Python
How to Test Jupyter Notebooks: nbmake, testbook, and nbval
Jupyter notebooks are the primary artifact for data science work—model training, data exploration, report generation. Yet most teams treat them as write-only documents. Notebooks break silently when dependencies update, when data shapes change, or when code paths that ran during development are skipped during the final run. Testing notebooks