panel VS dash

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.

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.

You could use something like Streamlit or Dash. In any case you will be accessing your app through the browser.

Useful list. Dash & bokeh as two more in the space

https://github.com/plotly/dash

I also heard of Dash which serves the same purpose I guess, but I think it has more to offer.

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.)

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.

looks like you can get it manually (albeit with a loss of interactivity) https://github.com/plotly/dash/issues/145

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.