ipywidgets
Flask
ipywidgets | Flask | |
---|---|---|
6 | 135 | |
3,057 | 66,417 | |
0.8% | 0.5% | |
7.5 | 8.7 | |
18 days ago | 4 days ago | |
TypeScript | 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.
ipywidgets
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ipywidgets alternatives - solara and ipyvuetify
3 projects | 13 Oct 2023
- [IPKernelApp] ERROR | No such comm target registered: jupyter.widget.control · Issue #3454 · jupyter-widgets/ipywidgets
- ipywidgets don't work on virtualenv · Issue #2257 · jupyter-widgets/ipywidgets
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INTERACTIVE RESULTS WITH JUPYTER NOTEBOOK
Ipywidgets also known as jupyter-widgets or simple widgets, are interactive HTML widgets for Jupyter notebooks and the IPython kernel. Notebooks come alive when interactive widgets are used. Users gain control of their data and can visualize changes in the data.
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IDOM - It's React, but in Python
IPyWidgets - Adds interactive widgets to Jupyter Notebooks
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?
dash - Data Apps & Dashboards for Python. No JavaScript Required.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
streamlit - Streamlit — A faster way to build and share data apps.
Django - The Web framework for perfectionists with deadlines.
reactpy - It's React, but in Python
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
sanic - Accelerate your web app development | Build fast. Run fast.
starlette - The little ASGI framework that shines. 🌟
ipympl - Matplotlib Jupyter Integration
quart - An async Python micro framework for building web applications.
Vue.js - This is the repo for Vue 2. For Vue 3, go to https://github.com/vuejs/core
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.