Lessons Learned in X Years of Parallel Programming

Explore the intricacies of parallel programming in Python through this insightful 34-minute conference talk from EuroPython 2017. Delve into advanced topics beyond multiprocessing.Pool().map, including performance measurement, memory management, data transfer optimization, and debugging techniques for parallel programs. Gain practical knowledge from real-world examples in both enterprise and scientific programming contexts. Learn about the convenience of parallel programming on single machines and discover key considerations for medium-sized cluster environments. Examine a compatibility layer developed to work across various parallelization technologies, including multiprocessing, concurrent.futures, celery, ipyparallel, and grid engine.