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docs/source/interactive/autoawait.rst

@@ -1,316 +1,316 b''
 .. _autoawait:
 
 Asynchronous in REPL: Autoawait
 ===============================
 
 .. note::
 
    This feature is experimental and behavior can change between python and
    IPython version without prior deprecation.
 
 Starting with IPython 7.0, and when user Python 3.6 and above, IPython offer the
 ability to run asynchronous code from the REPL. Constructs which are
 :exc:`SyntaxError` s in the Python REPL can be used seamlessly in IPython.
 
 The examples given here are for terminal IPython, running async code in a
 notebook interface or any other frontend using the Jupyter protocol needs
 IPykernel version 5.0 or above. The details of how async code runs in IPykernel
 will differ between IPython, IPykernel and their versions.
 
 When a supported library is used, IPython will automatically allow Futures and
 Coroutines in the REPL to be ``await`` ed. This will happen if an :ref:`await
 <await>` (or any other async constructs like async-with, async-for) is use at
 top level scope, or if any structure valid only in `async def
 <https://docs.python.org/3/reference/compound_stmts.html#async-def>`_ function
 context are present. For example, the following being a syntax error in the
 Python REPL::
 
     Python 3.6.0 
     [GCC 4.2.1]
     Type "help", "copyright", "credits" or "license" for more information.
     >>> import aiohttp
     >>> result = aiohttp.get('https://api.github.com')
     >>> response = await result
       File "<stdin>", line 1
         response = await result
                               ^
     SyntaxError: invalid syntax
 
 Should behave as expected in the IPython REPL::
 
     Python 3.6.0
     Type 'copyright', 'credits' or 'license' for more information
     IPython 7.0.0 -- An enhanced Interactive Python. Type '?' for help.
 
     In [1]: import aiohttp
        ...: result = aiohttp.get('https://api.github.com')
 
     In [2]: response = await result
     <pause for a few 100s ms>
 
     In [3]: await response.json()
     Out[3]:
     {'authorizations_url': 'https://api.github.com/authorizations',
      'code_search_url': 'https://api.github.com/search/code?q={query}...',
     ...
     }
 
 
 You can use the ``c.InteractiveShell.autoawait`` configuration option and set it
 to :any:`False` to deactivate automatic wrapping of asynchronous code. You can
 also use the :magic:`%autoawait` magic to toggle the behavior at runtime::
 
     In [1]: %autoawait False
 
     In [2]: %autoawait
     IPython autoawait is `Off`, and set to use `asyncio`
 
 
 
 By default IPython will assume integration with Python's provided
 :mod:`asyncio`, but integration with other libraries is provided. In particular
 we provide experimental integration with the ``curio`` and ``trio`` library.
 
 You can switch current integration by using the
 ``c.InteractiveShell.loop_runner`` option or the ``autoawait <name
 integration>`` magic.
 
 For example::
 
     In [1]: %autoawait trio
 
     In [2]: import trio
 
     In [3]: async def child(i):
        ...:     print("   child %s goes to sleep"%i)
        ...:     await trio.sleep(2)
        ...:     print("   child %s wakes up"%i)
 
     In [4]: print('parent start')
        ...: async with trio.open_nursery() as n:
        ...:     for i in range(5):
        ...:         n.spawn(child, i)
        ...: print('parent end')
     parent start
        child 2 goes to sleep
        child 0 goes to sleep
        child 3 goes to sleep
        child 1 goes to sleep
        child 4 goes to sleep
        <about 2 seconds pause>
        child 2 wakes up
        child 1 wakes up
        child 0 wakes up
        child 3 wakes up
        child 4 wakes up
     parent end
 
 
 In the above example, ``async with`` at top level scope is a syntax error in
 Python.
 
 Using this mode can have unexpected consequences if used in interaction with
 other features of IPython and various registered extensions. In particular if
 you are a direct or indirect user of the AST transformers, these may not apply
 to your code.
 
 When using command line IPython, the default loop (or runner) does not process
 in the background, so top level asynchronous code must finish for the REPL to
 allow you to enter more code. As with usual Python semantic, the awaitables are
 started only when awaited for the first time. That is to say, in first example,
 no network request is done between ``In[1]`` and ``In[2]``.
 
 
 Effects on IPython.embed()
-==========================
+--------------------------
 
 IPython core being asynchronous, the use of ``IPython.embed()`` will now require
 a loop to run. By default IPython will use a fake coroutine runner which should
 allow ``IPython.embed()`` to be nested. Though this will prevent usage of the
 ``autoawait`` feature when using IPython embed. 
 
 You can set explicitly a coroutine runner for ``embed()`` if you desire to run
 asynchronous code, the exact behavior is though undefined.
 
 Effects on Magics
-=================
+-----------------
 
 A couple of magics (``%%timeit``, ``%timeit``, ``%%time``, ``%%prun``) have not
 yet been updated to work with asynchronous code and will raise syntax errors
 when trying to use top-level ``await``. We welcome any contribution to help fix
 those, and extra cases we haven't caught yet. We hope for better support in Cor
 Python for top-level Async code.
 
 Internals
-=========
+---------
 
 As running asynchronous code is not supported in interactive REPL (as of Python
 3.7) we have to rely to a number of complex workaround and heuristic to allow
 this to happen. It is interesting to understand how this works in order to
 comprehend potential bugs, or provide a custom runner.
 
