[Python-Dev] PEP 492: async/await in Python; version 5

Yury Selivanov yselivanov.ml at gmail.com
Tue May 5 18:29:44 CEST 2015

Hi python-dev,

Updated version of the PEP is below.

Quick summary of changes:

1. set_coroutine_wrapper and get_coroutine_wrapper functions
are now thread-specific (like settrace etc).

2. Updated Abstract & Rationale sections.

3. RuntimeWarning is always raised when a coroutine wasn't
awaited on. This is in addition to what 'set_coroutine_wrapper'
will/can do.

4. asyncio.async is renamed to asyncio.ensure_future; it will
be deprecated in 3.5.

5. Uses of async/await in CPython codebase are documented.

6. Other small edits and updates.


PEP: 492
Title: Coroutines with async and await syntax
Version: $Revision$
Last-Modified: $Date$
Author: Yury Selivanov <yselivanov at sprymix.com>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 09-Apr-2015
Python-Version: 3.5
Post-History: 17-Apr-2015, 21-Apr-2015, 27-Apr-2015, 29-Apr-2015,


The growth of Internet and general connectivity has triggered the
proportionate need for responsive and scalable code.  This proposal
aims to answer that need by making writing explicitly asynchronous,
concurrent Python code easier and more Pythonic.

It is proposed to make *coroutines* a proper standalone concept in
Python, and introduce new supporting syntax.  The ultimate goal
is to help establish a common, easily approachable, mental
model of asynchronous programming in Python and make it as close to
synchronous programming as possible.

We believe that the changes proposed here will help keep Python
relevant and competitive in a quickly growing area of asynchronous
programming, as many other languages have adopted, or are planning to
adopt, similar features: [2]_, [5]_, [6]_, [7]_, [8]_, [10]_.

Rationale and Goals

Current Python supports implementing coroutines via generators (PEP
342), further enhanced by the ``yield from`` syntax introduced in PEP
380. This approach has a number of shortcomings:

* It is easy to confuse coroutines with regular generators, since they
   share the same syntax; this is especially true for new developers.

* Whether or not a function is a coroutine is determined by a presence
   of ``yield``  or ``yield from`` statements in its *body*, which can
   lead to unobvious errors when such statements appear in or disappear
   from function body during refactoring.

* Support for asynchronous calls is limited to expressions where
   ``yield`` is allowed syntactically, limiting the usefulness of
   syntactic features, such as ``with`` and ``for`` statements.

This proposal makes coroutines a native Python language feature, and
clearly separates them from generators.  This removes
generator/coroutine ambiguity, and makes it possible to reliably define
coroutines without reliance on a specific library.  This also enables
linters and IDEs to improve static code analysis and refactoring.

Native coroutines and the associated new syntax features make it
possible to define context manager and iteration protocols in
asynchronous terms. As shown later in this proposal, the new ``async
with`` statement lets Python programs perform asynchronous calls when
entering and exiting a runtime context, and the new ``async for``
statement makes it possible to perform asynchronous calls in iterators.


This proposal introduces new syntax and semantics to enhance coroutine
support in Python.

This specification presumes knowledge of the implementation of
coroutines in Python (PEP 342 and PEP 380).  Motivation for the syntax
changes proposed here comes from the asyncio framework (PEP 3156) and
the "Cofunctions" proposal (PEP 3152, now rejected in favor of this

 From this point in this document we use the word *native coroutine* to
refer to functions declared using the new syntax. *generator-based
coroutine* is used where necessary to refer to coroutines that are
based on generator syntax.  *coroutine* is used in contexts where both
definitions are applicable.

New Coroutine Declaration Syntax

The following new syntax is used to declare a *native coroutine*::

     async def read_data(db):

Key properties of *coroutines*:

* ``async def`` functions are always coroutines, even if they do not
   contain ``await`` expressions.

* It is a ``SyntaxError`` to have ``yield`` or ``yield from``
   expressions in an ``async`` function.

* Internally, two new code object flags were introduced:

   - ``CO_COROUTINE`` is used to enable runtime detection of
     *coroutines* (and migrating existing code).

   - ``CO_NATIVE_COROUTINE`` is used to mark *native coroutines*
     (defined with new syntax.)

   All coroutines have ``CO_COROUTINE``, ``CO_NATIVE_COROUTINE``, and
   ``CO_GENERATOR`` flags set.

* Regular generators, when called, return a *generator object*;
   similarly, coroutines return a *coroutine object*.

* ``StopIteration`` exceptions are not propagated out of coroutines,
   and are replaced with a ``RuntimeError``.  For regular generators
   such behavior requires a future import (see PEP 479).

* When a *coroutine* is garbage collected, a ``RuntimeWarning`` is
   raised if it was never awaited on (see also `Debugging Features`_.)

* See also `Coroutine objects`_ section.


A new function ``coroutine(gen)`` is added to the ``types`` module.  It
allows interoperability between existing *generator-based coroutines*
in asyncio and *native coroutines* introduced by this PEP.

