PEP: 525 Title: Asynchronous Generators Version: $Revision$ Last-Modified: $Date$ Author: Yury Selivanov Discussions-To: Status: Final Type: Standards Track Content-Type: text/x-rst Created: 28-Jul-2016 Python-Version: 3.6 Post-History: 02-Aug-2016, 23-Aug-2016, 01-Sep-2016, 06-Sep-2016 Abstract ======== PEP 492 introduced support for native coroutines and ``async``/``await`` syntax to Python 3.5. It is proposed here to extend Python's asynchronous capabilities by adding support for *asynchronous generators*. Rationale and Goals =================== Regular generators (introduced in PEP 255) enabled an elegant way of writing complex *data producers* and have them behave like an iterator. However, currently there is no equivalent concept for the *asynchronous iteration protocol* (``async for``). This makes writing asynchronous data producers unnecessarily complex, as one must define a class that implements ``__aiter__`` and ``__anext__`` to be able to use it in an ``async for`` statement. Essentially, the goals and rationale for PEP 255, applied to the asynchronous execution case, hold true for this proposal as well. Performance is an additional point for this proposal: in our testing of the reference implementation, asynchronous generators are **2x** faster than an equivalent implemented as an asynchronous iterator. As an illustration of the code quality improvement, consider the following class that prints numbers with a given delay once iterated:: class Ticker: """Yield numbers from 0 to `to` every `delay` seconds.""" def __init__(self, delay, to): self.delay = delay self.i = 0 self.to = to def __aiter__(self): return self async def __anext__(self): i = self.i if i >= self.to: raise StopAsyncIteration self.i += 1 if i: await asyncio.sleep(self.delay) return i The same can be implemented as a much simpler asynchronous generator:: async def ticker(delay, to): """Yield numbers from 0 to `to` every `delay` seconds.""" for i in range(to): yield i await asyncio.sleep(delay) Specification ============= This proposal introduces the concept of *asynchronous generators* to Python. This specification presumes knowledge of the implementation of generators and coroutines in Python (PEP 342, PEP 380 and PEP 492). Asynchronous Generators ----------------------- A Python *generator* is any function containing one or more ``yield`` expressions:: def func(): # a function return def genfunc(): # a generator function yield We propose to use the same approach to define *asynchronous generators*:: async def coro(): # a coroutine function await smth() async def asyncgen(): # an asynchronous generator function await smth() yield 42 The result of calling an *asynchronous generator function* is an *asynchronous generator object*, which implements the asynchronous iteration protocol defined in PEP 492. It is a ``SyntaxError`` to have a non-empty ``return`` statement in an asynchronous generator. Support for Asynchronous Iteration Protocol ------------------------------------------- The protocol requires two special methods to be implemented: 1. An ``__aiter__`` method returning an *asynchronous iterator*. 2. An ``__anext__`` method returning an *awaitable* object, which uses ``StopIteration`` exception to "yield" values, and ``StopAsyncIteration`` exception to signal the end of the iteration. Asynchronous generators define both of these methods. Let's manually iterate over a simple asynchronous generator:: async def genfunc(): yield 1 yield 2 gen = genfunc() assert gen.__aiter__() is gen assert await gen.__anext__() == 1 assert await gen.__anext__() == 2 await gen.__anext__() # This line will raise StopAsyncIteration. Finalization ------------ PEP 492 requires an event loop or a scheduler to run coroutines. Because asynchronous generators are meant to be used from coroutines, they also require an event loop to run and finalize them. Asynchronous generators can have ``try..finally`` blocks, as well as ``async with``. It is important to provide a guarantee that, even when partially iterated, and then garbage collected, generators can be safely finalized. For example:: async def square_series(con, to): async with con.transaction(): cursor = con.cursor( 'SELECT generate_series(0, $1) AS i', to) async for row in cursor: yield row['i'] ** 2 async for i in square_series(con, 1000): if i == 100: break The above code defines an asynchronous generator that uses ``async with`` to iterate over a database cursor in a transaction. The generator is then iterated over with ``async for``, which interrupts the iteration at some point. The ``square_series()`` generator will then be garbage collected, and without a mechanism to asynchronously close the generator, Python interpreter would not be able to do anything. To solve this problem we propose to do the following: 1. Implement an ``aclose`` method on asynchronous generators returning a special *awaitable*. When awaited it throws a ``GeneratorExit`` into the suspended generator and iterates over it until either a ``GeneratorExit`` or a ``StopAsyncIteration`` occur. This is very similar to what the ``close()`` method does to regular Python generators, except that an event loop is required to execute ``aclose()``. 