django-storages
celery
django-storages | celery | |
---|---|---|
11 | 43 | |
2,640 | 23,550 | |
- | 1.1% | |
8.2 | 9.5 | |
3 days ago | 1 day ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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django-storages
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Images on Database Question
I recommend using https://github.com/jschneier/django-storages for handling this
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Use Celery with any Django Storage as a Result Backend
On the other side, the Django itself, together with a django-storages package, provides a wide range of file-like storage backends also using local, network, and cloud storage implementations.
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How to monkey-patch this simple script.py ?
the images are uploading correcty to dropbox but still have this stupid error.. same problem as here https://github.com/jschneier/django-storages/issues/1109
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Store static files on S3 but staticfiles.json manifest locally
I have a Django application running on Heroku. To store and serve my static files, I'm using django-storages with my S3 bucket, as well as the standard Django ManifestFilesMixin. I'm also using django-pipeline.
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Django with backblaze
And I hace tried https://github.com/pyutil/django-b2 https://github.com/royendgel/django-backblazeb2-storage https://github.com/jschneier/django-storages but aside from following their readme the manage.py run keeps asking me for more info and I'm really lost on what do I have to add
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Useful Django 3rd party packages Part 2
Doc: https://django-storages.readthedocs.io/en/latest/ Source: https://github.com/jschneier/django-storages
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Fixing Django anti-patterns in Sentry
Django documentation suggests not hard-coding static URLs, and instead using the {% static template tag. {% static ... returns the path the browser can use to request the file. At it's simplest, that would return a path that looks up the file on your local file system. That's fine for your local dev environment but in prod we will likely use third-party libraries such as whitenoise or django-storages to improve performance of the production web server.
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Using Docker on Lambda for Postgres to S3 Backups
By far the most annoying part of this whole thing was finding some GitHub issue comment that mentioned that Lambdas automatically set the AWS_SESSION_TOKEN and AWS_SECURITY_TOKEN environment variables, and it turns out it was causing a hard-to-track-down error in the backup script's invocation of the aws client along the lines of:
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What Django best practices is Django breaking?
If you’re unfamiliar: {% static ... returns the path the browser can use to request the file. At it's simplest, that would return a path that looks up the file on your local file system. That's fine for local dev but in prod we will likely use third-party libraries such as whitenoise or django-storages to improve performance of the production web server.
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1000s of Static Files Being Sent to S3
I would then suggest to use django-storages to handle uploaded files to S3 if you are not doing it already.
celery
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Streaming responses to websockets with multiple LLMs, am I going about this wrong?
So this might be my understanding, but stuff like celery is more like an orchestrator that chunks up workloads (think Hadoop with multiple nodes).
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Examples of using task scheduler with Go?
In the Django world, you'd probably rely on Celery to do this for you. You're probably looking for something similar that works with Go. https://github.com/celery/celery
- SynchronousOnlyOperation from celery task using gevent execution pool on django orm
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FastAPI + Celery problem: Celery task is still getting exectued even though I'm raising an exception on task_prerun
I've been doing some research and there doesn't seem to be much information on this issue, aditionally there's this but without a fix yet or any workaround: https://github.com/celery/celery/issues/7792
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Taskiq: async celery alternative
RabbitMQ Classic mirror queues are very fragile to network partitioning. They are deprecated in favor of Quorum queues, but Celery doesn't support them yet : https://github.com/celery/celery/issues/6067
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Use Celery with any Django Storage as a Result Backend
The Celery package provides some number of (undocumented!) result backends to store task results in different local, network, and cloud storages. The django-celery-result package adds options to use Django-specific ORM-based result storage, as well as Django-specific cache subsystem.
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Django Styleguide
I spent 3 years building a high scale crawler on top of Celery.
I can't recommend it. We found many bugs in the more advanced features of Celery (like Canvas) we also ran into some really weird issues like tasks getting duplicated for no reason [1].
The most concerning problem is that the project was abandoned. The original creator is not working on it anymore and all issues that we raised were ignored. We had to fork the project and apply our own fixes to it. This was 4 years ago so maybe things improved since them.
Celery is also extremely complex.
I would recommend https://dramatiq.io/ instead.
[1]: https://github.com/celery/celery/issues/4426
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Processing input and letting user download the result
You can use celery to process the file for extraction, saving and creating rar/zip.
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RQ-Scheduler for tasks in far future?
Celery not usefull for long term future tasks (far future) · Issue #4522 · celery/celery (github.com)
What are some alternatives?
django-compressor - Compresses linked and inline javascript or CSS into a single cached file.
dramatiq - A fast and reliable background task processing library for Python 3.
Flask-Assets - Flask webassets integration.
Apache Kafka - Mirror of Apache Kafka
django-pipeline - Pipeline is an asset packaging library for Django.
huey - a little task queue for python
fanstatic
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
webassets - Asset management for Python web development.
rq - Simple job queues for Python
jinja-assets-compressor - A Jinja extension (compatible with Flask and other frameworks) to compile and/or compress your assets.
kombu - Messaging library for Python.