Reading files from code

[psychemedia]

If I mount a file system directory, open a notebook in that context, and then try to read a file in that context, e.g. using pandas I get a file not found error.

Is there a way of setting a path either to a file in the file system directory, or a path to a file in the default file system (the browser file directory context, not the shared file-system-access context) when working on a notebook in the shared file-system context?

[martinRenou]

Thanks for opening an issue.

Are you talking about a JupyterLab context or a JupyterLite context?

• In the case of jupyterlite, you will be able to read and write into the "mounted" drive, because we also mount the drive in the Emscripten context (at least concerning jupyterlite-xeus's python kernel or jupyterlite-pyodide).
• In the case of jupyterlab, it will not work. The Python kernel executes its code on the server or an another external machine and it does not know anything about what happens in the front-end. jupyterlab-filesystem-access being a pure front-end package it does not communicate anything to the Python kernel about the mounted directory. I don't know if we can easily workaround this, but it's surely a difficult problem: jupyterlab is multi-client, what do you do if two users mount a local directory? Should we communicate their files to the server for the Python kernel to read and write? I don't think there is a good (and safe) solution to this problem.

[psychemedia]

JupyterLab ("full" server). Ok - so jupyterlab-filesystem-access is purely a UI tool in the browser, rather than a mount, although changes made to files in the UI will be saved back to the desktop.

FWIW, the use case is an educational environment, where students are accessing a remote server, The remote server does have file persistence, but it is also useful for students to have local copies of their files. Being able to access and run local files using the remotely served UI is really useful.

I suppose a workaround is for students to mirror data files by uploading them to the remote server, the kernel presumably seeing that file system as code is executed.

I guess another solution might be to upload eg data files that are intended to be read from executed code to a temporary directory on the server? Or maybe changing the background to a file listed in the jupyterlab-file-system-access file listing if a file of the same name exists the current directory path as seen on the server and as such was readable from code?