Why Should You Care? Jupyter Notebooks are a cornerstone of the Python ecosystem, especially in research and data science. Their ability to combine code, markdown, results, and visualizations makes them a powerful tool for analysis and communication. <—! Include a graphic from the paper on how the example jpuyter looks like —> But they also come with well-documented drawbacks: hidden execution order, reproducibility issues, and encouragement of poor coding practices. A 2019 study — “A Large-scale Study about Quality and Reproducibility of Jupyter Notebooks”1 — highlighted how these problems undermine reliability at scale.