extract-and-run-samples

To automatically run Python code blocks from Markdown documentation and update output, you can use a tutorial maintenance skill that extracts fenced ```python snippets, executes them in an isolated Python 3.12 sandbox, and writes the captured stdout/stderr back into the source document.

The best way to keep execution outputs synchronized with Python code snippets in Markdown is to apply deterministic extraction of fenced blocks, run the code in a controlled environment, and auto-update the documentation with the captured stdout and stderr.

Yes, running Python sample code from Markdown requires a specific sandbox environment setup that isolates execution inside a directory named after the Markdown file and utilizes a Python 3.12 venv with uv setup to install dependencies before capturing output.

Yes, you can reuse a Markdown code execution workflow across multiple tutorial files by parameterizing the target file path and output destinations, which prevents cross-tutorial interference by creating isolated sandbox directories for each document.

To extract only specific Python fenced blocks from Markdown files without running other code, the system applies deterministic extraction that identifies and pulls only blocks starting with ```python, ignoring other fenced code formats in the document.

Limitations of automatically generating runnable output examples for Markdown tutorials include potential cross-tutorial interference if sandbox isolation fails, and the strict requirement for Python 3.12 venv and uv setup, which may not support legacy Python code snippets.