Automates the execution, editing, and dependency management of Jupyter notebooks using jtool and uv.
This skill streamlines Jupyter notebook workflows by leveraging jtool for granular cell execution and uv for isolated, high-performance dependency management. It allows Claude to perform headless notebook execution, programmatically patch notebook JSON structures (nbformat v4), and manage local Jupyter servers, ensuring a clean and efficient environment for data science and analysis tasks without polluting global system paths.
Key Features
01Jupyter server management and jtool integration
02Headless notebook execution via uv and nbconvert
03Programmatic notebook editing and patching via Python scripts
0412 GitHub stars
05Isolated dependency injection using uv --with flags
06Automated cell-level control and output management
Use Cases
01Updating notebook content or dependencies programmatically
02Executing notebooks in CI/CD environments without manual GUI interaction
03Running automated data analysis pipelines from the command line
