tictacreact2
fastapi
tictacreact2 | fastapi | |
---|---|---|
6 | 467 | |
17 | 71,023 | |
- | - | |
2.2 | 9.8 | |
10 months ago | 4 days ago | |
Python | Python | |
- | 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.
tictacreact2
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Reviving PyMiniRacer: A Python <> JavaScript Bridge
I've made React applications using Python via Transcrypt, but wrap component functions in a Python decorator that make direct calls to React.createElement() instead of using JSX (example: https://github.com/JennaSys/tictacreact2). It's possible to use JSX with this approach as well, but IMO it starts to get messy and defeats the purpose of using JSX in the first place.
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React JSX vs react with HMTL
If you are curious what the code looks like, this is the official Intro to React tutorial done in Python with function components.
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Reacton - A pure Python port of React for ipywidgets
I actually use Python to create React applications via Transcrypt and use functional components in that process. IMO it's quite a bit cleaner than using class components. It's more of a functional programming paradigm than OOP, but didn't take long to get used to. You do end up using more closures and lambdas than you would with procedural and OOP. This example based on the official React tutorial gives you an idea of what it looks like in Python.
- Show HN: Pynecone – web apps in pure Python
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Python and the Browser - Revisited
Listing 1: index.html
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New Python Library for Reactive UI
As an exercise, I did the official React tutorial using Python, and also converted it to use hooks instead of classes: https://github.com/JennaSys/tictacreact2
fastapi
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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.
- 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:
What are some alternatives?
reflex - 🕸️ Web apps in pure Python 🐍
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
pyedifice - Declarative GUI framework for Python and Qt
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
reacton - A pure Python port of React for ipywidgets
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
flet - Flet enables developers to easily build realtime web, mobile and desktop apps in Python. No frontend experience required.
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
tictacreact - React tutorial app using Python with Transcrypt
Flask - The Python micro framework for building web applications.
wasp - The fastest way to develop full-stack web apps with React & Node.js.
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.