Hi, It takes long time to open files and folders now. It has gotten worse over the last month. I write code in ipynb, and I know that the files can heavy. Could that be why?
Steps to Reproduce
Try to open a folder with data and scripts in ipynb files
A couple things that can help narrow down what’s happening on your side:
Start Cursor with extensions disabled and see if it makes a difference:
cursor --disable-extensions
This often helps confirm if an extension is causing the slowdown, like Jupyter or Python.
Open Process Explorer Cmd+Shift+P then Developer: Open Process Explorer while opening an .ipynb and check which process is using CPU or memory, like extensionHost, ptyHost, or the renderer.
Your Windows 10 version is build 17763, which is LTSC 2019 from 2018. Newer Electron apps can run slower on builds like that. If you can update Windows, it’s worth trying since it can help performance a lot.
If you find one process or a specific extension that clearly triggers the slowdown, send it here and it’ll help the investigation.
The issue is Cursor specific, because other IDEs do not face the same issues with the same repos.
One quick fix I use is to first open the folder in Cursor, and close all open windows that have .ipynb or markdown files(while it’s all still loading) and close the Cursor window. Then reopen the folder in Cursor, and it loads up quickly.
Thanks for getting back to us. Another workaround from @Adarsh_Pandey in the post above is worth trying: open the folder, close all .ipynb and markdown tabs while everything is loading, then restart Cursor and open the folder again. A few users have already said this helps.
If you find a specific extension or a process in Process Explorer that clearly slows things down when opening .ipynb, drop it here and we’ll add it to the investigation.
Hi, Your solution has also worked for me now; open new folder, close the notebooks and markdowns that are automatically opened, close cursor, open cursor and the folder again.
Hey @Lars_Kjaer, glad to hear the workaround helped. We’re still working on overall Jupyter Notebook performance, so if you run into slowdowns again in a future version, please open a new thread and we’ll take another look.