What to read after Python Threading Jump-Start?

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 making 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.