Getting Around the GIL - Parallelizing Python for Better Performance
Offered By: PyCon US via YouTube
Course Description
Overview
Explore techniques for parallelizing Python code to overcome the Global Interpreter Lock (GIL) and enhance performance in data science pipelines. Learn how to speed up CPU-bound programs, data collection, pre-processing, and feature engineering tasks through various parallelization methods. Discover strategies to work with larger datasets and gain deeper insights by reducing execution times. This 31-minute PyCon US talk provides practical approaches to implement parallelism based on specific program requirements and desired outcomes.
Syllabus
Talks - Alireza Farhidzadeh: Getting Around the GIL: Parallelizing Python for Better Performance
Taught by
PyCon US
Related Courses
Multithreaded Python without the GILEuroPython Conference via YouTube Extending Cython with GIL-Free Types
EuroPython Conference via YouTube Is It Me, or the GIL
EuroPython Conference via YouTube Addressing Multithreading and Multiprocessing in Transparent and Pythonic Ways
EuroPython Conference via YouTube Running Python Code in Parallel and Asynchronously
EuroPython Conference via YouTube