2. Raise a ``RuntimeError``, when an asynchronous generator executes a ``yield`` expression in its ``finally`` block (using ``await`` is fine, though):: async def gen(): try: yield finally: await asyncio.sleep(1) # Can use 'await'. yield # Cannot use 'yield', # this line will trigger a # RuntimeError. 3. Add two new methods to the ``sys`` module: ``set_asyncgen_hooks()`` and ``get_asyncgen_hooks()``. The idea behind ``sys.set_asyncgen_hooks()`` is to allow event loops to intercept asynchronous generators iteration and finalization, so that the end user does not need to care about the finalization problem, and everything just works. ``sys.set_asyncgen_hooks()`` accepts two arguments: * ``firstiter``: a callable which will be called when an asynchronous generator is iterated for the first time. * ``finalizer``: a callable which will be called when an asynchronous generator is about to be GCed. When an asynchronous generator is iterated for the first time, it stores a reference to the current *finalizer*. When an asynchronous generator is about to be garbage collected, it calls its cached *finalizer*. The assumption is that the finalizer will schedule an ``aclose()`` call with the loop that was active when the iteration started. For instance, here is how asyncio is modified to allow safe finalization of asynchronous generators:: # asyncio/base_events.py class BaseEventLoop: def run_forever(self): ... old_hooks = sys.get_asyncgen_hooks() sys.set_asyncgen_hooks(finalizer=self._finalize_asyncgen) try: ... finally: sys.set_asyncgen_hooks(*old_hooks) ... def _finalize_asyncgen(self, gen): self.create_task(gen.aclose()) The second argument, ``firstiter``, allows event loops to maintain a weak set of asynchronous generators instantiated under their control. This makes it possible to implement "shutdown" mechanisms to safely finalize all open generators and close the event loop. ``sys.set_asyncgen_hooks()`` is thread-specific, so several event loops running in parallel threads can use it safely. ``sys.get_asyncgen_hooks()`` returns a namedtuple-like structure with ``firstiter`` and ``finalizer`` fields. asyncio ------- The asyncio event loop will use ``sys.set_asyncgen_hooks()`` API to maintain a weak set of all scheduled asynchronous generators, and to schedule their ``aclose()`` coroutine methods when it is time for generators to be GCed. To make sure that asyncio programs can finalize all scheduled asynchronous generators reliably, we propose to add a new event loop coroutine method ``loop.shutdown_asyncgens()``. The method will schedule all currently open asynchronous generators to close with an ``aclose()`` call. After calling the ``loop.shutdown_asyncgens()`` method, the event loop will issue a warning whenever a new asynchronous generator is iterated for the first time. The idea is that after requesting all asynchronous generators to be shutdown, the program should not execute code that iterates over new asynchronous generators. An example of how ``shutdown_asyncgens`` coroutine should be used:: try: loop.run_forever() finally: loop.run_until_complete(loop.shutdown_asyncgens()) loop.close() Asynchronous Generator Object ----------------------------- The object is modeled after the standard Python generator object. Essentially, the behaviour of asynchronous generators is designed to replicate the behaviour of synchronous generators, with the only difference in that the API is asynchronous. The following methods and properties are defined: 1. ``agen.__aiter__()``: Returns ``agen``. 2. ``agen.__anext__()``: Returns an *awaitable*, that performs one asynchronous generator iteration when awaited. 3. ``agen.asend(val)``: Returns an *awaitable*, that pushes the ``val`` object in the ``agen`` generator. When the ``agen`` has not yet been iterated, ``val`` must be ``None``. Example:: async def gen(): await asyncio.sleep(0.1) v = yield 42 print(v) await asyncio.sleep(0.2) g = gen() await g.asend(None) # Will return 42 after sleeping # for 0.1 seconds. await g.asend('hello') # Will print 'hello' and # raise StopAsyncIteration # (after sleeping for 0.2 seconds.) 