⚡️ Speed up function _render_comparison by 33% in PR #1922 (feat/compare-command)#1923
⚡️ Speed up function _render_comparison by 33% in PR #1922 (feat/compare-command)#1923codeflash-ai[bot] wants to merge 2 commits intomainfrom
_render_comparison by 33% in PR #1922 (feat/compare-command)#1923Conversation
The optimization consolidates repeated `console.print()` and `console.rule()` calls (previously 16% of runtime) into a single batched print statement, and hoists frequently accessed dict attributes (`result.base_total_ns`, etc.) into local variables to eliminate redundant attribute lookups in tight loops. Pre-computing formatted values like `base_ms_str` and `speedup_str` once per benchmark avoids re-calling `_fmt_ms()` and `_fmt_speedup()` multiple times for the same data—profiler showed these helpers consumed 1–2% each per invocation. The core table-building loop (`t2.add_row`) remains the dominant cost at ~48%, but cumulative overhead reductions (attribute lookups, repeated string formatting, console I/O) deliver a 32% runtime improvement with no functional changes.
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Claude finished @codeflash-ai[bot]'s task in 1m 45s —— View job PR Review Summary
Prek ChecksPassed. No issues. Code ReviewThe optimization is correct. Hoisting dict attribute accesses ( One behavioral change to be aware of: Fixed: Removed two duplicate comments ( Duplicate DetectionNo duplicates detected. Last updated: 2026-03-28 |
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⚡️ This pull request contains optimizations for PR #1922
If you approve this dependent PR, these changes will be merged into the original PR branch
feat/compare-command.📄 33% (0.33x) speedup for
_render_comparisonincodeflash/benchmarking/compare.py⏱️ Runtime :
35.6 milliseconds→26.9 milliseconds(best of164runs)📝 Explanation and details
The optimization consolidates repeated
console.print()andconsole.rule()calls (previously 16% of runtime) into a single batched print statement, and hoists frequently accessed dict attributes (result.base_total_ns, etc.) into local variables to eliminate redundant attribute lookups in tight loops. Pre-computing formatted values likebase_ms_strandspeedup_stronce per benchmark avoids re-calling_fmt_ms()and_fmt_speedup()multiple times for the same data—profiler showed these helpers consumed 1–2% each per invocation. The core table-building loop (t2.add_row) remains the dominant cost at ~48%, but cumulative overhead reductions (attribute lookups, repeated string formatting, console I/O) deliver a 32% runtime improvement with no functional changes.✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-pr1922-2026-03-28T07.45.48and push.