rq
fastapi
Our great sponsors
rq | fastapi | |
---|---|---|
27 | 465 | |
9,503 | 70,779 | |
1.1% | - | |
8.3 | 9.8 | |
8 days ago | 4 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
rq
-
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
-
The Many Problems with Celery
https://github.com/rq/rq is to the rescue.
-
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/
-
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?
-
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
-
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
fastapi
-
FastAPI Got Me an OpenAPI Spec Really... Fast
That’s when I found FastAPI.
-
How to Deploy a Fast API Application to a Kubernetes Cluster using Podman and Minikube
FastAPI & Uvicorn
-
Analysing FastAPI Middleware Performance
Discussion at FastAPI GitHub: https://github.com/tiangolo/fastapi/issues/2696
-
LangChain, Python, and Heroku
An API application framework (such as FastAPI)
-
Litestar – powerful, flexible, and highly performant Python ASGI framework
It’s been my experience that async Python frameworks tend to turn IO bound problems into CPU bound problems with a high enough request rate, because due to their nature they act as unbounded queues.
This ends up made worse if you’re using sync routes.
If you’re constrained on a resource such as a database connection pool, your framework will continue to pull http requests off the wire that a sane client will cancel and retry due to timeouts because it takes too long to get a connection out of the pool. Since there isn’t a straightforward way to cancel the execution of a route handler in every Python http framework I’ve seen exhibit this problem, the problem quickly snowballs.
This is an issue with fastapi, too- https://github.com/tiangolo/fastapi/issues/5759
-
AI-Powered Image Search with CLIP, pgvector, and Fast API
Fast API.
- Ask HN: What is your go-to stack for the web?
-
Fun with Avatars: Crafting the core engine | Part. 1
We will create our API using FastAPI, a modern high-performance web framework for building fast APIs with Python. It is designed to be easy to use, efficient, and highly scalable. Some key features of FastAPI include:
-
Building Fast APIs with FastAPI: A Comprehensive Guide
FastAPI is a modern, fast, web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, fast to run, and secure. In this blog post, we’ll explore the key features of FastAPI and walk through the process of creating a simple API using this powerful framework.
-
Effortless API Documentation: Accelerating Development with FastAPI, Swagger, and ReDoc
FastAPI is a modern, fast web framework for building APIs with Python 3.7+ that automatically generates OpenAPI and JSON Schema documentation. While FastAPI simplifies API development, manually creating and updating API documentation can still be a time-consuming task. In this blog post, we’ll explore how to leverage FastAPI’s automatic documentation generation capabilities, specifically focusing on Swagger and ReDoc, and how to streamline the process of documenting your APIs.
What are some alternatives?
celery - Distributed Task Queue (development branch)
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
huey - a little task queue for python
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
mrq - Mr. Queue - A distributed worker task queue in Python using Redis & gevent
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
procrastinate - PostgreSQL-based Task Queue for Python
Flask - The Python micro framework for building web applications.
Apache Kafka - Mirror of Apache Kafka
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.