strawberry
fastapi
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strawberry | fastapi | |
---|---|---|
33 | 465 | |
3,755 | 70,779 | |
2.0% | - | |
9.4 | 9.8 | |
5 days ago | 5 days ago | |
Python | Python | |
MIT License | 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.
strawberry
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My PHP Problems
have a look to http://strawberry.rocks for Python.
I've still to find a better code first implementation too
- Strawberry: A Python Library for GraphQL
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A question
Strawberry GraphQL with the Apollo library in React.
- Ask HN: Who is hiring? (July 2023)
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Appwrite OSS Fund Sponsors Strawberry
Strawberry is a modern GraphQL library for Python, that leverages Python’s type hint for a concise and intuitive API design. The library makes it easy to build GraphQL API and provides a built-in debug server for testing and debugging, support for Django, FastAPI and other frameworks.
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GitHub Accelerator: our first cohort and what's next
- https://github.com/strawberry-graphql/strawberry: A GraphQL library for Python that leverages type annotations
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These 20 startups are in 1st ever batch of GitHub OS Accelerator
Strawberry : Python GraphQL library leveraging type annotations
- Startups are in first batch of GitHub OS Accelerator
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What is the best option for writing GraphQL APIs using Django in 2023?
Currently happily using strawberry-graphql for a small project.
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Python package for large scale project.
Hi there, I'm one of the maintainer of Strawberry GraphQL (https://strawberry.rocks/) so I'm definitely biased towards it :)
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?
Graphene - GraphQL framework for Python
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
ariadne - Python library for implementing GraphQL servers using schema-first approach.
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
ariadne - A fancy diagnostics & error reporting crate
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
ariadne-extended - niceties when working with ariadne and Django
django-ninja - đź’¨ Fast, Async-ready, Openapi, type hints based framework for building APIs
starsessions - Advanced sessions for Starlette and FastAPI frameworks
Flask - The Python micro framework for building web applications.
uvicorn - An ASGI web server, for Python. 🦄
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.