⚡ Bolt: [performance improvement] optimize DataFrame iteration in verify_processed_omol25.py

[alinelena]

💡 What: Replaced df.iterrows() with df.to_dict('records') in src/lavello_mlips/verify_processed_omol25.py, updating downstream data access since row items are now native dictionaries. Added explanatory comments.

🎯 Why: df.iterrows() is an anti-pattern in Pandas because it incurs massive overhead by creating a new Series object for every single row. For large datasets like those found in Parquet metadata, this becomes a severe bottleneck.

📊 Impact: This optimization significantly speeds up the verification pipeline—iterating over a list of dicts is often 10x–100x faster than using df.iterrows().

🔬 Measurement: Execute python -m pytest tests/test_verify_processed_omol25.py to confirm functionality works as expected. Measure execution time with a large sample parquet file before and after this change.

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PR created automatically by Jules for task 5705054899208680353 started by @alinelena

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