Speed Up Python With Concurrency

Concurrency is the act of having your computer do multiple things at the same time. If you’ve heard lots of talk about asyncio being added to Python but are curious how it compares to other concurrency methods or are wondering what concurrency is and how it might speed up your program, you’ve come to the right place.

In this course, you’ll learn the following:

  • How I/O bound programs are effected by latency
  • Which concurrent programming patterns to use
  • What the differences are between the Python concurrency libraries
  • How to write code that uses the threading, asyncio, and multiprocessing libraries

Sample code was tested using Python 3.8.5. Much of the asyncio library has been in flux since Python 3.4, it is recommended to use at least Python 3.7 for the asyncio portions of the course.

What’s Included:

  • 10 Lessons
  • Video Subtitles and Full Transcripts
  • 2 Downloadable Resources
  • Accompanying Text-Based Tutorial
  • Interactive Quiz to Check Your Progress
  • Q&A With Python Experts: Ask a Question
  • Certificate of Completion

Downloadable Resources:

Related Learning Paths:

About Christopher Trudeau

Christopher has a passion for the Python language and writes for Real Python. He is a consultant who helps advise organizations on how to improve their technical teams.

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Each tutorial at Real Python is created by a team of developers so that it meets our high quality standards. The team members who worked on this tutorial are:

Participant Comments

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danP on Dec. 1, 2021

Awesome lesson, with the added benefit of finally understanding what the GIL actually does!

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