⚡️ Speed up function _filter_new_declarations by 12% in PR #1546 (follow-up-reference-graph)#1548
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The optimization achieves a **12% runtime improvement** (783μs → 698μs) by replacing the lambda function in the sorting key with `operator.attrgetter("start_line")` and eliminating an unnecessary intermediate variable.
**Key optimization:**
Using `attrgetter("start_line")` instead of `lambda d: d.start_line` reduces per-item function call overhead during sorting. In Python, lambda functions incur dispatch costs for each element, while `attrgetter` is implemented in C and provides faster attribute access. The line profiler shows the sorting operation dropped from 967μs (24.7% of runtime) to 756μs (22.5%), a reduction of ~22% in sorting time alone.
**Why this works:**
- `attrgetter` is a specialized built-in operator that bypasses Python's function call mechanism
- Removing the `sorted_declarations` intermediate variable eliminates a list reference assignment and slightly reduces memory allocation overhead
- The optimization directly iterates over `sorted()`, which is more idiomatic and marginally more efficient
**Performance characteristics from tests:**
- **Small inputs (< 10 items):** Minor slowdown of 1-15% due to the overhead of importing `attrgetter` outweighing benefits
- **Large inputs (100-1000 items):** Significant speedup of 8-27%, with the best gains (27.7%) on the 1000-item test case where sorting overhead dominates
- The optimization particularly excels when filtering many declarations with duplicate sources, as seen in tests with 100-500 items showing 6-26% improvements
This is a textbook micro-optimization that pays dividends in hot paths processing many declarations, trading a negligible cost on trivial inputs for substantial gains on realistic workloads.
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PR Review SummaryPrek Checks
Code ReviewNo critical issues found. This is a straightforward micro-optimization:
Test Coverage
Last updated: 2026-02-19 |
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⚡️ This pull request contains optimizations for PR #1546
If you approve this dependent PR, these changes will be merged into the original PR branch
follow-up-reference-graph.📄 12% (0.12x) speedup for
_filter_new_declarationsincodeflash/languages/javascript/code_replacer.py⏱️ Runtime :
783 microseconds→698 microseconds(best of250runs)📝 Explanation and details
The optimization achieves a 12% runtime improvement (783μs → 698μs) by replacing the lambda function in the sorting key with
operator.attrgetter("start_line")and eliminating an unnecessary intermediate variable.Key optimization:
Using
attrgetter("start_line")instead oflambda d: d.start_linereduces per-item function call overhead during sorting. In Python, lambda functions incur dispatch costs for each element, whileattrgetteris implemented in C and provides faster attribute access. The line profiler shows the sorting operation dropped from 967μs (24.7% of runtime) to 756μs (22.5%), a reduction of ~22% in sorting time alone.Why this works:
attrgetteris a specialized built-in operator that bypasses Python's function call mechanismsorted_declarationsintermediate variable eliminates a list reference assignment and slightly reduces memory allocation overheadsorted(), which is more idiomatic and marginally more efficientPerformance characteristics from tests:
attrgetteroutweighing benefitsThis is a textbook micro-optimization that pays dividends in hot paths processing many declarations, trading a negligible cost on trivial inputs for substantial gains on realistic workloads.
✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-pr1546-2026-02-19T11.06.50and push.