The Best 10 Python Concurrency and Parallelism Libraries

MPIRE, short for MultiProcessing Is Really Easy, is a Python package for multiprocessing, but faster and more user-friendly than the default multiprocessing package.

Trio – a friendly Python library for async concurrency and I/O The Trio project aims to produce a production-quality, permissively licensed, async/awa

SCOOP (Scalable COncurrent Operations in Python) is a distributed task module allowing concurrent parallel programming on various environments, from h

uvloop is a fast, drop-in replacement of the built-in asyncio event loop. uvloop is implemented in Cython and uses libuv under the hood. The project d

Awesome asyncio A carefully curated list of awesome Python asyncio frameworks, libraries, software and resources. The Python asyncio module introduced

Parallelformers: An Efficient Model Parallelization Toolkit for Deployment

Concurrent Sync A concurrent sync tool which works similar to rsync. It supports syncing given sources with multiple targets concurrently. Requirement

A lightweight (serverless) native python parallel processing framework based on simple decorators and call graphs, supporting both control flow and dataflow execution paradigms as well as de-centralized CPU & GPU scheduling.

future-map is a Python library to use together with the official concurrent.futures module.

rosny is a lightweight library for building concurrent systems. Installation Tested on: Linux Python = 3.6 From pip: pip install rosny From source: p