Скачать или смотреть Jakub Urban - Async to Distributed: Concurrency Patterns for Data Processing (PyData Prague #30)

Jakub Urban - Async to Distributed: Concurrency Patterns for Data Processing

How to make your Python data workflows scale and run faster? We will explore built‑in concurrent.futures and asyncio patterns, and then show if and how to scale using frameworks like Dask or Ray. We will focus on practical recipes for CPU (or GPU) and memory demanding tasks, typical for data processing.

Presented at PyData Prague #30 - Pro: To Type Asynchronously (24.9.2025 at Qminers)

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