connexion
fastapi
connexion | fastapi | |
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23 | 469 | |
4,420 | 71,223 | |
0.3% | - | |
8.2 | 9.8 | |
8 days ago | 2 days ago | |
Python | Python | |
Apache License 2.0 | 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.
connexion
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Write OpenAPI with TypeSpec
I like the idea, especially the TS-like syntax around enums and union types. I've always preferred the SDL for GraphQL vs writing OpenAPI for similar reasons.
I echo the sentiment others have brought up, which is the trade-offs of a code-driven schema vs schema-driven code.
At work we use Pydantic and FastAPI to generate the OpenAPI contract, but there's some cruft and care needed around exposing those underlying Pydantic models through the API documentation. It's been easy to create schemas that have compatibility problems when run through other code generators. I know there are projects such as connexction[1] which attempt to inverse this, but I don't have much experience with it. In the GraphQL space it seems that code-first approaches are becoming more favored, though there's a different level of complexity needed to create a "typesafe" GraphQL server (eg. model mismatches between root query resolvers and field resolvers).
[1] https://github.com/spec-first/connexion
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Connexion 3 released!
Connexion is a popular Python web framework (~ 5 million downloads per month) that makes spec-first and api-first development easy. You describe your API in an OpenAPI (or swagger) specification with as much detail as you want and Connexion will guarantee that it works as you specified.
- Connexion 3.0 Released
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Show HN: REST Alternative to GraphQL and tRPC
> While REST APIs don't generally provide the same level of control to clients as GraphQL, many times this could be seen as a benefit especially in scenarios where strict control over data access and operations is crucial.
Rest is more secure, cacheable, and more performant on the server side as field resolution doesn't need to happen like it does with GraphQL. It is not more performant on the client side, and this is a trade-off, but I favor rest applications over GraphQL ones as a DevOps engineer. They are much easier to administer infrastructure-wise, I can cache the requests, etc.
Data at our company suggests that several small queries actually do better performance-wise than one large one. We switched to GraphQL a year and a half ago or so, but this piece of data seems to suggest that we might have been better off just sticking with REST. My suggestion to that effect was not met with optimism either on the client or server side. Apparently there are server-side benefits as well, allowing for more modular development or something like that.
I have used OpenAPI using connexion[1]. It was hard to understand at first, but I really liked that the single source of truth was one schema. It also made it really easy to develop against the API because it came with a UI that showed the documentation for all the rest end points and even had test buttons.
1: https://connexion.readthedocs.io/en/latest/
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Ask HN: Why is there no specification for Command Line Interfaces?
What's the use case? I was thinking about this exact issue because my product ships several CLI tools, but I wasn't convinced it would be worth the effort.
An OpenAPI specification describes an HTTP interface, and I see it as useful because it makes it easier to write code in language-of-choice to generate HTTP requests (by generating client libraries from the OpenAPI spec).
For a CLI, the interface is the command-line. Usually people type these commands, or they end up in bash scripts, or sometimes they get called from programming language of choice by shelling out to the CLI. So I could see a use case for a CLI spec, which would make it easier to generate client libraries (which would shell out to the CLI)... but it seems a little niche.
Or maybe, as input to a documentation tool (like Swagger docs). I would imagine if you're using a CLI library like Python's Click, most of that data is already there. Click Parameters documentation: https://click.palletsprojects.com/en/8.1.x/parameters/
Or maybe, you could start from the spec and then generate code which enforces it. So any changes pass through the spec, which would make it easy to write code (server and client-side) / documentation / changelogs. Some projects like this: Guardrail (Scala) https://github.com/guardrail-dev/guardrail , and Connexion (Python) https://github.com/spec-first/connexion .
But without this ecosystem of tooling, documenting your CLI in a specification didn't really seem worth the effort. Of course, that's a bootstrapping problem.
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Flask is Great!
Connexion is a framework on top of Flask that automagically handles HTTP requests defined using OpenAPI/Swagger.
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What is the best practice for mapping JSON requests to objects and back to JSON?
I recommend you create a OpenAPI Specification and implement a python module that you expose via connexion or on the cli via click(for easy testing).
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Flask-Powered APIs: Fast, Reliable, and Used by the World's Top Companies
I'm here because Swagger-CodeGen created flask-Connexion boilerplate for python.
- Python REST APIs With Flask, Connexion, and SQLAlchemy – Part 1 – Real Python
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Does anybody know any good resources I could use to study ISP architecture?
Personally we just prov them using librouteros and flask-connexion/openapi.
fastapi
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Github Sponsor Sebastián Ramírez Python programmer
He is probably most well know for creating FastAPI that I taught to some of my clients and Typer that I've never used.
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Python: A SQLAlchemy Wrapper Component That Works With Both Flask and FastAPI Frameworks
It has been an interesting exercise developing this wrapper component. The fact that it seamlessly integrates with the FastAPI framework is just a bonus for me; I didn't plan for it since I hadn't learned FastAPI at the time. I hope you find this post useful. Thank you for reading, and stay safe as always.
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FastAPI Best Practices: A Condensed Guide with Examples
FastAPI is a modern, high-performance web framework for building APIs with Python, based on standard Python type hints.
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Building an Email Assistant Application with Burr
In this tutorial, I will demonstrate how to use Burr, an open source framework (disclosure: I helped create it), using simple OpenAI client calls to GPT4, and FastAPI to create a custom email assistant agent. We’ll describe the challenge one faces and then how you can solve for them. For the application frontend we provide a reference implementation but won’t dive into details for it.
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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.
What are some alternatives?
flask-restful - Simple framework for creating REST APIs
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
Flask RestPlus - Fully featured framework for fast, easy and documented API development with Flask
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
flasgger - Easy OpenAPI specs and Swagger UI for your Flask API
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
django-rest-framework - Web APIs for Django. 🎸
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
eve - REST API framework designed for human beings
Flask - The Python micro framework for building web applications.
falcon - The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale.
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.