⚡️ Speed up method GraphicsContextPdf.clip_cmd by 13%
#233
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📄 13% (0.13x) speedup for
GraphicsContextPdf.clip_cmdinlib/matplotlib/backends/backend_pdf.py⏱️ Runtime :
21.3 microseconds→18.8 microseconds(best of16runs)📝 Explanation and details
The optimized code achieves a 13% speedup through several targeted micro-optimizations that reduce Python's attribute lookup overhead and object creation costs:
Key optimizations:
Reduced attribute lookups in
pathOperations: The original code performed repeatedOp.moveto.value,Op.lineto.value, etc. lookups inside the list literal on every call. The optimized version extracts these values into local variables once, eliminating redundant attribute access. This is particularly effective sincepathOperationsis a static method called frequently during PDF path rendering.Variable localization in
push()andpop(): The optimized code storesself.fileandself.parentin local variables to avoid repeated attribute lookups. Inpop(),parent = self.parenteliminates multipleself.parentaccesses, which is especially beneficial sincepop()can be called many times in loops.Optimized tuple comparisons in
clip_cmd(): The original code repeatedly accessedself._cliprectandself._clippathin tuple comparisons. The optimized version caches these values ascr, cpandtrg_cr, trg_cp, reducing attribute access overhead in the tight loop where clipping state is checked.Precomputed Name cache for procsets: The optimized code moves the
Nameobject creation for PDF procsets outside the resource dictionary construction, avoiding repeated object instantiation during PDF initialization.Performance impact: The line profiler shows that while the total time for individual functions remains similar, the optimizations reduce per-hit costs for frequently executed operations. The test results demonstrate 11.8-14.9% improvements in clipping operations, which are critical for PDF rendering performance where graphics contexts are frequently pushed/popped during complex drawing operations.
These optimizations are particularly valuable for matplotlib's PDF backend, which handles numerous graphics state changes during plot rendering, making the cumulative effect of these micro-optimizations significant for complex figures with many elements.
✅ Correctness verification report:
🌀 Generated Regression Tests and Runtime
To edit these changes
git checkout codeflash/optimize-GraphicsContextPdf.clip_cmd-miyoj9t7and push.