alive-progress VS panel

And here are some libraries that might pique your interest although they don't strictly answer your question: - tqdm for adding a progress bar on for loops (it comes with useful information like iteration per second and estimated time needed to finish) - alive_progress adds a progress bar like tqdm, but it works even with generators and while loops which I don't think tqdm does. -timebudget, with just a decorator as soon as a function is completed it prints the time taken to execute it - send2trash for sending files to the trash bin instead of permanently deleting them - keyboard for sending keyboard inputs or check if a key is pressed - mouse same as keyboard but with mouse buttons - textract for extracting text from many types of file with a single interface. It supports documents, powerpoint presentations, csv, excels, images, gifs, audio, and many more

I still have to write about all the 2.0 features, the largest release I'll ever do... 😅 => https://github.com/rsalmei/alive-progress/pull/51

panel – data exploration & web app framework for Python

https://panel.holoviz.org/ It's a web app framework for Python similar to what Dash does for plotly. It plays nicely with bokeh visuals and I think the front-end is built using bokeh css elements.

I'm following the Panel FastAPI example here: https://github.com/holoviz/panel/blob/main/examples/apps/fastApi/main.py

If you want to build Python dashboards, look at the solara (react-style lib, https://solara.dev/) and panel (https://panel.holoviz.org/).

panel

My suggestion is https://panel.holoviz.org/

Fully open sourced, makes it easy to make reactive apps with small changes, can even configured as a graphical REPL.

I am doing something like this in a [panel](https://panel.holoviz.org/) dashboard, which I am currently converting to nicegui. Maybe I can provide an example in some days.

Ill have to check it out and see how it compares to voilà and holoviz panel. What I like about Holoviz panel is you can create a data web app from code that resides in a notebook or create a completely standalone app from just plain py scripts, and it supports many different visualization backends. I have found it to be the more flexible and generalizable data web app framework among the others I have come across (like Voilà, Dash, Plotly, and Streamlit).

Like the previous three alternatives, Panel is an open-source Python library for creating interactive dashboard web apps. Panel is extremely flexible, allowing you to use any plotting library you like. Like Gradio but unlike Streamlit, you can use Panel in Jupyter notebooks. Panel dashboards can also be deployed as standalone web apps, but like Plotly Dash, you'll need to set up a server to deploy it yourself.