A JupyterLab plugin that adds multiple filebrowsers for local and remote filesystems like S3 and Samba.
jupyter-fs is a JupyterLab plugin that acts as a filesystem-like contents manager, allowing users to access and manage multiple local and remote filesystems directly within JupyterLab. It connects to backends like S3, SMB, and local OS filesystems via PyFilesystem and fsspec, eliminating the need to switch between tools for data access.
Data scientists, researchers, and developers working in Jupyter environments who need to interact with diverse storage systems such as cloud buckets (S3) or network shares (SMB) without leaving their notebooks.
It provides a seamless, integrated way to browse and manage multiple filesystems within JupyterLab, with flexible configuration, authentication support, and compatibility with numerous backend protocols through established Python libraries.
A filesystem-like contents manager for multiple backends in Jupyter
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Allows setting up and using as many filebrowsers as needed for different filesystem resources, directly within JupyterLab, as shown in the demo GIF and configuration examples.
Built on PyFilesystem and fsspec, it supports diverse filesystems like S3, SMB, and local OS, leveraging existing Python libraries for extensive protocol support.
Features a built-in auth dialog that securely handles credentials via templated URLs (e.g., smb://{{user}}:{{passwd}}@host), simplifying access to protected resources.
Can be configured through JupyterLab's settings UI or server-side config files (JSON or Python), offering both user-friendly and administrative control.
Configuring backends like s3fs requires manual environment variable setup (e.g., FSSPEC_S3_KEY), as noted in the documentation, which can be error-prone and tedious.
The README admits only S3 and SMB backends are tested in CI, so other PyFilesystem or fsspec backends may have untested compatibility issues or bugs.
Relies heavily on PyFilesystem and fsspec, meaning any limitations, breaking changes, or bugs in those libraries directly impact jupyter-fs's stability and functionality.