s3ite | rq | |
---|---|---|
1 | 27 | |
13 | 9,589 | |
- | 0.7% | |
5.4 | 8.5 | |
3 months ago | 9 days ago | |
Rust | Python | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
s3ite
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Redis Re-Implemented with SQLite
In other abuses of SQLite, I wrote a tool [0] that exposes blobs in SQLite via an Amazon S3 API. It doesn't do expiry (but that would be easy enough to add if S3 does it).
We were using it to manage a millions of images for machine learning as many tools support S3 and the ability to add custom metadata to objects is useful (harder with files). It is one SQLite database per bucket but at the bucket level it is transactional.
0: https://github.com/seddonm1/s3ite
rq
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Redis Re-Implemented with SQLite
That's pretty cool. Reckon it would work with existing code that calls Redis over the wire for RQ?
https://python-rq.org
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The Many Problems with Celery
https://github.com/rq/rq is to the rescue.
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Keep the Monolith, but Split the Workloads
We use RQ[0], it has Redis as a dependency. It’s pretty straightforward and we’re very happy with it. If you are using Django you may want to look at Django RQ[1] as well. RQ has built in scheduling capabilities these days, but historically it did not so we used (and still use) RQ Scheduler[2] which I think still has some advantages over the built in stuff.
[0] https://python-rq.org/
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SQL Maxis: Why We Ditched RabbitMQ and Replaced It with a Postgres Queue
Also had a similar experience using RabbitMQ with Django+Celery. Extremely complicated and workers/queues would just stop for no reason.
Moved to Python-RQ [1] + Redis and been rock solid for years now.
[1] https://python-rq.org/
- Ask HN: Redis Queue Hacks and Questions
- What libraries do you use the most alongside django?
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Recommendations other than celery to send an API processing in background, which would only take 5 mins to process and API usage would be once a month or so.
Yep, rq is simple and good: https://python-rq.org/ It also has a Django wrapper: https://github.com/rq/django-rq
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GPU instance crashes when two python processes use the same pt file
We have a GPU (G5) instance that uses Python RQ (https://python-rq.org/).
- Dynamically update periodic tasks in Celery and Django
- Celery + RabbitMQ alternatives
What are some alternatives?
sabledb - Ultra fast, persistent database supporting Redis API
celery - Distributed Task Queue (development branch)
huey - a little task queue for python
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
mrq - Mr. Queue - A distributed worker task queue in Python using Redis & gevent
procrastinate - PostgreSQL-based Task Queue for Python
Apache Kafka - Mirror of Apache Kafka
KQ - Kafka-based Job Queue for Python
Flask-RQ2 - A Flask extension for RQ.
kombu - Messaging library for Python.
Streamz - Real-time stream processing for python
budibase - Budibase is an open-source low code platform that helps you build internal tools in minutes 🚀