jupyter_server
dash
jupyter_server | dash | |
---|---|---|
1 | 56 | |
456 | 20,653 | |
3.7% | 1.4% | |
8.9 | 9.6 | |
2 days ago | 8 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.
jupyter_server
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Want to change shell of Jupyter lab terminal.
There is a setting in Jupyter-server for this ServerApp.terminado_settings see: https://jupyter-server.readthedocs.io/en/latest/users/configuration.html https://github.com/jupyter-server/jupyter_server/pull/949
dash
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dash VS solara - a user suggested alternative
2 projects | 13 Oct 2023
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[Python] NiceGUI: Lassen Sie jeden Browser das Frontend für Ihren Python-Code sein
Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally, we wanted to offer a gentle learning curve while still providing the ability to go all the way down to HTML, CSS, and JavaScript if needed.
- Visualizing parquet in s3 bucket for data analysis?
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Little guidance of a python newbie
You could use something like Streamlit or Dash. In any case you will be accessing your app through the browser.
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Launch HN: Pynecone (YC W23) – Web Apps in Pure Python
Useful list. Dash & bokeh as two more in the space
https://github.com/plotly/dash
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Python projects with best practices on Github?
I also heard of Dash which serves the same purpose I guess, but I think it has more to offer.
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4 Streamlit Alternatives for Building Python Data Apps
Plotly is a plotting library, and Dash is their open-source framework for building data apps with Python, R or Julia. (Dash also has an Enterprise version, but we'll focus on the open-source library here.)
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NiceGUI: Let any browser be the frontend for your Python code
Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally, we wanted to offer a gentle learning curve while still providing the ability to go all the way down to HTML, CSS, and JavaScript if needed.
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Sharing interactive Plotly graphs
looks like you can get it manually (albeit with a loss of interactivity) https://github.com/plotly/dash/issues/145
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Containerizing Shiny for Python and Shinylive Applications
Shiny is a framework that makes it easy to build interactive web applications. Shiny was introduced 10 years ago as an R package. In his 10th anniversary keynote speech, Joe Cheng announced Shiny for Python at the 2022 RStudio Conference. Python programmers can now try out Shiny to create interactive data-driven web applications. Shiny comes as an alternative to other frameworks, like Dash, or Streamlit.
What are some alternatives?
streamlit - Streamlit — A faster way to build and share data apps.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
panel - Panel: The powerful data exploration & web app framework for Python
uvicorn - An ASGI web server, for Python. 🦄
Flask - The Python micro framework for building web applications.
nicegui - Create web-based user interfaces with Python. The nice way.
PyWebIO - Write interactive web app in script way.
reflex - 🕸️ Web apps in pure Python 🐍
Jinja2 - A very fast and expressive template engine.
ipywidgets - Interactive Widgets for the Jupyter Notebook
datapane - Build and share data reports in 100% Python
ttkthemes - A group of themes for the ttk extenstions for Tkinter