Python Concurrency & Parallel Programming

Learning Path ⋅ Skills: Multithreading, Multiprocessing, Async IO

Speed Up Your Python Program With Concurrency

With this learning path you’ll gain a deep understanding of concurrency and parallel programming in Python. You can use these newfound skills to speed up CPU or IO-bound Python programs.

Python Concurrency & Parallel Programming

Learning Path ⋅ 6 Resources

Speed Up Your Python Program With Concurrency

Tutorial

Speed Up Your Python Program With Concurrency

Learn what concurrency means in Python and why you might want to use it. You'll see a simple, non-concurrent approach and then look into why you'd want threading, asyncio, or multiprocessing.

(⭐⭐⭐ Advanced)
Speed Up Your Python Program With Concurrency

Interactive Quiz

Python Concurrency Quiz

In this quiz you’ll review topics covered in the Speed Up Your Python Program With Concurrency tutorial.

(⭐⭐⭐ Advanced)
Async IO in Python: A Complete Walkthrough

Course

Hands-on Python 3 Concurrency With the asyncio Module

Learn how to speed up your Python 3 programs using concurrency and the asyncio module in the standard library.

(⭐⭐⭐ Advanced)
An Intro to Threading in Python

Tutorial

An Intro to Threading in Python

Learn how to use threading in your Python programs. You'll see how to create threads, how to coordinate and synchronize them, and how to handle common problems that arise in threading.

(⭐⭐⭐ Advanced)
Async IO in Python: A Complete Walkthrough

Tutorial

Async IO in Python: A Complete Walkthrough

This tutorial will give you a firm grasp of Python’s approach to async IO, which is a concurrent programming design that has received dedicated support in Python, evolving rapidly from Python 3.4 through 3.7 (and probably beyond).

(⭐⭐⭐ Advanced)
Advanced Python

Tutorial

What is the Python Global Interpreter Lock (GIL)?

Learn how the GIL affects the performance of your Python programs.

(⭐⭐⭐ Advanced)
Core Python Tutorials Artwork

Course

Parallel Map Reduce in Python

How to do parallel processing with multiprocessing and concurrent.futures using a functional programming map-reduce approach.

(⭐⭐⭐ Advanced)

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