awesome-python
Flask
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awesome-python | Flask | |
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85 | 135 | |
204,784 | 66,287 | |
- | 0.7% | |
7.1 | 8.7 | |
7 days ago | 9 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | 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.
awesome-python
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How I do technology watch
Python: https://github.com/vinta/awesome-python
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Top 10 GitHub Repositories Every Developer Should Bookmark in 2024
6) Awesome Python: Embrace the power of Python with this extensive collection of awesome libraries, frameworks, resources, and software. Whether you're a seasoned Pythonista or just starting your journey, this repository is your ultimate guide to maximizing the potential of this versatile language. (https://github.com/vinta/awesome-python)
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Good coding groups for black women?
- https://github.com/vinta/awesome-python
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Top GitHub Resources to Level Up Your Python game
🎇 Repository Link: Awesome Python
- GitHub - vinta/awesome-python: A curated list of awesome Python frameworks, libraries, software and resources
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10 Github repositories to achieve Python mastery
Explore here.
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Alternatives?
I know of curated lists like https://github.com/vinta/awesome-python but they are nowhere close to alternativeto.net in terms of information (relations) and community involvement.
- Help me out.
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Ask HN: Best place/resource to learn metaprogramming in Python
https://github.com/vinta/awesome-python
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Which MATLAB course to take for undecided
There are a lot of python packages for engineering and scientific applications (as well as other applications in general, and, thanks to the inherently collaborative nature of free software, they are only growing in quantity and quality. Many MATLAB toolboxes already have Python equivalents.
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?
Qtile-Config - This is my configuration of Qtile, a window manager written in python.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
VeRyPy - A python library with implementations of 15 classical heuristics for the capacitated vehicle routing problem.
Django - The Web framework for perfectionists with deadlines.
Pyadomd - A pythonic approach to query SSAS data models.
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
quart - An async Python micro framework for building web applications.
DearPyGui - Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies
starlette - The little ASGI framework that shines. 🌟
Box - Python dictionaries with advanced dot notation access
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.