generate-notebook-from-module

Generating a Jupyter Notebook from a Python module is automated by parsing the module's public API with Python AST and assembling structured notebooks with code and markdown example templates into a notebooks directory.

Documenting a Python module's public API for exploration is best achieved by extracting public functions through AST parsing and producing structured Jupyter Notebooks with API usage examples to support documentation and teaching workflows.

Yes, Python AST parsing is required to analyze completed Python modules, extract their public API, and auto-generate corresponding Jupyter Notebooks with structured API example templates for documentation purposes.

You can organize generated notebooks by task ordering for teaching workflows because the notebook assembler supports optional task-ordering and deterministic naming within the notebooks directory to align with documentation and learning objectives.

The notebook generator does not extract private methods from Python modules; it specifically analyzes the public API using AST parsing to ensure the generated notebook templates focus on external usage and exploration.