# Python Threading Jump-Start

![Python Threading Jump-Start](cover.png)

* <https://github.com/SuperFastPython/PythonThreadingJumpStart>

This repository provides all source code for the book:

* **Python Threading Jump-Start**: _Develop Concurrent IO-bound Programs And Work With The GIL_, Jason Brownlee, 2022.


## Source Code
You can access all Python .py files directly here:

* [src/](src/)


## Get the Book

You can learn more about the book here:

* [Gumroad](https://superfastpython.gumroad.com/l/ptj)
* [Amazon Paperback](https://amzn.to/3Q4BU54)
* [Amazon Kindle](https://amzn.to/3Sn9x3w)
* [GooglePlay](https://play.google.com/store/books/details?id=m0V_EAAAQBAJ)
* [GoogleBooks](https://books.google.com/books/about?id=m0V_EAAAQBAJ)
* [Goodreads](https://www.goodreads.com/book/show/61863433-python-threading-jump-start)


### Book Blurb

> Unlock concurrency with Python threads (and run 100s or 1,000s of tasks simultaneously).
>
> The threading module provides easy-to-use thread-based concurrency in Python.
>
> Unlike Python multiprocessing, the threading module is limited by the infamous Global Interpreter Lock (GIL).
>
> Critically, the GIL is released when performing blocking I/O. Additionally, threads can share memory make them perfectly suited to I/O-bound tasks such as reading and writing from files and socket connections.
>
> This is the API you need to use to make your code run faster.
>
> Introducing: "Python Threading Jump-Start". A new book designed to teach you the threading module in Python, super fast!
>
> You will get a rapid-paced, 7-part course to get you started and make you awesome at using the threading API.
>
> Each of the 7 lessons was carefully designed to teach one critical aspect of the threading module, with explanations, code snippets and worked examples.
>
> You will discover:
>
> * How to choose tasks that are well suited to threads.
> * How to create and run new threads.
> * How to locate and query running threads.
> * How to use locks, semaphores, barriers and more.
> * How to share data between threads using queues.
> * How to execute ad hoc tasks with reusable worker threads.
> * How to gracefully stop and forcefully kill threads.
>
> Each lesson ends with an exercise for you to complete to confirm you understand the topic, a summary of what was learned, and links for further reading if you want to go deeper.
>
> Stop copy-pasting code from StackOverflow answers.
>
> Learn Python concurrency correctly, step-by-step.