Joblib
think-async
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Joblib | think-async | |
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2 | 4 | |
3,656 | 222 | |
2.0% | - | |
7.0 | 7.8 | |
7 days ago | 2 months ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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Joblib
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Celery & Scikit-Learn: Using n_jobs under a Celery task throws joblib/Loky warning
Here's a thread from a few years ago btw on using billiard as a backend for joblib. https://github.com/joblib/joblib/issues/311
think-async
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Think Async: Resources for Exploring Different Concurrency Paradigms in Python
Lately, at my workplace, I've been doing a lot of asynchronous I/O programming in Python. In my case, ironically, I picked up Golang faster than Python's async paradigm despite Python being my primary language. Coroutine chauffeured asynchronous programming demanded a substantial shift in the way I used to compose solutions in synchronous Python.
However, after successfully writing two services using asyncio, SQS, DynamoDB, and aiobotocore—I'm convinced that this is actually worth it. Here're a few resources that I've found helpful along the way. Pull requests are very much welcome.
https://github.com/rednafi/think-async
- Think Async in Python
What are some alternatives?
schedule - Python job scheduling for humans.
aiomultiprocess - Take a modern Python codebase to the next level of performance.
celery - Distributed Task Queue (development branch)
arq - Fast job queuing and RPC in python with asyncio and redis.
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
vermin - Concurrently detect the minimum Python versions needed to run code
doit - task management & automation tool
gevent - Coroutine-based concurrency library for Python
APScheduler - Task scheduling library for Python
mnqueues - Monitored Multiprocessing Queues
django-schedule - A calendaring app for Django. It is now stable, Please feel free to use it now. Active development has been taken over by bartekgorny.
regta - 📅 Production-ready scheduler with async, multithreading and multiprocessing support for Python