2025-10-01 –, Louis Armand 1 - Est
jupyter-fs provides an interface between PyFilesystem and fsspec file systems, the JupyterLab user interface, and the Jupyter notebooks you run. Connect and browse your local filesystem, S3, Samba, WebDAV, and more, interacting with data seamlessly from both the JupyterLab UI and your notebook's kernel.
Jupyter is built with local filesystem integration out of the box. However, most data-oriented workflows involve data living in a lot of locations:
- somewhere outside your development tree on your local machine
- a shared drive
- S3
- etc
Navigating across these resources involves switching back and forth between different applications and browsers.
This can introduce a lot of friction when doing data analysis.
jupyter-fs provides an interface between the JupyterLab UI, the python notebook kernel, and arbitrary filesystem backends.
It is built on top of PyFilesystem and fsspec, which allow connection to a wide array of data backends including S3, SFTP, SSHFS, FTP, Samba, WebDAV, Git, Dropbox, Google Drive, and many more.
Backends are exposed via the high performance tree-finder UI library right inside of JupyterLab, providing a convenient and unified tree-oriented file browsing experience.
Backends can be directly connected to via click interactions or python snippets, making it quick and easy to connect to the resources you're viewing in the tree browser directly from your notebook kernel or from other JupyterLab extensions (like the CSV Viewer).
With jupyter-fs, your notebook environment can become a high powered data studio.
Tim is a Quantitative Developer at Cubist Systematic Strategies and an adjunct professor in the Computer Science Department at Columbia University.