4. ``agen.athrow(typ, [val, [tb]])``: Returns an *awaitable*, that throws an exception into the ``agen`` generator. Example:: async def gen(): try: await asyncio.sleep(0.1) yield 'hello' except ZeroDivisionError: await asyncio.sleep(0.2) yield 'world' g = gen() v = await g.asend(None) print(v) # Will print 'hello' after # sleeping for 0.1 seconds. v = await g.athrow(ZeroDivisionError) print(v) # Will print 'world' after $ sleeping 0.2 seconds. 5. ``agen.aclose()``: Returns an *awaitable*, that throws a ``GeneratorExit`` exception into the generator. The *awaitable* can either return a yielded value, if ``agen`` handled the exception, or ``agen`` will be closed and the exception will propagate back to the caller. 6. ``agen.__name__`` and ``agen.__qualname__``: readable and writable name and qualified name attributes. 7. ``agen.ag_await``: The object that ``agen`` is currently *awaiting* on, or ``None``. This is similar to the currently available ``gi_yieldfrom`` for generators and ``cr_await`` for coroutines. 8. ``agen.ag_frame``, ``agen.ag_running``, and ``agen.ag_code``: defined in the same way as similar attributes of standard generators. ``StopIteration`` and ``StopAsyncIteration`` are not propagated out of asynchronous generators, and are replaced with a ``RuntimeError``. Implementation Details ---------------------- Asynchronous generator object (``PyAsyncGenObject``) shares the struct layout with ``PyGenObject``. In addition to that, the reference implementation introduces three new objects: 1. ``PyAsyncGenASend``: the awaitable object that implements ``__anext__`` and ``asend()`` methods. 2. ``PyAsyncGenAThrow``: the awaitable object that implements ``athrow()`` and ``aclose()`` methods. 3. ``_PyAsyncGenWrappedValue``: every directly yielded object from an asynchronous generator is implicitly boxed into this structure. This is how the generator implementation can separate objects that are yielded using regular iteration protocol from objects that are yielded using asynchronous iteration protocol. ``PyAsyncGenASend`` and ``PyAsyncGenAThrow`` are awaitables (they have ``__await__`` methods returning ``self``) and are coroutine-like objects (implementing ``__iter__``, ``__next__``, ``send()`` and ``throw()`` methods). Essentially, they control how asynchronous generators are iterated: .. image:: pep-0525-1.png :align: center :width: 80% PyAsyncGenASend and PyAsyncGenAThrow ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ``PyAsyncGenASend`` is a coroutine-like object that drives ``__anext__`` and ``asend()`` methods and implements the asynchronous iteration protocol. ``agen.asend(val)`` and ``agen.__anext__()`` return instances of ``PyAsyncGenASend`` (which hold references back to the parent ``agen`` object.) The data flow is defined as follows: 1. When ``PyAsyncGenASend.send(val)`` is called for the first time, ``val`` is pushed to the parent ``agen`` object (using existing facilities of ``PyGenObject``.) Subsequent iterations over the ``PyAsyncGenASend`` objects, push ``None`` to ``agen``. When a ``_PyAsyncGenWrappedValue`` object is yielded, it is unboxed, and a ``StopIteration`` exception is raised with the unwrapped value as an argument. 2. When ``PyAsyncGenASend.throw(*exc)`` is called for the first time, ``*exc`` is thrown into the parent ``agen`` object. Subsequent iterations over the ``PyAsyncGenASend`` objects, push ``None`` to ``agen``. When a ``_PyAsyncGenWrappedValue`` object is yielded, it is unboxed, and a ``StopIteration`` exception is raised with the unwrapped value as an argument. 3. ``return`` statements in asynchronous generators raise ``StopAsyncIteration`` exception, which is propagated through ``PyAsyncGenASend.send()`` and ``PyAsyncGenASend.throw()`` methods. ``PyAsyncGenAThrow`` is very similar to ``PyAsyncGenASend``. The only difference is that ``PyAsyncGenAThrow.send()``, when called first time, throws an exception into the parent ``agen`` object (instead of pushing a value into it.) New Standard Library Functions and Types ---------------------------------------- 1. ``types.AsyncGeneratorType`` -- type of asynchronous generator object. 2. ``sys.set_asyncgen_hooks()`` and ``sys.get_asyncgen_hooks()`` methods to set up asynchronous generators finalizers and iteration interceptors in event loops. 3. ``inspect.isasyncgen()`` and ``inspect.isasyncgenfunction()`` introspection functions. 4. New method for asyncio event loop: ``loop.shutdown_asyncgens()``. 