larentals VS dash

Also be sure to check out the interactive version of this spreadsheet at WhereToLive.LA courtesy of /u/cheeze_whiz_dot_com, my thanks to him.

Also be sure to check out the interactive version of this spreadsheet at WhereToLive.LA courtesy of /u/cheeze_whiz_dot_com, my thanks to him.

I appreciate the stance you're taking. I myself am trying to find an apartment to lease starting July 1st. As everyone here would know, its difficult. I've been utilizing the wheretolive.la site and have had trouble contacting a few places I'm interested in. Assuming your inbox may be busy, I wanted to ask if I could message or email you for some help and direction on securing a spot. I've really been on the hunt and contacted every phone and email available to me.

I just looked on wheretolive.la and this place is pretty cool:

Check out my website https://wheretolive.la/ (I modeled it based on the weekly rental listing spreadsheets posted here every Monday). You can filter the map according to all of your specified needs except for "normal neighborhood" - that's a little too subjective of a criteria to filter on 😛

Check https://wheretolive.la/. It's actually data sourced from the weekly spreadsheets from /u/WilliamMcCarty!

The front end is actually written in Python (but it's a wrapper for the Leaflet JavaScript (or is it React?) library) so I can only really accept contributions written in Python. If you're willing & able to do that though feel free to submit a PR or an issue on my GitHub! I could always use more help.

Also be sure to check out the interactive version of this spreadsheet at WhereToLive.LA courtesy of /u/cheeze_whiz_dot_com, my thanks to him.

Also be sure to check out the interactive version of this spreadsheet at WhereToLive.LA courtesy of /u/cheeze_whiz_dot_com, my thanks to him.

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.