[Question] Need help debugging a Python memory leak with pandas -- DataFrame keeps growing after drop()
3 months ago
I'm processing 50GB of CSV data in batches, but my process RSS climbs from 800MB to 12GB over an hour despite using .drop(inplace=True) and del df. Could be reference counting issue or C-level cache retention -- any specific garbage collection flags or tools you'd recommend for pinpointing which object isn't being freed?
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