⚡️ Speed up function _pipe_line_with_colons by 46% in PR #217 (proper-cleanup)
#221
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⚡️ This pull request contains optimizations for PR #217
If you approve this dependent PR, these changes will be merged into the original PR branch
proper-cleanup.📄 46% (0.46x) speedup for
_pipe_line_with_colonsincodeflash/code_utils/tabulate.py⏱️ Runtime :
1.15 milliseconds→789 microseconds(best of265runs)📝 Explanation and details
Here are the main performance issues and solutions for your program.
Profile Insights
_pipe_segment_with_colonsis hit many times, and most time is spent creating new strings with expressions like'-' * nand concatenation._pipe_line_with_colons, almost all runtime is spent in the list comprehension calling_pipe_segment_with_colons._pipe_segment_with_colonscan be accelerated for common values (like when width is small or common) via caching.Optimizations
if-elif._pipe_segment_with_colonsusingfunctools.lru_cache(for acceleration when the same alignment and width is requested over and over).str.join,str.__mul__).strconcatenations.Here's the optimized code.
Why this version is faster
_pipe_segment_with_colonsto memoize results (Python will keep the last few most requested line segments in RAM). This is effective since your profile shows thousands of hits with the same arguments.eliffor clarity.These changes together should provide measurably improved runtime—especially for repeated, table-wide invocations! If you expect very large tables or uncommon
(align, colwidth)combinations, you can tune the cache size in@lru_cache(maxsize=N). For typical markdown/pipe-aligned tables, this value is more than enough.You may further accelerate with Cython or by using dedicated C-based formatters, but not within pure Python constraints.
✅ Correctness verification report:
🌀 Generated Regression Tests Details
To edit these changes
git checkout codeflash/optimize-pr217-2025-05-19T04.28.06and push.