The function applies ``CO_COROUTINE`` flag to generator-function's code
object, making it return a *coroutine object*.

The function can be used as a decorator, since it modifies generator-
functions in-place and returns them.

Note, that the ``CO_NATIVE_COROUTINE`` flag is not applied by
``types.coroutine()`` to make it possible to separate *native
coroutines* defined with new syntax, from *generator-based coroutines*.

Await Expression

The following new ``await`` expression is used to obtain a result of
coroutine execution::

     async def read_data(db):
         data = await db.fetch('SELECT ...')

``await``, similarly to ``yield from``, suspends execution of
``read_data`` coroutine until ``db.fetch`` *awaitable* completes and
returns the result data.

It uses the ``yield from`` implementation with an extra step of
validating its argument.  ``await`` only accepts an *awaitable*, which
can be one of:

* A *native coroutine object* returned from a *native coroutine*.

* A *generator-based coroutine object* returned from a generator
   decorated with ``types.coroutine()``.

* An object with an ``__await__`` method returning an iterator.

   Any ``yield from`` chain of calls ends with a ``yield``.  This is a
   fundamental mechanism of how *Futures* are implemented.  Since,
   internally, coroutines are a special kind of generators, every
   ``await`` is suspended by a ``yield`` somewhere down the chain of
   ``await`` calls (please refer to PEP 3156 for a detailed

   To enable this behavior for coroutines, a new magic method called
   ``__await__`` is added.  In asyncio, for instance, to enable *Future*
   objects in ``await`` statements, the only change is to add
   ``__await__ = __iter__`` line to ``asyncio.Future`` class.

   Objects with ``__await__`` method are called *Future-like* objects in
   the rest of this PEP.

   Also, please note that ``__aiter__`` method (see its definition
   below) cannot be used for this purpose.  It is a different protocol,
   and would be like using ``__iter__`` instead of ``__call__`` for
   regular callables.

   It is a ``TypeError`` if ``__await__`` returns anything but an

* Objects defined with CPython C API with a ``tp_await`` function,
   returning an iterator (similar to ``__await__`` method).

It is a ``SyntaxError`` to use ``await`` outside of an ``async def``
function (like it is a ``SyntaxError`` to use ``yield`` outside of
``def`` function.)

It is a ``TypeError`` to pass anything other than an *awaitable* object
to an ``await`` expression.

Updated operator precedence table

``await`` keyword is defined as follows::

     power ::=  await ["**" u_expr]
     await ::=  ["await"] primary

where "primary" represents the most tightly bound operations of the
language.  Its syntax is::

     primary ::=  atom | attributeref | subscription | slicing | call

See Python Documentation [12]_ and `Grammar Updates`_ section of this
proposal for details.

The key ``await`` difference from ``yield`` and ``yield from``
operators is that *await expressions* do not require parentheses around
them most of the times.

Also, ``yield from`` allows any expression as its argument, including
expressions like ``yield from a() + b()``, that would be parsed as
``yield from (a() + b())``, which is almost always a bug.  In general,
the result of any arithmetic operation is not an *awaitable* object.
To avoid this kind of mistakes, it was decided to make ``await``
precedence lower than ``[]``, ``()``, and ``.``, but higher than ``**``

| Operator                     | Description |
| ``yield`` ``x``,             | Yield expression |
| ``yield from`` ``x``         | |
| ``lambda``                   | Lambda expression |
| ``if`` -- ``else``           | Conditional expression |
| ``or``                       | Boolean OR |
| ``and``                      | Boolean AND |
| ``not`` ``x``                | Boolean NOT |
| ``in``, ``not in``,          | Comparisons, including membership |
| ``is``, ``is not``, ``<``,   | tests and identity tests          |
| ``<=``, ``>``, ``>=``, |                                   |
| ``!=``, ``==``               | |
| ``|``                        | Bitwise OR |
| ``^``                        | Bitwise XOR |
| ``&``                        | Bitwise AND                       |
| ``<<``, ``>>``               | Shifts                            |
| ``+``, ``-``                 | Addition and subtraction |
| ``*``, ``@``, ``/``, ``//``, | Multiplication, matrix |
| ``%``                        | multiplication, division, |
|                              | remainder |
| ``+x``, ``-x``, ``~x``       | Positive, negative, bitwise NOT |
| ``**``                       | Exponentiation |
| ``await`` ``x``              | Await expression |
| ``x[index]``,                | Subscription, slicing, |
| ``x[index:index]``,          | call, attribute reference |
| ``x(arguments...)``,         | |
| ``x.attribute``              | |
| ``(expressions...)``,        | Binding or tuple display, |
| ``[expressions...]``,        | list display, |
| ``{key: value...}``,         | dictionary display, |
| ``{expressions...}``         | set display |

Examples of "await" expressions

Valid syntax examples:

