This section outlines high-level asyncio APIs to work with coroutines and Tasks.
Coroutines declared with the 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
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:
async def 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().
asyncio.run(coro, *, debug=False)Execute the coroutine coro and return the result.
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.
Example:
async def main():
await asyncio.sleep(1)
print('hello')
asyncio.run(main())
New in version 3.7.
Note
The source code for asyncio.run() can be found in
Lib/asyncio/runners.py.
asyncio.create_task(coro, *, name=None)Wrap the coro coroutine into a Task
and schedule its execution. Return the Task object.
If name is not None, it is set as the name of the task using
Task.set_name().
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.
Changed in version 3.8: Added the name parameter.
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.
Deprecated since version 3.8, will be removed in version 3.10: The loop parameter.
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())
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.
Deprecated since version 3.8, will be removed in version 3.10: The loop parameter.
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
Note
If return_exceptions is False, cancelling gather() after it
has been marked done won’t cancel any submitted awaitables.
For instance, gather can be marked done after propagating an
exception to the caller, therefore, calling gather.cancel()
after catching an exception (raised by one of the awaitables) from
gather won’t cancel any other awaitables.
Changed in version 3.7: If the gather itself is cancelled, the cancellation is propagated regardless of return_exceptions.
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
Deprecated since version 3.8, will be removed in version 3.10: The loop parameter.
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.
Deprecated since version 3.8, will be removed in version 3.10: The loop parameter.
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.
asyncio.wait(aws, *, loop=None, timeout=None, return_when=ALL_COMPLETED)Run awaitable objects in the aws iterable concurrently and block until the condition specified by return_when.
Returns two sets of Tasks/Futures: (done, pending).
Usage:
done, pending = await asyncio.wait(aws)
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 |
|---|---|
|
The function will return when any future finishes or is cancelled. |
|
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.
|
|
The function will return when all futures finish or are cancelled. |
Unlike wait_for(), wait() does not cancel the
futures when a timeout occurs.
Deprecated since version 3.8: 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.
Deprecated since version 3.8, will be removed in version 3.10: The loop parameter.
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.
Deprecated since version 3.8: Passing coroutine objects to wait() directly is
deprecated.
asyncio.as_completed(aws, *, loop=None, timeout=None)Run awaitable objects in the aws iterable concurrently. Return an iterator of coroutines. Each coroutine returned can be awaited to get the earliest next result from the iterable of the remaining awaitables.
Raises asyncio.TimeoutError if the timeout occurs before
all Futures are done.
Deprecated since version 3.8, will be removed in version 3.10: The loop parameter.
Example:
for coro in as_completed(aws):
earliest_result = await coro
# ...
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.
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.
asyncio.Task(coro, *, loop=None, name=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.
Changed in version 3.8: Added the name parameter.
Deprecated since version 3.8, will be removed in version 3.10: The loop parameter.
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.
get_coro()Return the coroutine object wrapped by the Task.
New in version 3.8.
get_name()Return the name of the Task.
If no name has been explicitly assigned to the Task, the default asyncio Task implementation generates a default name during instantiation.
New in version 3.8.
set_name(value)Set the name of the Task.
The value argument can be any object, which is then converted to a string.
In the default Task implementation, the name will be visible
in the repr() output of a task object.
New in version 3.8.
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.
Deprecated since version 3.7, will be removed in version 3.9: Do not call this as a task method. Use the asyncio.all_tasks()
function instead.
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.
Deprecated since version 3.7, will be removed in version 3.9: Do not call this as a task method. Use the
asyncio.current_task() function instead.
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.coroutineDecorator 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 should not be used for async def
coroutines.
Deprecated since version 3.8, will be removed in version 3.10: Use async def instead.
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.