Automates the execution, editing, and dependency management of Jupyter notebooks using jtool and uv.
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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.
Características Principales
Jupyter server management and jtool integration
Headless notebook execution via uv and nbconvert
Programmatic notebook editing and patching via Python scripts
12 GitHub stars
Isolated dependency injection using uv --with flags
Automated cell-level control and output management
Casos de Uso
Updating notebook content or dependencies programmatically
Executing notebooks in CI/CD environments without manual GUI interaction
Running automated data analysis pipelines from the command line