================================== ==================================
Expression                         Will be parsed as
================================== ==================================
``if await fut: pass``             ``if (await fut): pass``
``if await fut + 1: pass``         ``if (await fut) + 1: pass``
``pair = await fut, 'spam'``       ``pair = (await fut), 'spam'``
``with await fut, open(): pass``   ``with (await fut), open(): pass``
``await foo()['spam'].baz()()``    ``await ( foo()['spam'].baz()() )``
``return await coro()``            ``return ( await coro() )``
``res = await coro() ** 2``        ``res = (await coro()) ** 2``
``func(a1=await coro(), a2=0)``    ``func(a1=(await coro()), a2=0)``
``await foo() + await bar()``      ``(await foo()) + (await bar())``
``-await foo()``                   ``-(await foo())``
================================== ==================================

Invalid syntax examples:

================================== ==================================
Expression                         Should be written as
================================== ==================================
``await await coro()``             ``await (await coro())``
``await -coro()``                  ``await (-coro())``
================================== ==================================

Asynchronous Context Managers and "async with"

An *asynchronous context manager* is a context manager that is able to
suspend execution in its *enter* and *exit* methods.

To make this possible, a new protocol for asynchronous context managers
is proposed.  Two new magic methods are added: ``__aenter__`` and
``__aexit__``. Both must return an *awaitable*.

An example of an asynchronous context manager::

     class AsyncContextManager:
         async def __aenter__(self):
             await log('entering context')

         async def __aexit__(self, exc_type, exc, tb):
             await log('exiting context')

New Syntax

A new statement for asynchronous context managers is proposed::

     async with EXPR as VAR:

which is semantically equivalent to::

     mgr = (EXPR)
     aexit = type(mgr).__aexit__
     aenter = type(mgr).__aenter__(mgr)
     exc = True

         VAR = await aenter
         if not await aexit(mgr, *sys.exc_info()):
         await aexit(mgr, None, None, None)

As with regular ``with`` statements, it is possible to specify multiple
context managers in a single ``async with`` statement.

It is an error to pass a regular context manager without ``__aenter__``
and ``__aexit__`` methods to ``async with``.  It is a ``SyntaxError``
to use ``async with`` outside of an ``async def`` function.


With *asynchronous context managers* it is easy to implement proper
database transaction managers for coroutines::

     async def commit(session, data):

         async with session.transaction():
             await session.update(data)

Code that needs locking also looks lighter::

     async with lock:

instead of::

     with (yield from lock):

Asynchronous Iterators and "async for"

An *asynchronous iterable* is able to call asynchronous code in its
*iter* implementation, and *asynchronous iterator* can call
asynchronous code in its *next* method.  To support asynchronous

1. An object must implement an  ``__aiter__`` method returning an
    *awaitable* resulting in an *asynchronous iterator object*.

2. An *asynchronous iterator object* must implement an ``__anext__``
    method returning an *awaitable*.

3. To stop iteration ``__anext__`` must raise a ``StopAsyncIteration``

An example of asynchronous iterable::

     class AsyncIterable:
         async def __aiter__(self):
             return self

         async def __anext__(self):
             data = await self.fetch_data()
             if data:
                 return data
                 raise StopAsyncIteration

         async def fetch_data(self):

New Syntax

A new statement for iterating through asynchronous iterators is

     async for TARGET in ITER:

which is semantically equivalent to::

     iter = (ITER)
     iter = await type(iter).__aiter__(iter)
     running = True
     while running:
             TARGET = await type(iter).__anext__(iter)
         except StopAsyncIteration:
             running = False

It is a ``TypeError`` to pass a regular iterable without ``__aiter__``
method to ``async for``.  It is a ``SyntaxError`` to use ``async for``
outside of an ``async def`` function.

As for with regular ``for`` statement, ``async for`` has an optional
``else`` clause.

Example 1

With asynchronous iteration protocol it is possible to asynchronously
buffer data during iteration::

     async for data in cursor:

Where ``cursor`` is an asynchronous iterator that prefetches ``N`` rows
of data from a database after every ``N`` iterations.

The following code illustrates new asynchronous iteration protocol::

     class Cursor:
         def __init__(self):
             self.buffer = collections.deque()

         def _prefetch(self):

         async def __aiter__(self):
             return self

         async def __anext__(self):
             if not self.buffer:
                 self.buffer = await self._prefetch()
                 if not self.buffer:
                     raise StopAsyncIteration
             return self.buffer.popleft()

then the ``Cursor`` class can be used as follows::

     async for row in Cursor():

which would be equivalent to the following code::

     i = await Cursor().__aiter__()
     while True:
             row = await i.__anext__()
         except StopAsyncIteration:

Example 2

The following is a utility class that transforms a regular iterable to
an asynchronous one.  While this is not a very useful thing to do, the
code illustrates the relationship between regular and asynchronous


     class AsyncIteratorWrapper:
         def __init__(self, obj):
             self._it = iter(obj)

         async def __aiter__(self):
             return self

         async def __anext__(self):
                 value = next(self._it)
             except StopIteration:
                 raise StopAsyncIteration
             return value

     async for letter in AsyncIteratorWrapper("abc"):

Why StopAsyncIteration?

