fastapi-crudrouter
fastapi
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fastapi-crudrouter | fastapi | |
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4 | 465 | |
1,304 | 70,779 | |
- | - | |
0.0 | 9.8 | |
6 months ago | 5 days ago | |
Python | Python | |
MIT License | MIT License |
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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.
fastapi-crudrouter
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why when I search for Python jobs I find alot! but when I search for Django (the most used Python framework ) I get few compared to spring or nodejs ?
FastAPI does have an equivalent. Something like this? https://github.com/awtkns/fastapi-crudrouter
- FastAPI CRUD Router
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FUNCTOOLS CHANGED MY LIFE
I can't show any pics cuz of uk NDA and all that. I can tell you the gist of it though. FastAPI is already pretty good at the abstraction part. Our middleware had a lot of rerouting and it was basically just a bunch of redundant functions. I just used this cool ass package https://fastapi-crudrouter.awtkns.com/ and used the partial function from functools to generate endpoints for every scenario/db tables.
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FastAPI framework, high perf, easy to learn, fast to code, ready for production
Thanks, that's a really helpful example.
Where I think this could be taken to the next level of reusability is in modularising the front-end into API-specific components. For example, the login behaviour could depend on FastAPI-Users, with a sibling frontend library containing components that implement the same login flow. Adding user behaviour is then a matter of using the same third-party library on the front and back end.
This approach could be extended to other components such as an admin panel (perhaps using https://github.com/awtkns/fastapi-crudrouter), or a blogging component.
fastapi
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FastAPI Got Me an OpenAPI Spec Really... Fast
That’s when I found FastAPI.
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How to Deploy a Fast API Application to a Kubernetes Cluster using Podman and Minikube
FastAPI & Uvicorn
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Analysing FastAPI Middleware Performance
Discussion at FastAPI GitHub: https://github.com/tiangolo/fastapi/issues/2696
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LangChain, Python, and Heroku
An API application framework (such as FastAPI)
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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
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AI-Powered Image Search with CLIP, pgvector, and Fast API
Fast API.
- Ask HN: What is your go-to stack for the web?
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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:
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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.
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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?
starlite - Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant APIs [Moved to: https://github.com/litestar-org/litestar]
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
Flask-AppBuilder - Simple and rapid application development framework, built on top of Flask. includes detailed security, auto CRUD generation for your models, google charts and much more. Demo (login with guest/welcome) - http://flaskappbuilder.pythonanywhere.com/
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
fastapi-users - Ready-to-use and customizable users management for FastAPI
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
mangum - AWS Lambda support for ASGI applications
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
Dask - Parallel computing with task scheduling
Flask - The Python micro framework for building web applications.
openapi-generator - OpenAPI Generator allows generation of API client libraries (SDK generation), server stubs, documentation and configuration automatically given an OpenAPI Spec (v2, v3)
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.