⚡️ Speed up function pipeline by 66%#308
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codeflash-ai[bot] wants to merge 1 commit intoexperimentalfrom
Open
⚡️ Speed up function pipeline by 66%#308codeflash-ai[bot] wants to merge 1 commit intoexperimentalfrom
pipeline by 66%#308codeflash-ai[bot] wants to merge 1 commit intoexperimentalfrom
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The hot path replaced `Array.prototype.reduce` with a cached-length for-loop, eliminating per-iteration closure allocation and callback overhead that `reduce` imposes when threading the accumulator through each function. This change is most visible in the no-functions edge case (28% faster) and chains with many simple transformations (e.g., 100-element chain improved 129%), where the original reducer's internal dispatch cost dominated. A fast-path check for zero functions avoids loop setup entirely. Minor slowdowns in a few Jest spy and large-data tests (4–10% range) reflect fixture-specific variance but do not offset the 65% overall runtime win.
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📄 66% (0.66x) speedup for
pipelineinjs/src/dataTransform.ts⏱️ Runtime :
15.1 milliseconds→9.10 milliseconds(best of100runs)📝 Explanation and details
The hot path replaced
Array.prototype.reducewith a cached-length for-loop, eliminating per-iteration closure allocation and callback overhead thatreduceimposes when threading the accumulator through each function. This change is most visible in the no-functions edge case (28% faster) and chains with many simple transformations (e.g., 100-element chain improved 129%), where the original reducer's internal dispatch cost dominated. A fast-path check for zero functions avoids loop setup entirely. Minor slowdowns in a few Jest spy and large-data tests (4–10% range) reflect fixture-specific variance but do not offset the 65% overall runtime win.✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-pipeline-mn6mx8q3and push.