Coroutines are still based on generators internally.  So, before PEP
479, there was no fundamental difference between


     def g1():
         yield from fut
         return 'spam'



     def g2():
         yield from fut
         raise StopIteration('spam')

And since PEP 479 is accepted and enabled by default for coroutines,
the following example will have its ``StopIteration`` wrapped into a


     async def a1():
         await fut
         raise StopIteration('spam')

The only way to tell the outside code that the iteration has ended is
to raise something other than ``StopIteration``.  Therefore, a new
built-in exception class ``StopAsyncIteration`` was added.

Moreover, with semantics from PEP 479, all ``StopIteration`` exceptions
raised in coroutines are wrapped in ``RuntimeError``.

Coroutine objects

Differences from generators

This section applies only to *native coroutines* with
``CO_NATIVE_COROUTINE`` flag, i.e. defined with the new ``async def``

**The behavior of existing *generator-based coroutines* in asyncio
remains unchanged.**

Great effort has been made to make sure that coroutines and
generators are treated as distinct concepts:

1. *Native coroutine objects* do not implement ``__iter__`` and
    ``__next__`` methods.  Therefore, they cannot be iterated over or
    passed to ``iter()``, ``list()``, ``tuple()`` and other built-ins.
    They also cannot be used in a ``for..in`` loop.

    An attempt to use ``__iter__`` or ``__next__`` on a *native
    coroutine object* will result in a ``TypeError``.

2. *Plain generators* cannot ``yield from`` *native coroutine objects*:
    doing so will result in a ``TypeError``.

3. *generator-based coroutines* (for asyncio code must be decorated
    with ``@asyncio.coroutine``) can ``yield from`` *native coroutine

4. ``inspect.isgenerator()`` and ``inspect.isgeneratorfunction()``
    return ``False`` for *native coroutine objects* and *native
    coroutine functions*.

Coroutine object methods

Coroutines are based on generators internally, thus they share the
implementation.  Similarly to generator objects, coroutine objects have
``throw()``, ``send()`` and ``close()`` methods. ``StopIteration`` and
``GeneratorExit`` play the same role for coroutine objects (although
PEP 479 is enabled by default for coroutines).  See PEP 342, PEP 380,
and Python Documentation [11]_ for details.

``throw()``, ``send()`` methods for coroutine objects are used to push
values and raise errors into *Future-like* objects.

Debugging Features

A common beginner mistake is forgetting to use ``yield from`` on

     def useful():
         asyncio.sleep(1) # this will do noting without 'yield from'

For debugging this kind of mistakes there is a special debug mode in
asyncio, in which ``@coroutine`` decorator wraps all functions with a
special object with a destructor logging a warning.  Whenever a wrapped
generator gets garbage collected, a detailed logging message is
generated with information about where exactly the decorator function
was defined, stack trace of where it was collected, etc.  Wrapper
object also provides a convenient ``__repr__`` function with detailed
information about the generator.

The only problem is how to enable these debug capabilities.  Since
debug facilities should be a no-op in production mode, ``@coroutine``
decorator makes the decision of whether to wrap or not to wrap based on
an OS environment variable ``PYTHONASYNCIODEBUG``.  This way it is
possible to run asyncio programs with asyncio's own functions
instrumented.  ``EventLoop.set_debug``, a different debug facility, has
no impact on ``@coroutine`` decorator's behavior.

With this proposal, coroutines is a native, distinct from generators,
concept.  *In addition* to a ``RuntimeWarning`` being raised on
coroutines that were never awaited, it is proposed to add two new
functions to the ``sys`` module: ``set_coroutine_wrapper`` and
``get_coroutine_wrapper``.  This is to enable advanced debugging
facilities in asyncio and other frameworks (such as displaying where
exactly coroutine was created, and a more detailed stack trace of where
it was garbage collected).

New Standard Library Functions

* ``types.coroutine(gen)``.  See `types.coroutine()`_ section for

* ``inspect.iscoroutine(obj)`` returns ``True`` if ``obj`` is a
   *coroutine object*.

* ``inspect.iscoroutinefunction(obj)`` returns ``True`` if ``obj`` is a
   *coroutine function*.

* ``inspect.isawaitable(obj)`` returns ``True`` if ``obj`` can be used
   in ``await`` expression.  See `Await Expression`_ for details.

* ``sys.set_coroutine_wrapper(wrapper)`` allows to intercept creation
   of *coroutine objects*.  ``wrapper`` must be a callable that accepts
   one argument: a *coroutine object* or ``None``.  ``None`` resets the
   wrapper.  If called twice, the new wrapper replaces the previous one.
   The function is thread-specific.  See `Debugging Features`_ for more

* ``sys.get_coroutine_wrapper()`` returns the current wrapper object.
   Returns ``None`` if no wrapper was set.  The function is
   thread-specific.  See  `Debugging Features`_ for more details.


