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⚡ Bolt: Replace df.iterrows() with df.to_dict('records')#71

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bolt-optimize-iterrows-12947904602993068091
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⚡ Bolt: Replace df.iterrows() with df.to_dict('records')#71
alinelena wants to merge 1 commit into
mainfrom
bolt-optimize-iterrows-12947904602993068091

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@alinelena

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💡 What: Replaced df.iterrows() with df.to_dict('records') inside src/lavello_mlips/verify_processed_omol25.py.
🎯 Why: Iterating over pandas DataFrames using iterrows() is a known massive performance bottleneck because it yields a new Series object for every single row. Converting to a native Python list of dictionaries first completely bypasses this overhead, resulting in much faster execution for large parquet files.
📊 Impact: Significant reduction in verification time when matching datasets, avoiding pandas object instantiation per row.
🔬 Measurement: Run verify_processed_omol25 on a large test set and compare execution times; the to_dict('records') version should be orders of magnitude faster. Verified correctness via pytest.


PR created automatically by Jules for task 12947904602993068091 started by @alinelena

Replaced the slow `df.iterrows()` with the highly performant `df.to_dict('records')` in `verify_processed_omol25.py`. Updated downstream handling of the row type to expect a native dictionary rather than a pandas Series, avoiding massive pandas overhead for large datasets.

Co-authored-by: alinelena <3306823+alinelena@users.noreply.github.com>
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