Implemented ingestion #9
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| try: | ||
| df = df.applymap(lambda x: int(x) if pd.notna(x) else x) | ||
| except ValueError as e: | ||
| raise HTTPException( | ||
| status_code=status.HTTP_400_BAD_REQUEST, | ||
| detail=f"Data type error: Non-integer value found: {e}", | ||
| ) |
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We can let the parent try/except handle this exception, since we already handle ValueError there
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They both handle different cases of value error. the apply map raises a value error if the something from the map is incorrect datatype. while the outervalue error handles value error from loading the df which might be some random value error in the csv like maybe mixed datatypes in a column.
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if this is the case but non-obvious, put a comment explaining it exactly as you did here.
in general if something is non-obvious in a PR and someone comments on it, it's good to put a comment. same goes for below.
| if df.index.duplicated().any(): | ||
| raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Duplicate Gene IDs detected.") | ||
| if df.columns.duplicated().any(): | ||
| raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Duplicate Sample IDs detected.") |
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these HTTP exceptions are re-caught below as 500s, which is incorrect.
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