:Native coroutine:
     A coroutine function is declared with ``async def``. It uses
     ``await`` and ``return value``; see `New Coroutine Declaration
     Syntax`_ for details.

:Native coroutine object:
     Returned from a native coroutine function. See `Await Expression`_
     for details.

:Generator-based coroutine:
     Coroutines based on generator syntax.  Most common example are
     functions decorated with ``@asyncio.coroutine``.

:Generator-based coroutine object:
     Returned from a generator-based coroutine function.

     Either *native coroutine* or *generator-based coroutine*.

:Coroutine object:
     Either *native coroutine object* or *generator-based coroutine

:Future-like object:
     An object with an ``__await__`` method, or a C object with
     ``tp_await`` function, returning an iterator.  Can be consumed by
     an ``await`` expression in a coroutine. A coroutine waiting for a
     Future-like object is suspended until the Future-like object's
     ``__await__`` completes, and returns the result.  See `Await
     Expression`_ for details.

     A *Future-like* object or a *coroutine object*.  See `Await
     Expression`_ for details.

:Asynchronous context manager:
    An asynchronous context manager has ``__aenter__`` and ``__aexit__``
    methods and can be used with ``async with``.  See `Asynchronous
    Context Managers and "async with"`_ for details.

:Asynchronous iterable:
     An object with an ``__aiter__`` method, which must return an
     *asynchronous iterator* object.  Can be used with ``async for``.
     See `Asynchronous Iterators and "async for"`_ for details.

:Asynchronous iterator:
     An asynchronous iterator has an ``__anext__`` method.  See
     `Asynchronous Iterators and "async for"`_ for details.

List of functions and methods

================= =================================== =================
Method            Can contain                         Can't contain
================= =================================== =================
async def func    await, return value                 yield, yield from
async def __a*__  await, return value                 yield, yield from
def __a*__        return awaitable                    await
def __await__     yield, yield from, return iterable  await
generator         yield, yield from, return value     await
================= =================================== =================


* "async def func": native coroutine;

* "async def __a*__": ``__aiter__``, ``__anext__``, ``__aenter__``,
   ``__aexit__`` defined with the ``async`` keyword;

* "def __a*__": ``__aiter__``, ``__anext__``, ``__aenter__``,
   ``__aexit__`` defined without the ``async`` keyword, must return an

* "def __await__": ``__await__`` method to implement *Future-like*

* generator: a "regular" generator, function defined with ``def`` and
   which contains a least one ``yield`` or ``yield from`` expression.

Transition Plan

To avoid backwards compatibility issues with ``async`` and ``await``
keywords, it was decided to modify ``tokenizer.c`` in such a way, that

* recognizes ``async def`` ``NAME`` tokens combination;

* keeps track of regular ``def`` and ``async def`` indented blocks;

* while tokenizing ``async def`` block, it replaces ``'async'``
   ``NAME`` token with ``ASYNC``, and ``'await'`` ``NAME`` token with

* while tokenizing ``def`` block, it yields ``'async'`` and ``'await'``
   ``NAME`` tokens as is.

This approach allows for seamless combination of new syntax features
(all of them available only in ``async`` functions) with any existing

An example of having "async def" and "async" attribute in one piece of

     class Spam:
         async = 42

     async def ham():
         print(getattr(Spam, 'async'))

     # The coroutine can be executed and will print '42'

Backwards Compatibility

This proposal preserves 100% backwards compatibility.


``asyncio`` module was adapted and tested to work with coroutines and
new statements.  Backwards compatibility is 100% preserved, i.e. all
existing code will work as-is.

The required changes are mainly:

1. Modify ``@asyncio.coroutine`` decorator to use new
    ``types.coroutine()`` function.

2. Add ``__await__ = __iter__`` line to ``asyncio.Future`` class.

3. Add ``ensure_future()`` as an alias for ``async()`` function.
    Deprecate ``async()`` function.

asyncio migration strategy

Because *plain generators* cannot ``yield from`` *native coroutine
objects* (see `Differences from generators`_ section for more details),
it is advised to make sure that all generator-based coroutines are
decorated with ``@asyncio.coroutine`` *before* starting to use the new

async/await in CPython code base

There is no use of ``await`` names in CPython.

``async`` is mostly used by asyncio.  We are addressing this by
renaming ``async()`` function to ``ensure_future()`` (see `asyncio`_
section for details.)

