[Python-Dev] async/await in Python; v2
Wolfgang Langner
tds333+pydev at gmail.com
Thu Apr 23 09:30:30 CEST 2015
Hi,
most of the time I am a silent reader but in this discussion I must step in.
I use twisted and async stuff a lot over years followed development of
asyncio closely.
First it is good to do differentiate async coroutines from generators. So
everyone can see it and have this in mind
and don't mix up booth. It is also easier to explain for new users.
Sometimes generators blows their mind and it takes
a while to get used to them. Async stuff is even harder.
1. I am fine with using something special instead of "yield" or "yield
from" for this. C# "await" is ok.
Everything else suggested complicates the language and makes it harder to
read.
2.
async def f(): is harder to read and something special also it breaks the
symmetry in front (def indent).
Also every existing tooling must be changed to support it. Same for def
async, def f() async:
I thing a decorator is enough here
@coroutine
def f():
is the best solution to mark something as a coroutine.
3.
async with and async for
Bead idea, we clutter the language even more and it is one more thing every
newbie could do wrong.
for x in y:
result = await f()
is enough, every 'async' framework lived without it over years.
Same for with statement.
The main use case suggested was for database stuff and this is also where
most are best with
defer something to a thread and keep it none async.
All together it is very late in the development cycle for 3.5 to
incorporate such a big change.
Best is to give all this some more time and defer it to 3.6 and some alpha
releases to experiment with.
Regards,
Wolfgang
On Tue, Apr 21, 2015 at 7:26 PM, Yury Selivanov <yselivanov.ml at gmail.com>
wrote:
> Hi python-dev,
>
> I'm moving the discussion from python-ideas to here.
>
> The updated version of the PEP should be available shortly
> at https://www.python.org/dev/peps/pep-0492
> and is also pasted in this email.
>
> Updates:
>
> 1. CO_ASYNC flag was renamed to CO_COROUTINE;
>
> 2. sys.set_async_wrapper() was renamed to
> sys.set_coroutine_wrapper();
>
> 3. New function: sys.get_coroutine_wrapper();
>
> 4. types.async_def() renamed to types.coroutine();
>
> 5. New section highlighting differences from
> PEP 3152.
>
> 6. New AST node - AsyncFunctionDef; the proposal
> now is 100% backwards compatible;
>
> 7. A new section clarifying that coroutine-generators
> are not part of the current proposal;
>
> 8. Various small edits/typos fixes.
>
>
> There's is a bug tracker issue to track code review
> of the reference implementation (Victor Stinner is
> doing the review): http://bugs.python.org/issue24017
> While the PEP isn't accepted, we want to make sure
> that the reference implementation is ready when such
> a decision will be made.
>
>
> Let's discuss some open questions:
>
> 1. Victor raised a question if we should locate
> coroutine() function from 'types' module to
> 'functools'.
>
> My opinion is that 'types' module is a better
> place for 'corotine()', since it adjusts the
> type of the passed generator. 'functools' is
> about 'partials', 'lru_cache' and 'wraps' kind
> of things.
>
> 2. I propose to disallow using of 'for..in' loops,
> and builtins like 'list()', 'iter()', 'next()',
> 'tuple()' etc on coroutines.
>
> It's possible by modifying PyObject_GetIter to
> raise an exception if it receives a coroutine-object.
>
> 'yield from' can also be modified to only accept
> coroutine objects if it is called from a generator
> with CO_COROUTINE flag.
>
> This will further separate coroutines from
> generators, making it harder to screw something
> up by an accident.
>
> I have a branch of reference implementation
> https://github.com/1st1/cpython/tree/await_noiter
> where this is implemented. I did not observe
> any performance drop.
>
> There is just one possible backwards compatibility
> issue here: there will be an exception if some user
> of asyncio actually used to iterate over generators
> decorated with @coroutine. But I can't imagine
> why would someone do that, and even if they did --
> it's probably a bug or wrong usage of asyncio.
>
>
> That's it! I'd be happy to hear some feedback!
