traceback for this Task.

This produces output similar to that of the traceback module for the frames retrieved by get_stack().

The limit argument is passed to get_stack() directly.

The file argument is an I/O stream to which the output is written; by default output is written to sys.stderr.

classmethod all_tasks(loop=None)¶

Return a set of all tasks for an event loop.

By default all tasks for the current event loop are returned. If loop is None, the get_event_loop() function is used to get the current loop.

This method is deprecated and will be removed in Python 3.9. Use the asyncio.all_tasks() function instead.

classmethod current_task(loop=None)¶

Return the currently running task or None.

If loop is None, the get_event_loop() function is used to get the current loop.

This method is deprecated and will be removed in Python 3.9. Use the asyncio.current_task() function instead.

Generator-based Coroutines ¶

Note

Support for generator-based coroutines is deprecated and is scheduled for removal in Python 3.10.

Generator-based coroutines predate async/await syntax. They are Python generators that use yield from expressions to await on Futures and other coroutines.

Generator-based coroutines should be decorated with @asyncio.coroutine, although this is not enforced.

@asyncio.coroutine¶

Decorator to mark generator-based coroutines.

This decorator enables legacy generator-based coroutines to be compatible with async/await code:

@asyncio.coroutine
def old_style_coroutine():
    yield from asyncio.sleep(1)

async def main():
    await old_style_coroutine()

This decorator is deprecated and is scheduled for removal in Python 3.10.

This decorator should not be used for async def coroutines.

asyncio.iscoroutine(obj)¶

Return True if obj is a coroutine object.

This method is different from inspect.iscoroutine() because it returns True for generator-based coroutines.

asyncio.iscoroutinefunction(func)¶

Return True if func is a coroutine function.

This method is different from inspect.iscoroutinefunction() because it returns True for generator-based coroutine functions decorated with @coroutine.

Coroutines and Tasks¶

Coroutines ¶

Awaitables ¶

Running an asyncio Program ¶

Creating Tasks ¶

Sleeping ¶

Running Tasks Concurrently ¶

Shielding From Cancellation ¶

Timeouts ¶

Waiting Primitives ¶

Scheduling From Other Threads ¶

Introspection ¶

Task Object ¶

Generator-based Coroutines ¶

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