Another use of ``async`` keyword is in ``Lib/xml/dom/xmlbuilder.py``,
to define an ``async = False`` attribute for ``DocumentLS`` class.
There is no documentation or tests for it, it is not used anywhere else
in CPython.  It is replaced with a getter, that raises a
``DeprecationWarning``, advising to use ``async_`` attribute instead.
'async' attribute is not documented and is not used in CPython code

Grammar Updates

Grammar changes are fairly minimal::

     decorated: decorators (classdef | funcdef | async_funcdef)
     async_funcdef: ASYNC funcdef

     compound_stmt: (if_stmt | while_stmt | for_stmt | try_stmt | with_stmt
                     | funcdef | classdef | decorated | async_stmt)

     async_stmt: ASYNC (funcdef | with_stmt | for_stmt)

     power: atom_expr ['**' factor]
     atom_expr: [AWAIT] atom trailer*

Transition Period Shortcomings

There is just one.

Until ``async`` and ``await`` are not proper keywords, it is not
possible (or at least very hard) to fix ``tokenizer.c`` to recognize
them on the **same line** with ``def`` keyword::

     # async and await will always be parsed as variables

     async def outer():                             # 1
         def nested(a=(await fut)):

     async def foo(): return (await fut)            # 2

Since ``await`` and ``async`` in such cases are parsed as ``NAME``
tokens, a ``SyntaxError`` will be raised.

To workaround these issues, the above examples can be easily rewritten
to a more readable form::

     async def outer():                             # 1
         a_default = await fut
         def nested(a=a_default):

     async def foo():                               # 2
         return (await fut)

This limitation will go away as soon as ``async`` and ``await`` are
proper keywords.

Deprecation Plans

``async`` and ``await`` names will be softly deprecated in CPython 3.5
and 3.6. In 3.7 we will transform them to proper keywords.  Making
``async`` and ``await`` proper keywords before 3.7 might make it harder
for people to port their code to Python 3.

Design Considerations

PEP 3152

PEP 3152 by Gregory Ewing proposes a different mechanism for coroutines
(called "cofunctions").  Some key points:

1. A new keyword ``codef`` to declare a *cofunction*. *Cofunction* is
    always a generator, even if there is no ``cocall`` expressions
    inside it.  Maps to ``async def`` in this proposal.

2. A new keyword ``cocall`` to call a *cofunction*.  Can only be used
    inside a *cofunction*.  Maps to ``await`` in this proposal (with
    some differences, see below.)

3. It is not possible to call a *cofunction* without a ``cocall``

4. ``cocall`` grammatically requires parentheses after it::

     atom: cocall | <existing alternatives for atom>
     cocall: 'cocall' atom cotrailer* '(' [arglist] ')'
     cotrailer: '[' subscriptlist ']' | '.' NAME

5. ``cocall f(*args, **kwds)`` is semantically equivalent to
    ``yield from f.__cocall__(*args, **kwds)``.

Differences from this proposal:

1. There is no equivalent of ``__cocall__`` in this PEP, which is
    called and its result is passed to ``yield from`` in the ``cocall``
    expression. ``await`` keyword expects an *awaitable* object,
    validates the type, and executes ``yield from`` on it. Although,
    ``__await__`` method is similar to ``__cocall__``, but is only used
    to define *Future-like* objects.

2. ``await`` is defined in almost the same way as ``yield from`` in the
    grammar (it is later enforced that ``await`` can only be inside
    ``async def``).  It is possible to simply write ``await future``,
    whereas ``cocall`` always requires parentheses.

3. To make asyncio work with PEP 3152 it would be required to modify
    ``@asyncio.coroutine`` decorator to wrap all functions in an object
    with a ``__cocall__`` method, or to implement ``__cocall__`` on
    generators.  To call *cofunctions* from existing generator-based
    coroutines it would be required to use ``costart(cofunc, *args,
    **kwargs)`` built-in.

4. Since it is impossible to call a *cofunction* without a ``cocall``
    keyword, it automatically prevents the common mistake of forgetting
    to use ``yield from`` on generator-based coroutines.  This proposal
    addresses this problem with a different approach, see `Debugging

5. A shortcoming of requiring a ``cocall`` keyword to call a coroutine
    is that if is decided to implement coroutine-generators --
    coroutines with ``yield`` or ``async yield`` expressions -- we
    wouldn't need a ``cocall`` keyword to call them.  So we'll end up
    having ``__cocall__`` and no ``__call__`` for regular coroutines,
    and having ``__call__`` and no ``__cocall__`` for coroutine-

6. Requiring parentheses grammatically also introduces a whole lot
    of new problems.

    The following code::

        await fut
        await function_returning_future()
        await asyncio.gather(coro1(arg1, arg2), coro2(arg1, arg2))

    would look like::

        cocall fut()  # or cocall costart(fut)
        cocall (function_returning_future())()
        cocall asyncio.gather(costart(coro1, arg1, arg2),
                              costart(coro2, arg1, arg2))

7. There are no equivalents of ``async for`` and ``async with`` in PEP


With ``async for`` keyword it is desirable to have a concept of a
*coroutine-generator* -- a coroutine with ``yield`` and ``yield from``
expressions.  To avoid any ambiguity with regular generators, we would
likely require to have an ``async`` keyword before ``yield``, and
``async yield from`` would raise a ``StopAsyncIteration`` exception.

