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Top 23 Python Multiprocessing Projects
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Judoscale
Save 47% on cloud hosting with autoscaling that just works. Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
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Plutus
An automated bitcoin wallet collider that brute forces random wallet addresses (by Isaacdelly)
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pyper – Concurrent Python made simple
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root@cc0fa40c9237:~# imgp usage: imgp [-h] [-x res] [-o deg] [-a] [-c] [-e] [-f] [-H] [-i] [-k] [-m] [-M res] [-n] [-N] [-O] [-P] [-q N] [-r] [-s byte] [-w] [-d] [PATH ...] Resize, rotate JPEG and PNG images. positional arguments: PATH source file or dir [default: current dir] options: -h, --help show this help message and exit -x res, --res res output resolution in HxV or percentage -o deg, --rotate deg rotate clockwise by angle (in degrees) -a, --adapt adapt to resolution by orientation [default: off] -c, --convert convert PNG to JPG format [default: off] -e, --eraseexif erase exif metadata [default: off] -f, --force force to exact specified resolution [default: off] -H, --hidden include hidden (dot) files [default: off] -i, --includeimgp re-process _IMGP files. * RISKY: refer to docs -k, --keep skip (honors -c or --pr) images matching specified H or V or --res=100 [default: off] -m, --mute operate silently [default: informative] -M res, --minres res min resolution in HxV or percentage of --res to resize -n, --enlarge enlarge smaller images [default: off] -N, --nearest use nearest neighbour interpolation for PNG [default: antialias] -O, --optimize optimize the output images [default: off] -P, --progressive save JPEG images as progressive [default: off] -q N, --quality N quality factor (N=1-95, JPEG only) [default: 75] -r, --recurse process non-symbolic dirs recursively [default: off] -s byte, --size byte minimum size to process an image [default: 1024] -w, --overwrite overwrite source images [default: off] -d, --debug enable debug logs [default: off] Version 2.9 Copyright © 2016-2023 Arun Prakash Jana License: GPLv3 Webpage: https://github.com/jarun/imgp
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crypto-rl
Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent
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InfluxDB
InfluxDB high-performance time series database. Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.
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lithops
A multi-cloud framework for big data analytics and embarrassingly parallel jobs, that provides an universal API for building parallel applications in the cloud ☁️🚀
Lithops is a great library for abstracting over different cloud vendors so you can interact with a uniform API.
https://github.com/lithops-cloud/lithops
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ruck
🧬 Modularised Evolutionary Algorithms For Python with Optional JIT and Multiprocessing (Ray) support. Inspired by PyTorch Lightning
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regta
📅 Production-ready scheduler with async, multithreading and multiprocessing support for Python
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teller_of_tales
Create narrated video story from book chapter using NLP, OpenAI and StableDiffusion.
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python Multiprocessing discussion
Python Multiprocessing related posts
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crypto-rl: Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders)
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Mpire: A Python package for easier and faster multiprocessing
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I made autothread: the easiest way to add parallelization to your code
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crypto-rl: Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders)
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crypto-rl: Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders)
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crypto-rl: Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders)
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crypto-rl: Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders)
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A note from our sponsor - InfluxDB
influxdata.com | 21 Apr 2025
Index
What are some of the best open-source Multiprocessing projects in Python? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | Joblib | 4,041 |
| 2 | aiomultiprocess | 1,868 |
| 3 | PSpider | 1,833 |
| 4 | Plutus | 1,232 |
| 5 | pyper | 1,187 |
| 6 | imgp | 1,070 |
| 7 | crypto-rl | 887 |
| 8 | pytorch-A3C | 633 |
| 9 | vermin | 465 |
| 10 | lithops | 330 |
| 11 | tractor | 281 |
| 12 | DictDataBase | 237 |
| 13 | think-async | 233 |
| 14 | multitasking | 206 |
| 15 | LiSA | 153 |
| 16 | lox | 122 |
| 17 | ruck | 53 |
| 18 | google_drive_ocr | 38 |
| 19 | autothread | 35 |
| 20 | NotEnoughAV1Encodes-Qt | 30 |
| 21 | regta | 22 |
| 22 | geventmp | 19 |
| 23 | teller_of_tales | 13 |
Sponsored
Save 47% on cloud hosting with autoscaling that just works
Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
judoscale.com