 Among the many approaches that are at our disposition, we find only one that
 suited out need. Under the hood we use the code object from a async-def function
 and run it in global namespace after modifying it to not create a new
 ``locals()`` scope::
 
     async def inner_async():
         locals().update(**global_namespace)
         #
         # here is user code
         #
         return last_user_statement
     codeobj = modify(inner_async.__code__)
     coroutine = eval(codeobj, user_ns)
     display(loop_runner(coroutine))
 
 
 
 The first thing you'll notice is that unlike classical ``exec``, there is only
 one namespace. Second, user code runs in a function scope, and not a module
 scope.
 
 On top of the above there are significant modification to the AST of
 ``function``, and ``loop_runner`` can be arbitrary complex. So there is a
 significant overhead to this kind of code.
 
 By default the generated coroutine function will be consumed by Asyncio's
 ``loop_runner = asyncio.get_evenloop().run_until_complete()`` method if
 ``async`` mode is deemed necessary, otherwise the coroutine will just be
 exhausted in a simple runner. It is though possible to change the default
 runner.
 
 A loop runner is a *synchronous*  function responsible from running a coroutine
 object.
 
 The runner is responsible from ensuring that ``coroutine`` run to completion,
 and should return the result of executing the coroutine. Let's write a
 runner for ``trio`` that print a message when used as an exercise, ``trio`` is
 special as it usually prefer to run a function object and make a coroutine by
 itself, we can get around this limitation by wrapping it in an async-def without
 parameters and passing this value to ``trio``::
 
 
     In [1]: import trio
        ...: from types import CoroutineType
        ...:
        ...: def trio_runner(coro:CoroutineType):
        ...:     print('running asynchronous code')
        ...:     async def corowrap(coro):
        ...:         return await coro
        ...:     return trio.run(corowrap, coro)
 
 We can set it up by passing it to ``%autoawait``::
 
     In [2]: %autoawait trio_runner
 
     In [3]: async def async_hello(name):
        ...:     await trio.sleep(1)
        ...:     print(f'Hello {name} world !')
        ...:     await trio.sleep(1)
 
     In [4]: await async_hello('async')
     running asynchronous code
     Hello async world !
 
 
 Asynchronous programming in python (and in particular in the REPL) is still a
 relatively young subject. We expect some code to not behave as you expect, so
 feel free to contribute improvements to this codebase and give us feedback.
 
 We invite you to thoroughly test this feature and report any unexpected behavior
 as well as propose any improvement.
 
 Using Autoawait in a notebook (IPykernel)
-=========================================
+-----------------------------------------
 
 Update ipykernel to version 5.0 or greater::
 
    pip install ipykernel ipython --upgrade
    # or
    conda install ipykernel ipython --upgrade
 
 This should automatically enable ``autoawait`` integration. Unlike terminal
 IPython, all code runs on ``asyncio`` eventloop, so creating a loop by hand will
 not work, including with magics like ``%run`` or other frameworks that create
 the eventloop themselves. In cases like these you can try to use projects like
 `nest_asyncio <https://github.com/erdewit/nest_asyncio>`_ and follow `this discussion
 <https://github.com/jupyter/notebook/issues/3397#issuecomment-419386811>`_
 
 Difference between terminal IPython and IPykernel
-=================================================
+-------------------------------------------------
 
 The exact asynchronous code running behavior varies between Terminal IPython and
 IPykernel. The root cause of this behavior is due to IPykernel having a
-_persistent_ ``asyncio`` loop running, while Terminal IPython starts and stops a
+*persistent* ``asyncio`` loop running, while Terminal IPython starts and stops a
 loop for each code block. This can lead to surprising behavior in some case if
 you are used to manipulate asyncio loop yourself, see for example
 :ghissue:`11303` for a longer discussion but here are some of the astonishing
 cases.
 
 This behavior is an implementation detail, and should not be relied upon. It can
 change without warnings in future versions of IPython.
 
 In terminal IPython a loop is started for each code blocks only if there is top
 level async code::
 
    $ ipython
    In [1]: import asyncio
       ...: asyncio.get_event_loop()
    Out[1]: <_UnixSelectorEventLoop running=False closed=False debug=False>
 
    In [2]:
 
    In [2]: import asyncio
       ...: await asyncio.sleep(0)
       ...: asyncio.get_event_loop()
    Out[2]: <_UnixSelectorEventLoop running=True closed=False debug=False>
 
 See that ``running`` is ``True`` only in the case were we ``await sleep()``
 
 In a Notebook, with ipykernel the asyncio eventloop is always running::
 
    $ jupyter notebook
    In [1]: import asyncio
       ...: loop1 = asyncio.get_event_loop()
       ...: loop1
    Out[1]: <_UnixSelectorEventLoop running=True closed=False debug=False>
 
    In [2]: loop2 = asyncio.get_event_loop()
       ...: loop2
    Out[2]: <_UnixSelectorEventLoop running=True closed=False debug=False>
 
    In [3]: loop1 is loop2
    Out[3]: True
 
 In Terminal IPython background tasks are only processed while the foreground
 task is running, if and only if the foreground task is async::
 
    $ ipython
    In [1]: import asyncio
       ...:
       ...: async def repeat(msg, n):
       ...:     for i in range(n):
       ...:         print(f"{msg} {i}")
       ...:         await asyncio.sleep(1)
       ...:     return f"{msg} done"
       ...:
       ...: asyncio.ensure_future(repeat("background", 10))
    Out[1]: <Task pending coro=<repeat() running at <ipython-input-1-02d0ef250fe7>:3>>
 
    In [2]: await asyncio.sleep(3)
    background 0
    background 1
    background 2
    background 3
 
    In [3]: import time
    ...: time.sleep(5)
 
    In [4]: await asyncio.sleep(3)
    background 4
    background 5
    background 6g
 
 In a Notebook, QtConsole, or any other frontend using IPykernel, background
 tasks should behave as expected.