While it is possible to implement coroutine-generators, we believe that
they are out of scope of this proposal.  It is an advanced concept that
should be carefully considered and balanced, with a non-trivial changes
in the implementation of current generator objects.  This is a matter
for a separate PEP.

Why "async" and "await" keywords

async/await is not a new concept in programming languages:

* C# has it since long time ago [5]_;

* proposal to add async/await in ECMAScript 7 [2]_;
   see also Traceur project [9]_;

* Facebook's Hack/HHVM [6]_;

* Google's Dart language [7]_;

* Scala [8]_;

* proposal to add async/await to C++ [10]_;

* and many other less popular languages.

This is a huge benefit, as some users already have experience with
async/await, and because it makes working with many languages in one
project easier (Python with ECMAScript 7 for instance).

Why "__aiter__" returns awaitable

In principle, ``__aiter__`` could be a regular function.  There are
several good reasons to make it a coroutine:

* as most of the ``__anext__``, ``__aenter__``, and ``__aexit__``
   methods are coroutines, users would often make a mistake defining it
   as ``async`` anyways;

* there might be a need to run some asynchronous operations in
   ``__aiter__``, for instance to prepare DB queries or do some file

Importance of "async" keyword

While it is possible to just implement ``await`` expression and treat
all functions with at least one ``await`` as coroutines, this approach
makes APIs design, code refactoring and its long time support harder.

Let's pretend that Python only has ``await`` keyword::

     def useful():
         await log(...)

     def important():
         await useful()

If ``useful()`` function is refactored and someone removes all
``await`` expressions from it, it would become a regular python
function, and all code that depends on it, including ``important()``
would be broken.  To mitigate this issue a decorator similar to
``@asyncio.coroutine`` has to be introduced.

Why "async def"

For some people bare ``async name(): pass`` syntax might look more
appealing than ``async def name(): pass``.  It is certainly easier to
type.  But on the other hand, it breaks the symmetry between ``async
def``, ``async with`` and ``async for``, where ``async`` is a modifier,
stating that the statement is asynchronous.  It is also more consistent
with the existing grammar.

Why not "await for" and "await with"

``async`` is an adjective, and hence it is a better choice for a
*statement qualifier* keyword.  ``await for/with`` would imply that
something is awaiting for a completion of a ``for`` or ``with``

Why "async def" and not "def async"

``async`` keyword is a *statement qualifier*.  A good analogy to it are
"static", "public", "unsafe" keywords from other languages. "async
for" is an asynchronous "for" statement, "async with" is an
asynchronous "with" statement, "async def" is an asynchronous function.

Having "async" after the main statement keyword might introduce some
confusion, like "for async item in iterator" can be read as "for each
asynchronous item in iterator".

Having ``async`` keyword before ``def``, ``with`` and ``for`` also
makes the language grammar simpler.  And "async def" better separates
coroutines from regular functions visually.

Why not a __future__ import

`Transition Plan`_ section explains how tokenizer is modified to treat
``async`` and ``await`` as keywords *only* in ``async def`` blocks.
Hence ``async def`` fills the role that a module level compiler
declaration like ``from __future__ import async_await`` would otherwise

Why magic methods start with "a"

New asynchronous magic methods ``__aiter__``, ``__anext__``,
``__aenter__``, and ``__aexit__`` all start with the same prefix "a".
An alternative proposal is to use "async" prefix, so that ``__aiter__``
becomes ``__async_iter__``. However, to align new magic methods with
the existing ones, such as ``__radd__`` and ``__iadd__`` it was decided
to use a shorter version.

Why not reuse existing magic names

An alternative idea about new asynchronous iterators and context
managers was to reuse existing magic methods, by adding an ``async``
keyword to their declarations::

     class CM:
         async def __enter__(self): # instead of __aenter__

This approach has the following downsides:

* it would not be possible to create an object that works in both
   ``with`` and ``async with`` statements;

* it would break backwards compatibility, as nothing prohibits from
   returning a Future-like objects from ``__enter__`` and/or
   ``__exit__`` in Python <= 3.4;

* one of the main points of this proposal is to make native coroutines
   as simple and foolproof as possible, hence the clear separation of
   the protocols.

Why not reuse existing "for" and "with" statements

The vision behind existing generator-based coroutines and this proposal
is to make it easy for users to see where the code might be suspended.
Making existing "for" and "with" statements to recognize asynchronous
iterators and context managers will inevitably create implicit suspend
points, making it harder to reason about the code.


Syntax for asynchronous comprehensions could be provided, but this
construct is outside of the scope of this PEP.

Async lambda functions

Syntax for asynchronous lambda functions could be provided, but this
construct is outside of the scope of this PEP.


