dropbox-sdk-python VS dash

The creation of the dropbox-sdk-python repo was almost certainly overseen by Guido van Rossum since he was working at Dropbox at the time. There is a note in the Smartsheet SDK repo that parts of it were developed by Dropbox as well.

Or do you or should I just use this 'dropbox-sdk-python' (https://github.com/dropbox/dropbox-sdk-python)?

I'm not drawing conclusions from this, but I did some poking around..

I ran `git clone` on the repos of both rsync[0] and the official Dropbox SDK for Python[1]. I then ran sloccount on both of them.

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rsync came in at a total of 51,410 physical source lines of code.

The Dropbox SDK came in at a total of 74,140 physical source lines of code.

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[0] https://git.samba.org/rsync.git

[1] https://github.com/dropbox/dropbox-sdk-python

In this example, we will demonstrate how we can integrate with a third-party storage provider like Dropbox to create backups of files uploaded to Appwrite. For the sake of this example, we will be using Dropbox’s Python SDK. A similar concept applies to other API providers like Box or Google Drive. So let’s get started.

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.