⚡ Bolt: Replace df.iterrows() with df.to_dict('records')#71
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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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💡 What: Replaced
df.iterrows()withdf.to_dict('records')insidesrc/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_omol25on a large test set and compare execution times; theto_dict('records')version should be orders of magnitude faster. Verified correctness via pytest.PR created automatically by Jules for task 12947904602993068091 started by @alinelena