>
> Thanks,
> Yury
>
>
>
> 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
>
>
> Abstract
> ========
>
> This PEP introduces new syntax for coroutines, asynchronous ``with``
> statements and ``for`` loops. The main motivation behind this proposal
> is to streamline writing and maintaining asynchronous code, as well as
> to simplify previously hard to implement code patterns.
>
>
> 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; async libraries often attempt to alleviate
> this by using decorators (e.g. ``@asyncio.coroutine`` [1]_);
>
> * it is not possible to natively define a coroutine which has no
> ``yield`` or ``yield from`` statements, again requiring the use of
> decorators to fix potential refactoring issues;
>
> * 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.
>
>
> Specification
> =============
>
> This proposal introduces new syntax and semantics to enhance coroutine
> support in Python, it does not change the internal implementation of
> coroutines, which are still based on generators.
>
> It is strongly suggested that the reader understands how coroutines are
> implemented in Python (PEP 342 and PEP 380). It is also recommended to
> read PEP 3156 (asyncio framework) and PEP 3152 (Cofunctions).
>
> From this point in this document we use the word *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.
>
>
> New Coroutine Declaration Syntax
> --------------------------------
>
> The following new syntax is used to declare a coroutine::
>
> async def read_data(db):
> pass
>
> 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, a new code object flag - ``CO_COROUTINE`` - is introduced
> to enable runtime detection of coroutines (and migrating existing
> code). All coroutines have both ``CO_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).
>
>
> types.coroutine()
> -----------------
>
> A new function ``coroutine(gen)`` is added to the ``types`` module. It
> applies ``CO_COROUTINE`` flag to the passed generator-function's code
> object, making it to return a *coroutine object* when called.
>
> This feature enables an easy upgrade path for existing libraries.
>
>
> 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 *coroutine object* returned from a *coroutine* or 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
> explanation.)
>
> 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 ``SyntaxError`` to use ``await`` outside of a coroutine.
>
>
> 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:
> BLOCK
>
>
> which is semantically equivalent to::
>
> mgr = (EXPR)
> aexit = type(mgr).__aexit__
> aenter = type(mgr).__aenter__(mgr)
> exc = True
>
> try:
> try:
> VAR = await aenter
> BLOCK
> except:
> exc = False
> exit_res = await aexit(mgr, *sys.exc_info())
> if not exit_res:
> raise
>
> finally:
> if exc:
> 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 a coroutine.
>
>
> Example
> '''''''
>
> 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
> iteration:
>
> 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``
> exception.
>
> 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
> else:
> raise StopAsyncIteration
>
> async def fetch_data(self):
> ...
>
>
> New Syntax
> ''''''''''
>
> A new statement for iterating through asynchronous iterators is
> proposed::
>
> async for TARGET in ITER:
> BLOCK
> else:
> BLOCK2
>
> which is semantically equivalent to::
>
> iter = (ITER)
> iter = await type(iter).__aiter__(iter)
> running = True
> while running:
> try:
> TARGET = await type(iter).__anext__(iter)
> except StopAsyncIteration:
> running = False
> else:
> BLOCK
> else:
> BLOCK2
>
>
> It is an error to pass a regular iterable without ``__aiter__`` method
> to ``async for``. It is a ``SyntaxError`` to use ``async for`` outside
> of a coroutine.
>
> 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():
> print(row)
>
> which would be equivalent to the following code::
>
> i = await Cursor().__aiter__()
> while True:
> try:
> row = await i.__anext__()
> except StopAsyncIteration:
> break
> else:
> print(row)
>
>
> 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
> iterators.
>
> ::
>
> class AsyncIteratorWrapper:
> def __init__(self, obj):
> self._it = iter(obj)
>
> async def __aiter__(self):
> return self
>
> async def __anext__(self):
> try:
> value = next(self._it)
> except StopIteration:
> raise StopAsyncIteration
> return value
>
> async for item in AsyncIteratorWrapper("abc"):
> print(item)
>
>
> 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'
>
> and
>
> ::
>
> 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
> ``RuntimeError``
>
> ::
>
> 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``.
>
>
> Debugging Features
> ------------------
>
> One of the most frequent mistakes that people make when using
> generators as coroutines is forgetting to use ``yield from``::
>
> @asyncio.coroutine
> 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. New methods ``set_coroutine_wrapper`` and
> ``get_coroutine_wrapper`` are added to the ``sys`` module, with which
> frameworks can provide advanced debugging facilities.
