rq-scheduler
Flask-RQ2
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rq-scheduler | Flask-RQ2 | |
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4 | 3 | |
1,380 | 222 | |
0.9% | 1.4% | |
2.2 | 0.0 | |
17 days ago | 7 days ago | |
Python | Python | |
MIT License | MIT License |
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rq-scheduler
- Keep the Monolith, but Split the Workloads
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RQ-Scheduler for tasks in far future?
RQ-Scheduler is another simpler alternative (rq/rq-scheduler: A lightweight library that adds job scheduling capabilities to RQ (Redis Queue) (github.com)) that appears to be good for such purposes. It's not immediately clear if it would suffer from the same issues, but it seems not (Redis manages issues with data loss well, a separate queue is used for the scheduled tasks, etc.). Is anyone aware of any drawbacks to using RQ-Scheduler for something like this?
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Some advice: will my setup be production ready?
Some thoughts: - Storing API keys in Redis with AOF and RDB persistence turned on is going to be way faster than storing those keys in Mongo. - Did you mean RQ (redis-queue)/django-rq? If so, it works well as long as you don't need a scheduler for cron-like tasks, which it doesn't include. You can add rq-scheduler for that though: https://github.com/rq/rq-scheduler - Make sure your redis instance has a password -- redis 6 supports ACLs as well - The problem with slow requests is that they tie up app server processes and usually also database connections. That may be fine with a small number of consumers, but if you point your web site at this API, you may run into problems. Consider that if an app server serving web site traffic is waiting for a slow request to your API, then both app servers are affected -- you're now holding resources on the web site and the API, effectively. - HTTP clients often use a default timeout value for requests, and it's a best practice to use such a timeout -- so you'll need to coach your partners consuming this API not to use timeouts for your API.
Flask-RQ2
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Wondering if I should use Celery vs threads for what I want to do
From experience i would not use threads for this or any background jobs. I would use Celery or Flask-RQ2 to be your workers, you will also probably end up using them to run other tasks as you encounter the need for other jobs. They both use Redis as a broker and job store and you can use Redis for other things like caching and so many other useful features. I kind of like RQ2 more then Celery because its a little simpler but Celery has a lot more to offer, more features. RQ2 has rq-dashboard for monitoring jobs and Celery has Flower.
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Tutorials on how to build a flask extension?
However, you might need to access the app’s context like how you’d do so in the Flask-RQ2 extension by using ScriptInfo from flask.cli:
What are some alternatives?
fastapi-cloud-tasks - GCP's Cloud Tasks + Cloud Scheduler + FastAPI = Partial replacement for celery.
rq - Simple job queues for Python
django-rq - A simple app that provides django integration for RQ (Redis Queue)
celery - Distributed Task Queue (development branch)
rq-dashboard - Flask-based web front-end for monitoring RQ queues
flask-apscheduler - Adds APScheduler support to Flask
django-rq - A simple app that provides django integration for RQ (Redis Queue) [Moved to: https://github.com/rq/django-rq]
supervisor - Supervisor process control system for Unix (supervisord)
NiceHash-Mining-Scheduler - Schedule the start and stop of your NiceHash miners using this script.
arq - Fast job queuing and RPC in python with asyncio and redis.
django-todo - A multi-user, multi-group todo/ticketing system for Django projects. Includes CSV import and integrated mail tracking.