5. New ``collections.abc.AsyncGenerator`` abstract base class. Backwards Compatibility ----------------------- The proposal is fully backwards compatible. In Python 3.5 it is a ``SyntaxError`` to define an ``async def`` function with a ``yield`` expression inside, therefore it's safe to introduce asynchronous generators in 3.6. Performance =========== Regular Generators ------------------ There is no performance degradation for regular generators. The following micro benchmark runs at the same speed on CPython with and without asynchronous generators:: def gen(): i = 0 while i < 100000000: yield i i += 1 list(gen()) Improvements over asynchronous iterators ---------------------------------------- The following micro-benchmark shows that asynchronous generators are about **2.3x faster** than asynchronous iterators implemented in pure Python:: N = 10 ** 7 async def agen(): for i in range(N): yield i class AIter: def __init__(self): self.i = 0 def __aiter__(self): return self async def __anext__(self): i = self.i if i >= N: raise StopAsyncIteration self.i += 1 return i Design Considerations ===================== ``aiter()`` and ``anext()`` builtins ------------------------------------ Originally, PEP 492 defined ``__aiter__`` as a method that should return an *awaitable* object, resulting in an asynchronous iterator. However, in CPython 3.5.2, ``__aiter__`` was redefined to return asynchronous iterators directly. To avoid breaking backwards compatibility, it was decided that Python 3.6 will support both ways: ``__aiter__`` can still return an *awaitable* with a ``DeprecationWarning`` being issued. Because of this dual nature of ``__aiter__`` in Python 3.6, we cannot add a synchronous implementation of ``aiter()`` built-in. Therefore, it is proposed to wait until Python 3.7. Asynchronous list/dict/set comprehensions ----------------------------------------- Syntax for asynchronous comprehensions is unrelated to the asynchronous generators machinery, and should be considered in a separate PEP. Asynchronous ``yield from`` --------------------------- While it is theoretically possible to implement ``yield from`` support for asynchronous generators, it would require a serious redesign of the generators implementation. ``yield from`` is also less critical for asynchronous generators, since there is no need provide a mechanism of implementing another coroutines protocol on top of coroutines. And to compose asynchronous generators a simple ``async for`` loop can be used:: async def g1(): yield 1 yield 2 async def g2(): async for v in g1(): yield v Why the ``asend()`` and ``athrow()`` methods are necessary ---------------------------------------------------------- They make it possible to implement concepts similar to ``contextlib.contextmanager`` using asynchronous generators. For instance, with the proposed design, it is possible to implement the following pattern:: @async_context_manager async def ctx(): await open() try: yield finally: await close() async with ctx(): await ... Another reason is that it is possible to push data and throw exceptions into asynchronous generators using the object returned from ``__anext__`` object, but it is hard to do that correctly. Adding explicit ``asend()`` and ``athrow()`` will pave a safe way to accomplish that. In terms of implementation, ``asend()`` is a slightly more generic version of ``__anext__``, and ``athrow()`` is very similar to ``aclose()``. Therefore, having these methods defined for asynchronous generators does not add any extra complexity. Example ======= A working example with the current reference implementation (will print numbers from 0 to 9 with one second delay):: async def ticker(delay, to): for i in range(to): yield i await asyncio.sleep(delay) async def run(): async for i in ticker(1, 10): print(i) import asyncio loop = asyncio.get_event_loop() try: loop.run_until_complete(run()) finally: loop.close() Acceptance ========== PEP 525 was accepted by Guido, September 6, 2016 [2]_. Implementation ============== The implementation is tracked in issue 28003 [3]_. The reference implementation git repository is available at [1]_. References ========== .. [1] https://github.com/1st1/cpython/tree/async_gen .. [2] https://mail.python.org/pipermail/python-dev/2016-September/146267.html .. [3] http://bugs.python.org/issue28003 Acknowledgments =============== I thank Guido van Rossum, Victor Stinner, Elvis Pranskevichus, Nathaniel Smith, Łukasz Langa, Andrew Svetlov and many others for their feedback, code reviews, and discussions around this PEP. Copyright ========= 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 End: