ipynb

At a system level, working with .ipynb (Jupyter Notebook) files involves understanding them as structured JSON documents, and then managing, manipulating, or integrating them into broader data workflows, systems, or tools. Here’s a breakdown of what you can do at that level:

Programmatic Manipulation (as JSON)

.ipynb files are JSON-structured documents. At a system level, you can:

• Parse and modify them using Python (json module), nbformat, or external tools.
• Extract code cells, markdown cells, outputs, and metadata.
• Insert cells programmatically to generate templated or modular notebooks.

Execution Automation

You can execute .ipynb files non-interactively. Batch run notebooks with tools like:

• papermill (parameterised execution)
• nbconvert --execute
• jupyter nbclient

Conversion & Export

Convert notebooks into various formats:

• HTML, PDF (e.g., for reports, presentations)
• Python scripts (nbconvert)
• Slideshows (Reveal.js)
• Markdown for publishing

Embedding and Serving

• Serve as interactive documentation or reports (e.g., Jupyter Book)
• Used in browser-based notebook environments (JupyterHub, Google Colab).