⚡️ Speed up method _Distplot.make_hist by 45%
#79
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📄 45% (0.45x) speedup for
_Distplot.make_histinplotly/figure_factory/_distplot.py⏱️ Runtime :
971 microseconds→667 microseconds(best of530runs)📝 Explanation and details
The optimized code achieves a 45% speedup by eliminating repeated attribute lookups and function calls within the loop.
Key optimizations:
Local variable caching: The optimized version extracts all
self.*attributes into local variables before the loop (trace_number,hist_data,histnorm, etc.). This eliminates repeated attribute access overhead during each iteration.Pre-computed color array length: Instead of calling
len(self.colors)on every iteration for the modulo operation, it's computed once asn_colorsand reused.Dictionary literals over dict() constructor: Replaced
dict()calls with dictionary literals{}, which are faster to construct in Python.Why this works:
self.attribute) has overhead compared to local variable accesslen()function call was being repeated 2,000+ times in the profiler resultsdict()constructor callsPerformance characteristics:
The optimization scales particularly well with the number of traces since the attribute lookup overhead compounds with each iteration. All test cases show consistent improvements, with the largest gains on scenarios with many traces where the loop iterations amplify the per-iteration savings.
✅ Correctness verification report:
🌀 Generated Regression Tests and Runtime
🔎 Concolic Coverage Tests and Runtime
codeflash_concolic_grpsys06/tmpwxuplum7/test_concolic_coverage.py::test__Distplot_make_histTo edit these changes
git checkout codeflash/optimize-_Distplot.make_hist-mhg6s96qand push.