This repository provides all source code for the book:
- Python ThreadPoolExecutor Jump-Start: Execute IO-Bound Tasks Asynchronously With Modern Thread Pools, Jason Brownlee, 2022.
You can access all Python .py files directly here:
You can learn more about the book here:
How much faster could your Python code run (if you used 100s of thread workers)?
The ThreadPoolExecutor class provides modern thread pools for IO-bound tasks.
This is not some random third-party library, this is a class provided in the Python standard library (already installed on your system).
This is the class you need to make your code run faster.
There's just one problem. No one knows about it (or how to use it well).
Introducing: "Python ThreadPoolExecutor Jump-Start". A new book designed to teach you thread pools in Python, super fast!
You will get a rapid-paced, 7-part course to get you started and make you awesome at using the ThreadPoolExecutor.
Including:
- How to create thread pools and when to use them.
- How to configure thread pools including the number of threads.
- How to execute tasks with worker threads and handle for results.
- How to execute tasks in the thread pool asynchronously.
- How to query and get results from handles on asynchronous tasks called futures.
- How to wait on and manage diverse collections of asynchronous tasks.
- How to develop a concurrent website status checker that is 5x faster than the sequential version.
Each of the 7 lessons was carefully designed to teach one critical aspect of the ThreadPoolExecutor, with explanations, code snippets and worked examples.
Each lesson ends with an exercise for you to complete to confirm you understood 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.