microblog
fastapi
Our great sponsors
microblog | fastapi | |
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220 | 465 | |
4,421 | 70,779 | |
- | - | |
2.3 | 9.8 | |
about 1 month ago | 3 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.
microblog
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Simple Flask Integration for an Elastic Semantic Search App
In this blog, we're going to address the "on any website" part of a Search Solution. Or at least - propose a starting point for it. There are many great tutorials out there for a deep dive on Flask - one of the best from my colleague Miguel.
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Ask HN: Washed out PHP Dev – What to do next?
- https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial...
- The Flask Mega-Tutorial, Part I: Hello, World
- Deploying python code as a webapp
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Hosting small script
If you'd like to deploy a web app, Flask is your best friend. It's very user friendly and there's a lot of great tutorials online. The only thing you'd need other than Python knowledge is some basic understanding of HTML/CSS and Jinja notation for variables, both of which are pretty intuitive to learn. Good luck!
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Ask HN: How to get back to programming Python?
I can't speak highly enough of Miguel Grinberg's work with Python/Flask (https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial...) and the community he's created around it, for both beginners and advanced folks.
Racing through his mega tutorial was a great refresher for me on the fundamentals, and it's easy to plug in computer vision & related libraries/extensions/packages.
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Structuring scalable flask app
Use miguel grinberg’s tutorial https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-i-hello-world
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Flask blueprints and cyclic dependencies with routes.py files
I got a recommendation (from a few places) to use Miguel Grinberg's microblog series to help me get up to speed on some flask things. I'm on ch 15 with blueprints, and am running into pylint cyclic import errors, both on my app and in the actual project (https://github.com/miguelgrinberg/microblog/tree/v0.15?search=1)
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How to Visualize a Social Network in Python with a Graph Database: Flask + Docker + D3.js
In the project root directory create a folder called static with one subfolder called js and another called css. The js folder will contain all of the needed local JavaScript files while the css folder will contain all the CSS stylesheets. In the js folder create a file called index.js and in the css folder one called style.css. Just leave them empty for now. If you want to find out more about web development with Flask I suggest you try out this tutorial. Your current project structure should like this:
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What Is The Best Tutorial To Pick Up Flask?
https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-i-hello-world is not perfect, but a great start.
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?
flask-app-tutorial - Project for how to create a flask web application.
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
build-a-saas-app-with-flask - Learn how to build a production ready web app with Flask and Docker.
HS-Sanic - Async Python 3.6+ web server/framework | Build fast. Run fast. [Moved to: https://github.com/sanic-org/sanic]
CS50x-2021 - 🎓 HarvardX: CS50 Introduction to Computer Science (CS50x)
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
flasky - Companion code to my O'Reilly book "Flask Web Development", second edition.
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
kivy - Open source UI framework written in Python, running on Windows, Linux, macOS, Android and iOS
Flask - The Python micro framework for building web applications.
swagger-ui - Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.