Overall Impact

This proposal introduces no observable performance impact.  Here is an
output of python's official set of benchmarks [4]_:


     python perf.py -r -b default ../cpython/python.exe 


     Report on Darwin ysmac 14.3.0 Darwin Kernel Version 14.3.0:
     Mon Mar 23 11:59:05 PDT 2015; root:xnu-2782.20.48~5/RELEASE_X86_64
     x86_64 i386

     Total CPU cores: 8

     ### etree_iterparse ###
     Min: 0.365359 -> 0.349168: 1.05x faster
     Avg: 0.396924 -> 0.379735: 1.05x faster
     Significant (t=9.71)
     Stddev: 0.01225 -> 0.01277: 1.0423x larger

     The following not significant results are hidden, use -v to show them:
     django_v2, 2to3, etree_generate, etree_parse, etree_process, 
     fastunpickle, json_dump_v2, json_load, nbody, regex_v8, tornado_http.

Tokenizer modifications

There is no observable slowdown of parsing python files with the
modified tokenizer: parsing of one 12Mb file
(``Lib/test/test_binop.py`` repeated 1000 times) takes the same amount
of time.


The following micro-benchmark was used to determine performance
difference between "async" functions and generators::

     import sys
     import time

     def binary(n):
         if n <= 0:
             return 1
         l = yield from binary(n - 1)
         r = yield from binary(n - 1)
         return l + 1 + r

     async def abinary(n):
         if n <= 0:
             return 1
         l = await abinary(n - 1)
         r = await abinary(n - 1)
         return l + 1 + r

     def timeit(gen, depth, repeat):
         t0 = time.time()
         for _ in range(repeat):
         t1 = time.time()
         print('{}({}) * {}: total {:.3f}s'.format(
             gen.__name__, depth, repeat, t1-t0))

The result is that there is no observable performance difference.
Minimum timing of 3 runs


     abinary(19) * 30: total 12.985s
     binary(19) * 30: total 12.953s

Note that depth of 19 means 1,048,575 calls.

Reference Implementation

The reference implementation can be found here: [3]_.

List of high-level changes and new protocols

1. New syntax for defining coroutines: ``async def`` and new ``await``

2. New ``__await__`` method for Future-like objects, and new
    ``tp_await`` slot in ``PyTypeObject``.

3. New syntax for asynchronous context managers: ``async with``. And
    associated protocol with ``__aenter__`` and ``__aexit__`` methods.

4. New syntax for asynchronous iteration: ``async for``.  And
    associated protocol with ``__aiter__``, ``__aexit__`` and new built-
    in exception ``StopAsyncIteration``.

5. New AST nodes: ``AsyncFunctionDef``, ``AsyncFor``, ``AsyncWith``,

6. New functions: ``sys.set_coroutine_wrapper(callback)``,
    ``sys.get_coroutine_wrapper()``, ``types.coroutine(gen)``,
    ``inspect.iscoroutinefunction()``, ``inspect.iscoroutine()``,
    and ``inspect.isawaitable()``.

7. New ``CO_COROUTINE`` and ``CO_NATIVE_COROUTINE`` bit flags for code

While the list of changes and new things is not short, it is important
to understand, that most users will not use these features directly.
It is intended to be used in frameworks and libraries to provide users
with convenient to use and unambiguous APIs with ``async def``,
``await``, ``async for`` and ``async with`` syntax.

Working example

All concepts proposed in this PEP are implemented [3]_ and can be


     import asyncio

     async def echo_server():
         print('Serving on localhost:8000')
         await asyncio.start_server(handle_connection,
                                    'localhost', 8000)

     async def handle_connection(reader, writer):
         print('New connection...')

         while True:
             data = await reader.read(8192)

             if not data:

             print('Sending {:.10}... back'.format(repr(data)))

     loop = asyncio.get_event_loop()


.. [1] https://docs.python.org/3/library/asyncio-task.html#asyncio.coroutine

.. [2] http://wiki.ecmascript.org/doku.php?id=strawman:async_functions

.. [3] https://github.com/1st1/cpython/tree/await

.. [4] https://hg.python.org/benchmarks

.. [5] https://msdn.microsoft.com/en-us/library/hh191443.aspx

.. [6] http://docs.hhvm.com/manual/en/hack.async.php

.. [7] https://www.dartlang.org/articles/await-async/

.. [8] http://docs.scala-lang.org/sips/pending/async.html

.. [9] 

.. [10] 
http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2013/n3722.pdf (PDF)

.. [11] 

.. [12] https://docs.python.org/3/reference/expressions.html#primaries


I thank Guido van Rossum, Victor Stinner, Elvis Pranskevichus, Andrew
Svetlov, and Łukasz Langa for their initial feedback.


This document has been placed in the public domain.

    Local Variables:
    mode: indented-text
    indent-tabs-mode: nil
    sentence-end-double-space: t
    fill-column: 70
    coding: utf-8

More information about the Python-Dev mailing list