flask-restful
Flask
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flask-restful | Flask | |
---|---|---|
5 | 135 | |
6,772 | 66,350 | |
0.4% | 0.8% | |
1.5 | 8.7 | |
3 days ago | 3 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" 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-restful
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Faster time-to-market with API-first
When it comes to Flask, in particular, there’re plenty of choices. And in fairness, not all frameworks are created equal. You’ve got flasgger, restx (successor of flask-restplus), flask-RESTful, and flask-smorest, to mention a few. How do you choose among those???
- How to implement flask restful api to a flask application?
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Custom error messages with flask vs flask_restful
This has talked about in a similar matter: https://github.com/flask-restful/flask-restful/issues/221. However I'm still adamant about just using flask for exception handling. Unless I missed something,I'm having a hard time figuring out how to accomplish this in hopes to get rid of the string concatenation that flask_restful applies to the error message.
- Need help with flask-restful, application factories and blueprints
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Outdated Flask extensions
Considering the extension you've mentioned explicitly, the author of it has provided an explanation as to why he is not longer putting in any work, you can read about it here.
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:
https://github.com/pallets/flask
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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.
What are some alternatives?
Flask RestPlus - Fully featured framework for fast, easy and documented API development with Flask
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
flask-restx - Fork of Flask-RESTPlus: Fully featured framework for fast, easy and documented API development with Flask
Django - The Web framework for perfectionists with deadlines.
connexion - Connexion is a modern Python web framework that makes spec-first and api-first development easy.
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
flask-restless - NO LONGER MAINTAINED - A Flask extension for creating simple ReSTful JSON APIs from SQLAlchemy models.
quart - An async Python micro framework for building web applications.
flasgger - Easy OpenAPI specs and Swagger UI for your Flask API
starlette - The little ASGI framework that shines. 🌟
eve - REST API framework designed for human beings
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.