>
> It is also important to make coroutines as fast and efficient as
> possible, therefore there are no debug features enabled by default.
>
> Example::
>
> async def debug_me():
> await asyncio.sleep(1)
>
> def async_debug_wrap(generator):
> return asyncio.AsyncDebugWrapper(generator)
>
> sys.set_coroutine_wrapper(async_debug_wrap)
>
> debug_me() # <- this line will likely GC the coroutine object and
> # trigger AsyncDebugWrapper's code.
>
> assert isinstance(debug_me(), AsyncDebugWrapper)
>
> sys.set_coroutine_wrapper(None) # <- this unsets any
> # previously set wrapper
> assert not isinstance(debug_me(), AsyncDebugWrapper)
>
> If ``sys.set_coroutine_wrapper()`` is called twice, the new wrapper
> replaces the previous wrapper. ``sys.set_coroutine_wrapper(None)``
> unsets the wrapper.
>
>
> Glossary
> ========
>
> :Coroutine:
> A coroutine function, or just "coroutine", is declared with ``async
> def``. It uses ``await`` and ``return value``; see `New Coroutine
> Declaration Syntax`_ for details.
>
> :Coroutine object:
> Returned from a coroutine function. See `Await Expression`_ for
> details.
>
> :Future-like object:
> An object with an ``__await__`` method. 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.
>
> :Awaitable:
> A *Future-like* object or a *coroutine object*. See `Await
> Expression`_ for details.
>
> :Generator-based coroutine:
> Coroutines based in generator syntax. Most common example is
> ``@asyncio.coroutine``.
>
> :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
> ================= =================================== =================
>
> Where:
>
> * "async def func": 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
> *awaitable*;
>
> * "def __await__": ``__await__`` method to implement *Future-like*
> objects;
>
> * 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
> it:
>
> * recognizes ``async def`` name tokens combination (start of a
> coroutine);
>
> * keeps track of regular functions and coroutines;
>
> * replaces ``'async'`` token with ``ASYNC`` and ``'await'`` token with
> ``AWAIT`` when in the process of yielding tokens for coroutines.
>
> This approach allows for seamless combination of new syntax features
> (all of them available only in ``async`` functions) with any existing
> code.
>
> An example of having "async def" and "async" attribute in one piece of
> code::
>
> 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.
>
>
> Grammar Updates
> ---------------
>
> Grammar changes are also fairly minimal::
>
> await_expr: AWAIT test
> await_stmt: await_expr
>
> decorated: decorators (classdef | funcdef | async_funcdef)
> async_funcdef: ASYNC funcdef
>
> async_stmt: ASYNC (funcdef | with_stmt | for_stmt)
>
> compound_stmt: (if_stmt | while_stmt | for_stmt | try_stmt |
> with_stmt | funcdef | classdef | decorated |
> async_stmt)
>
> atom: ('(' [yield_expr|await_expr|testlist_comp] ')' |
> '[' [testlist_comp] ']' |
> '{' [dictorsetmaker] '}' |
> NAME | NUMBER | STRING+ | '...' | 'None' | 'True' | 'False’)
>
> expr_stmt: testlist_star_expr
> (augassign (yield_expr|await_expr|testlist) |
> ('=' (yield_expr|await_expr|testlist_star_expr))*)
>
>
> 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)):
> pass
>
> 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):
> pass
>
> async def foo(): # 2
> return (await fut)
>
> This limitation will go away as soon as ``async`` and ``await`` ate
> proper keywords. Or if it's decided to use a future import for this
> PEP.
>
>
> 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.
>
>
> asyncio
> -------
>
> ``asyncio`` module was adapted and tested to work with coroutines and
> new statements. Backwards compatibility is 100% preserved.
>
> 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_task()`` as an alias for ``async()`` function.
> Deprecate ``async()`` function.
>
>
> 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``
> keyword.
>
> 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. To call *cofunctions* from existing
> generator-based coroutines it would be required to use ``costart``
> built-in. In this proposal ``@asyncio.coroutine`` simply sets
> ``CO_COROUTINE`` on the wrapped function's code object and
> everything works automatically.
