https://github.com/fabricesalvaire/sidita
A simple distributed task queue for Python 3 asyncio
https://github.com/fabricesalvaire/sidita
python python-library python3 queue-tasks queue-workers queued-jobs task-manager task-runner task-scheduler
Last synced: 4 months ago
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A simple distributed task queue for Python 3 asyncio
- Host: GitHub
- URL: https://github.com/fabricesalvaire/sidita
- Owner: FabriceSalvaire
- License: gpl-3.0
- Created: 2018-04-28T15:03:48.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-05-03T23:14:42.000Z (over 7 years ago)
- Last Synced: 2025-06-03T21:24:35.035Z (5 months ago)
- Topics: python, python-library, python3, queue-tasks, queue-workers, queued-jobs, task-manager, task-runner, task-scheduler
- Language: Python
- Homepage: https://fabricesalvaire.github.io/sidita
- Size: 2.46 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.html
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE.txt
- Code of conduct: .github/CODE_OF_CONDUCT.md
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README
sidita
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sidita
sidita license
sidita python version
- Quick Link to Production Branch
- Quick Link to Devel Branch
Overview
What is sidita ?
Sidita is a Python module which implements a distributed task queue featuring an intermediate
solution between the multiprocessing module and a task scheduler like Celery.
The Sidita use case corresponds to the case where you need to run CPU bound tasks in parallel and
you require an immunity to crashes, memory leaks and overruns. Theses requirements are met by a
monitored subprocess implementation.
What are the main features ?
- Must be a simple solution to circumvent to the GIL limitation : i.e. distribute and run tasks in parallel on local CPU cores
- Must be a lightweight solution to Celery : no broker
- Should be portable on main OS like Unix and Windows
- Scheduler is implemented using an asyncio event loop and asyncio queue
- Scheduler queue can be limited on size so as to prevent a memory overshoot at startup
- Workers are spawned using asyncio subprocess and communicate through a pipe (stdin, stdout)
- Pass any pickable object as request and response
- Scheduler monitors workers and restart them when they was killed or they exceeded a memory or timeout threshold
- Provide basic metrics on workers
Technical details in brief:
- scheduler run a producer and N consumers coroutines in an asyncio event loop
- the producer coroutine awaits on
queue.put(task) ( if a size limit is set )
- each consumer coroutine wraps a worker subprocess and await data on the stdout pipe
Technical details in brief:
- scheduler run a producer and N consumers coroutines in an asyncio event loop
- the producer coroutine awaits on
queue.put(task) ( if a size limit is set )
- each consumer coroutine wraps a worker subprocess and await data on the stdout pipe
News
V0 2018-05-01
Started project