⚡ Bolt: [performance improvement]#46
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💡 What: Replaced iterative `.encode()` and `.update()` calls in the `geom_sha1` molecular fingerprinting function with a single generator expression `.join()` and a single `.encode()` / `.update()` operation. Also fixed E741 ambiguous variable name `l` to `l_idx` in `homo_lumo` and satisfied linters. 🎯 Why: Iterative method calls and repeated small string encoding inside a loop introduce significant overhead in Python, especially for large molecules or large datasets. 📊 Impact: Expected to reduce CPU overhead during fingerprint generation, leading to faster data processing speeds when handling millions of molecules. 🔬 Measurement: Run a local benchmark generating 10,000 hashes for large molecular structures and compare execution times, or monitor the throughput of the parsing worker during a large batch process. Co-authored-by: alinelena <3306823+alinelena@users.noreply.github.com>
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💡 What: Replaced iterative
.encode()and.update()calls in thegeom_sha1molecular fingerprinting function with a single generator expression.join()and a single.encode()/.update()operation. Also fixed E741 ambiguous variable nameltol_idxinhomo_lumoand satisfied linters.🎯 Why: Iterative method calls and repeated small string encoding inside a loop introduce significant overhead in Python, especially for large molecules or large datasets.
📊 Impact: Expected to reduce CPU overhead during fingerprint generation, leading to faster data processing speeds when handling millions of molecules.
🔬 Measurement: Run a local benchmark generating 10,000 hashes for large molecular structures and compare execution times, or monitor the throughput of the parsing worker during a large batch process.
PR created automatically by Jules for task 6459968803528350611 started by @alinelena