jmoldow-python3-async-tutorial

Tutorial for everything async in Python3: generators, coroutines, async/await syntax, and asyncio.

Author: Jordan Moldow
License: Apache License, Version 2.0
Git Repo URL: https://github.com/jmoldow/jmoldow-python3-async-tutorial
Website: https://jmoldow.github.io/jmoldow-python3-async-tutorial

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Table of Contents

• Introduction
• Chapter 1 - Iterators and iterables review
• Chapter 2 - Generators revisited
• Chapter 3 - yield from syntax for delegating to subgenerator
• Chapter 4 - Event loops
• Chapter 5 - Event loop futures
• Locally running the Jupyter notebooks
• Copyright Attributions
• License

Introduction

Have you ever seen code like:

# Code sample from <https://github.com/aio-libs/aiohttp/blob/2.0.4/README.rst>
# Copyright (c) 2013-2017 Nikolay Kim, Andrew Svetlov, and other aiohttp contributors: <https://github.com/aio-libs/aiohttp/blob/2.0.4/CONTRIBUTORS.txt>.
# License: Apache Software License, Version 2.0, <https://github.com/aio-libs/aiohttp/blob/2.0.4/LICENSE.txt>
async def fetch(session, url):
    with aiohttp.Timeout(10, loop=session.loop):
        async with session.get(url) as response:
            return await response.text()

and wondered things like:

• What do these async and await keywords do?
• What does it look like when this code executes?
• How does this asynchronous execution work?

Or perhaps you've never seen this style of Python programming before.

If any of these things apply to you, I hope that this tutorial can be educational for you.

Python 3.4 introduced, via the proposal in PEP 3156, the asyncio standard library module, a Python standard for asynchronous programming and event loops.

Python 3.5 expanded this, via the proposal in PEP 492, which extended the syntax of the Python language with the async and await keywords, and also introduced the notion of native coroutines and awaitables.

I had a difficult time understanding these features. On multiple occasions, I read the PEPs and the language reference. I also listened to a few conference talks on the subject. While these references gave good information on the "what" of the material ("asyncio provides an event loop that can run multiple IO-bound tasks on a single thread", "async def lets you define an asynchronous coroutine", "await waits on the value of a coroutine/future and returns the final result", etc.), they did not help me develop a mental model of what these things actually meant, how they worked at runtime, or how one would write or run asynchronous code.

After many attempts, with the help of reading the CPython source code, I've finally developed a decent understanding of what is going on with those features. Since I personally had trouble learning via the existing documentations and conference talk videos, I'm hoping that this tutorial can make the topic more accessible to others who might not understand it yet.

This tutorial is meant to cement my own understanding of async programming in Python, as well as to augment the existing body of documentation on these subjects, since I personally found them to be lacking for beginners.

We'll start from simple generators, moving to yield from syntax, and then to coroutines. From there we'll show how the language was extended with async/await syntax and native coroutines, and then finally we'll look at how the asyncio library executes these coroutines via its event loop.

Locally running the Jupyter notebooks

Bootstrapping requirements

• python3.6
• virtualenv
• make (setup can be performed manually if make isn't available)
• git clone https://github.com/jmoldow/jmoldow-python3-async-tutorial.git

Notebook requirements

See requirements.txt.

Commands

Start the server

make run_jupyter_notebook

This will create a new python3.6 virtualenv in this directory, install the latest versions of all the project's PyPI dependencies listed in requirements.txt, and start the Jupyter notebook server. When the server starts, the home page will be opened in the default web browser.

Manually start the server

make && source .pyvenv/bin/activate && python -m jupyter notebook

This does the same thing as make run_jupyter_notebook, but allows you to pass custom options to jupyter.

Clean the repository

make clean

This will delete everything that hasn't already been committed.

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Copyright Attributions

This projects includes code samples from https://github.com/python/cpython/tree/v3.6.1.
Copyright (c) 2001-2017 Python Software Foundation.
All Rights Reserved.
License: Python license, https://www.python.org/3.6/license.html

This projects includes code samples from https://github.com/aio-libs/aiohttp/tree/2.0.4.
Copyright (c) 2013-2017 Nikolay Kim, Andrew Svetlov, and other aiohttp contributors: https://github.com/aio-libs/aiohttp/blob/2.0.4/CONTRIBUTORS.txt.
License: Apache Software License, Version 2.0, https://github.com/aio-libs/aiohttp/blob/2.0.4/LICENSE.txt

License

License: Apache License, Version 2.0
Jordan Moldow, 2017

Copyright 2017 Jordan Moldow

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.