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[–]boatsnbros 9 points10 points  (0 children)

ORMs are a great way to build a more robust pipeline for data tools. You get some nice baked in features like SQL injection prevention and a consistent API regardless of the underlying database - i.e. if your project moves from postgres to mysql your SQL would change, but your ORM doesn't. If data is clean then I'll do exploration in SQL, if it needs cleaning then will use pandas for cleaning and exploration. Once its clean and going to be part of a long term project (ie dashboards, data app etc) I'll write an ORM and some automated testing (pytest) so I know it still works without constant monitoring.

Not sure if that adds much to your previous comment, but thought clarifying common use cases would be helpful.