⚡ Bolt: [performance improvement] optimize dataframe iteration

[alinelena]

💡 What: Replaced df.iterrows() with df.to_dict('records') when processing Parquet records in verify_processed_omol25.py.
🎯 Why: iterrows() is an anti-pattern in pandas for large datasets because it incurs huge overhead by creating a new pd.Series object for every single row. Converting the DataFrame to a list of native Python dictionaries pushes the iteration into optimized C code and returns lightweight dicts, which are perfectly suited for building the parquet_by_sha and parquet_by_argone_rel lookup tables.
📊 Impact: Significantly faster script execution time for verification of large datasets, bypassing the heavy pandas Series construction loop.
🔬 Measurement: Running the verification script on large Parquet and ExtXYZ files will show a drastically reduced "Loading Parquet file..." phase compared to the original code.

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PR created automatically by Jules for task 14907987310001069741 started by @alinelena

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