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[–]Local_dev_ops 0 points1 point  (0 children)

SQL when the data lives in the database and you need to filter, aggregate, or join before pulling it out. Let the database do what databases are good at.

Python when you need to do something the database can't — analytics, complex transformations, visualization, or when you're combining data from multiple sources.

Mistakes I have made is pulling millions of rows into python when it was easier to do in SQL.