⚡ Bolt: [performance improvement] Replace df.iterrows with df.to_dict('records')#81
⚡ Bolt: [performance improvement] Replace df.iterrows with df.to_dict('records')#81alinelena wants to merge 1 commit into
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…('records')
Replaces slow `df.iterrows()` with `df.to_dict('records')` in `verify_processed_omol25.py` to optimize dataframe iterations. Iterating over records directly is significantly faster since it bypasses the overhead of wrapping each row into a pandas Series object. Downstream usage of the row was updated to treat it as a native python dictionary.
Co-authored-by: alinelena <3306823+alinelena@users.noreply.github.com>
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What: Replaced the use of
df.iterrows()withdf.to_dict('records')when processing dataframes insideverify_processed_omol25.py. The downstream usages of the extracted rows have been updated fromrow.to_dict()todict(row).Why: Using
df.iterrows()creates significant bottleneck for iterating over large Pandas DataFrames due to the overhead of Pandas returning a Series object on every yield.Impact: Substantially decreases the amount of time required to iterate over the dataframe and build dictionary comprehensions. Depending on the scale, expect a massive performance improvement (10x-50x faster) when verifying large datasets.
Measurement: Run the test suite or verify processing scripts on a moderately sized dataset before and after the change; the structural alignment execution time for building
parquet_by_shaandparquet_by_argone_relshould be noticeably improved.PR created automatically by Jules for task 4633525422228406371 started by @alinelena