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

* Running in Threads

* Scheduling From Other Threads

* Introspection

* Task Object

* Generator-based Coroutines


Coroutines
==========

*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


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)

   Execute the *coroutine* *coro* and return the result.

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

   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.

   Changed in version 3.9: Updated to use
   "loop.shutdown_default_executor()".

   Note:

     The source code for "asyncio.run()" can be found in
     Lib/asyncio/runners.py.


Creating Tasks
==============

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())
      ...

   Important:

     Save a reference to the result of this function, to avoid a task
     disappearing mid execution.

   New in version 3.7.

   Changed in version 3.8: Added the *name* parameter.


Sleeping
========

coroutine asyncio.sleep(delay, result=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.

   Setting the delay to 0 provides an optimized path to allow other
   tasks to run. This can be used by long-running functions to avoid
   blocking the event loop for the full duration of the function call.

   Deprecated since version 3.8, removed in version 3.10: The "loop"
   parameter.  This function has been implicitly getting the current
   running loop since 3.7.  See What’s New in 3.10’s Removed section
   for more information.

   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())

   Changed in version 3.10: Removed the *loop* parameter.


Running Tasks Concurrently
==========================

awaitable asyncio.gather(*aws, 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.

   Changed in version 3.10: Removed 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({number}), currently i={i}...")
              await asyncio.sleep(1)
              f *= i
          print(f"Task {name}: factorial({number}) = {f}")
          return f

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

      asyncio.run(main())

      # Expected output:
      #
      #     Task A: Compute factorial(2), currently i=2...
      #     Task B: Compute factorial(3), currently i=2...
      #     Task C: Compute factorial(4), currently i=2...
      #     Task A: factorial(2) = 2
      #     Task B: Compute factorial(3), currently i=3...
      #     Task C: Compute factorial(4), currently i=3...
      #     Task B: factorial(3) = 6
      #     Task C: Compute factorial(4), currently i=4...
      #     Task C: factorial(4) = 24
      #     [2, 6, 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*.

   Changed in version 3.10: Removed the *loop* parameter.

   Deprecated since version 3.10: Deprecation warning is emitted if no
   positional arguments are provided or not all positional arguments
   are Future-like objects and there is no running event loop.


Shielding From Cancellation
===========================

awaitable asyncio.shield(aw)

   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

   Changed in version 3.10: Removed the *loop* parameter.

   Deprecated since version 3.10: Deprecation warning is emitted if
   *aw* is not Future-like object and there is no running event loop.


Timeouts
========

coroutine asyncio.wait_for(aw, timeout)

   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 an exception
   happens during cancellation, it is propagated.

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

   Changed in version 3.10: Removed 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.

   Changed in version 3.10: Removed the *loop* parameter.


Waiting Primitives
==================

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

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

   The *aws* iterable must not be empty.

   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                              |
   |===============================|==========================================|
   | "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.

   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.

   Changed in version 3.10: Removed 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, will be removed in version 3.11:
   Passing coroutine objects to "wait()" directly is deprecated.

   Changed in version 3.10: Removed the *loop* parameter.

asyncio.as_completed(aws, *, 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.

   Changed in version 3.10: Removed the *loop* parameter.

   Example:

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

   Changed in version 3.10: Removed the *loop* parameter.

   Deprecated since version 3.10: Deprecation warning is emitted if
   not all awaitable objects in the *aws* iterable are Future-like
   objects and there is no running event loop.


Running in Threads
==================

coroutine asyncio.to_thread(func, /, *args, **kwargs)

   Asynchronously run function *func* in a separate thread.

   Any *args and **kwargs supplied for this function are directly
   passed to *func*. Also, the current "contextvars.Context" is
   propagated, allowing context variables from the event loop thread
   to be accessed in the separate thread.

   Return a coroutine that can be awaited to get the eventual result
   of *func*.

   This coroutine function is primarily intended to be used for
   executing IO-bound functions/methods that would otherwise block the
   event loop if they were ran in the main thread. For example:

      def blocking_io():
          print(f"start blocking_io at {time.strftime('%X')}")
          # Note that time.sleep() can be replaced with any blocking
          # IO-bound operation, such as file operations.
          time.sleep(1)
          print(f"blocking_io complete at {time.strftime('%X')}")

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

          await asyncio.gather(
              asyncio.to_thread(blocking_io),
              asyncio.sleep(1))

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


      asyncio.run(main())

      # Expected output:
      #
      # started main at 19:50:53
      # start blocking_io at 19:50:53
      # blocking_io complete at 19:50:54
      # finished main at 19:50:54

   Directly calling *blocking_io()* in any coroutine would block the
   event loop for its duration, resulting in an additional 1 second of
   run time. Instead, by using *asyncio.to_thread()*, we can run it in
   a separate thread without blocking the event loop.

   Note:

     Due to the *GIL*, *asyncio.to_thread()* can typically only be
     used to make IO-bound functions non-blocking. However, for
     extension modules that release the GIL or alternative Python
     implementations that don’t have one, *asyncio.to_thread()* can
     also be used for CPU-bound functions.

   New in version 3.9.


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 concurrent.futures.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, 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 3.10: Deprecation warning is emitted if
   *loop* is not specified and there is no running event loop.

   cancel(msg=None)

      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.

      Changed in version 3.9: Added the *msg* parameter.

      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.


Generator-based Coroutines
==========================

Note:

  Support for generator-based coroutines is **deprecated** and is
  removed in Python 3.11.

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 should not be used for "async def" coroutines.

   Deprecated since version 3.8, will be removed in version 3.11: 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".
