dash VS bokeh

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.

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.

Take a look at streamlit and dash. Matplotlib widgets might also be of interest.

Dash

Bokeh - Interactive Web Plotting for Python.

Github: https://github.com/bokeh/bokeh

It sounds like you want BokehJS. It was one of the alternatives I was recommended while I was exploring, but for various reasons my particular use case is not so easy to integrate (plus my backend was already in Rust).

https://github.com/bokeh/bokeh

I did do a basic test, and the raw rects-on-screen performance is roughly comparable to my final solution.

I just came across this: https://bokeh.org/

Take a look at Bokeh. https://bokeh.org/

If so, one approach may be to abandon matplotlib for something like bokeh. Bokeh allows you to add many of the classical GUI elements (slider bars, radio buttons, etc). Depending on your needs, it can either make HTML files with your plots or with a little more work you can set it up as a server.

One particular interesting case is Dash by Plotly. While I myself have previously used Bokeh, I quickly made the transition to Dash since I felt it was more ready for usage as a deployed application. Additionally, having access to Plotly as a charting library is a big plus because it is such a successful open-source project with a strong community and a fantastic library.

Check out Bokeh https://bokeh.org/