>
> 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
> Features`_.
>
> 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-
> generators.
>
> 6. There are no equivalents of ``async for`` and ``async with`` in PEP
> 3152.
>
>
> Coroutine-generators
> --------------------
>
> 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.
>
>
> No implicit wrapping in Futures
> -------------------------------
>
> There is a proposal to add similar mechanism to ECMAScript 7 [2]_. A
> key difference is that JavaScript "async functions" always return a
> Promise. While this approach has some advantages, it also implies that
> a new Promise object is created on each "async function" invocation.
>
> We could implement a similar functionality in Python, by wrapping all
> coroutines in a Future object, but this has the following
> disadvantages:
>
> 1. Performance. A new Future object would be instantiated on each
> coroutine call. Moreover, this makes implementation of ``await``
> expressions slower (disabling optimizations of ``yield from``).
>
> 2. A new built-in ``Future`` object would need to be added.
>
> 3. Coming up with a generic ``Future`` interface that is usable for any
> use case in any framework is a very hard to solve problem.
>
> 4. It is not a feature that is used frequently, when most of the code
> is coroutines.
>
>
> 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__" is a coroutine
> ------------------------------
>
> 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
> operation.
>
>
> 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 a __future__ import
> ---------------------------
>
> ``__future__`` imports are inconvenient and easy to forget to add.
> Also, they are enabled for the whole source file. Consider that there
> is a big project with a popular module named "async.py". With future
> imports it is required to either import it using ``__import__()`` or
> ``importlib.import_module()`` calls, or to rename the module. The
> proposed approach makes it possible to continue using old code and
> modules without a hassle, while coming up with a migration plan for
> future python versions.
>
>
> 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 look confusing and would require some implicit magic behind
> the scenes in the interpreter;
>
> * one of the main points of this proposal is to make coroutines as
> simple and foolproof as possible.
>
>
> Comprehensions
> --------------
>
> For the sake of restricting the broadness of this PEP there is no new
> syntax for asynchronous comprehensions. This should be considered in a
> separate PEP, if there is a strong demand for this feature.
>
>
> Async lambdas
> -------------
>
> Lambda coroutines are not part of this proposal. In this proposal they
> would look like ``async lambda(parameters): expression``. Unless there
> is a strong demand to have them as part of this proposal, it is
> recommended to consider them later in a separate PEP.
>
>
> Performance
> ===========
>
> 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
> ../cpython-aw/python.exe
>
> [skipped]
>
> 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,
> fastpickle,
> 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.
>
>
> async/await
> -----------
>
> 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):
> list(gen(depth))
> 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``
> keyword.
>
> 2. New ``__await__`` method for Future-like objects.
>
> 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``,
> ``Await``.
>
> 6. New functions: ``sys.set_coroutine_wrapper(callback)``,
> ``sys.get_coroutine_wrapper()``, and ``types.coroutine(gen)``.
>
> 7. New ``CO_COROUTINE`` bit flag for code objects.
>
> 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
> tested.
>
> ::
>
> 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:
> break
>
> print('Sending {:.10}... back'.format(repr(data)))
> writer.write(data)
>
> loop = asyncio.get_event_loop()
> loop.run_until_complete(echo_server())
> try:
> loop.run_forever()
> finally:
> loop.close()
>
>
> References
> ==========
>
> .. [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]
> https://github.com/google/traceur-compiler/wiki/LanguageFeatures#async-functions-experimental
>
> .. [10] http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2013/n3722.pdf
> (PDF)
>
>
> Acknowledgments
> ===============
>
> I thank Guido van Rossum, Victor Stinner, Elvis Pranskevichus, Andrew
> Svetlov, and Łukasz Langa for their initial feedback.
>
>
> Copyright
> =========
>
> This document has been placed in the public domain.
>
> _______________________________________________
> Python-Dev mailing list
> Python-Dev at python.org
> https://mail.python.org/mailman/listinfo/python-dev
> Unsubscribe:
> https://mail.python.org/mailman/options/python-dev/tds333%2Bpydev%40gmail.com
>
--
bye by Wolfgang
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