Flask
quart
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Flask | quart | |
---|---|---|
135 | 5 | |
66,287 | 2,606 | |
0.7% | 3.5% | |
8.7 | 8.1 | |
4 days ago | 17 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" 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.
Flask
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Ask HN: High quality Python scripts or small libraries to learn from
I'd suggest Flask or some of the smaller projects in the Pallets ecosystem:
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Rapid Prototyping with Flask, Bootstrap and Secutio
#!/usr/bin/python # # https://flask.palletsprojects.com/en/3.0.x/installation/ # from flask import Flask, jsonify, request contacts = [ { "id": "1", "firstname": "Lorem", "lastname": "Ipsum", "email": "[email protected]", }, { "id": "2", "firstname": "Mauris", "lastname": "Quis", "email": "[email protected]", }, { "id": "3", "firstname": "Donec Purus", "lastname": "Purus", "email": "[email protected]", } ] app = Flask(__name__, static_url_path='', static_folder='public',) @app.route("/contact//save", methods=["PUT"]) def save_contact(id): data = request.json contacts[id - 1] = data return jsonify(contacts[id - 1]) @app.route("/contact/", methods=["GET"]) @app.route("/contact//edit", methods=["GET"]) def get_contact(id): return jsonify(contacts[id - 1]) @app.route('/') def root(): return app.send_static_file('index.html') if __name__ == '__main__': app.run(debug=True)
- Microdot "The impossibly small web framework for Python and MicroPython"
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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10 Github repositories to achieve Python mastery
Explore here.
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Ask HN: What would you use to build a mostly CRUD back end today?
I may use Flask-Admin initially to offload the "CRUD" operations to have an initial prototype fast but then drop it ASAP because I don't want to write a "flask-admin application" to fight against later on. If the application is mainly "CRUD", then Flask-Admin is suitable.
Now...
Would you do a breakdown/list of all the jobs you've done by sector/vertical and by function/role and by application functionality?
- [0]: https://flask.palletsprojects.com
- [1]: https://flask-admin.readthedocs.io/en/latest
- [2]: https://flask.palletsprojects.com/en/2.3.x/patterns/celery
- [3]: https://sentry.io
- [4]: https://posthog.com
- [5]: https://www.docker.com
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Implementing continuous delivery pipelines with GitHub Actions
In the lab to follow, we will be setting up an end-to-end DevOps workflow for a Flask microservice with GitHub Actions, using a self-managed custom runner for maximal control over the pipeline execution environment and automating deployments to a local Kubernetes cluster. Furthermore, we will construct separate pipelines for our "development" and "production" environments to further elaborate on the concepts of continuous deployment and delivery.
- How do you iterate on a library built locally?
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Flask Application Load Balancing using Docker Compose and Nginx
Flask Micro web Framework: You will use Flask to build a Flask web application.
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Open Source Flask-based web applications
In an earlier post I mentioned a bunch of Open Source web applications. Let's now focus on the ones written in Python using Flask the light-weight web framework.
quart
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Ask HN: What have you created that deserves a second chance on HN?
I've three things :),
1. Quart, https://quart.palletsprojects.com, an ASGI (async/await) re-implementation of the Python web MicroFramework Flask. It is now maintained alongside, by the same people, as Flask.
2. Hypercorn, https://hypercorn.readthedocs.io, an ASGI/WSGI server that supports HTTP/1, HTTP/2, and HTTP/3.
3. My book "A Blueprint for Production-Ready Web Applications", which uses both of the above and shows a beginner how to build a full stack app (React frontend) running on AWS. See https://pgjones.dev/tozo/ for details, code, and link to the example app.
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How does a single running instance of a Flask application handle multiple requests at once? Is it all async or multithreaded? Or handled by the webserver (NGINX, gunicorn, etc)?
If you want async flask, you should use quart for now. The roadmap is to fully incorporate quart into flask at some point, but it’s unclear when that’s going to happen.
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This Week In Python
quart – An async Python micro framework for building web applications
- Quart: An async Python micro framework for building web applications
- Quart, the async implementation of Flask has joined Pallets
What are some alternatives?
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
Django - The Web framework for perfectionists with deadlines.
starlette - The little ASGI framework that shines. 🌟
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
flask-pydantic - flask extension for integration with the awesome pydantic package
quart - An async Python micro framework for building web applications.
flask-smorest - DB agnostic framework to build auto-documented REST APIs with Flask and marshmallow
django-awl - Miscellaneous django tools
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.
asgiref - ASGI specification and utilities