⚡️ Speed up function bbox_to_polygon by 5%#8
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The optimization reduces redundant tuple indexing operations by caching `bbox[0]` and `bbox[1]` in local variables `bbox0` and `bbox1`. In the original code, `bbox[0]` is accessed 3 times and `bbox[1]` is accessed 3 times within the single return statement. Each tuple indexing operation has overhead in Python. The optimized version performs each indexing only once, storing the results in local variables that are then reused. This micro-optimization is particularly effective because: - **Tuple indexing reduction**: Eliminates 4 redundant indexing operations (from 6 total to 2) - **Local variable access**: Reading from local variables is faster than tuple indexing in Python - **Hot path optimization**: This function is likely called frequently in document processing workflows The test results show the optimization performs best on large-scale operations (5-7% speedup on batch processing tests like `test_bbox_to_polygon_many_boxes` and `test_bbox_to_polygon_stress_randomized`) where the indexing overhead compounds across many function calls. Individual function calls show mixed but generally positive results, with the overall 5% speedup representing meaningful performance gains for high-frequency geometric operations.
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📄 5% (0.05x) speedup for
bbox_to_polygonindoctr/utils/geometry.py⏱️ Runtime :
419 microseconds→398 microseconds(best of176runs)📝 Explanation and details
The optimization reduces redundant tuple indexing operations by caching
bbox[0]andbbox[1]in local variablesbbox0andbbox1.In the original code,
bbox[0]is accessed 3 times andbbox[1]is accessed 3 times within the single return statement. Each tuple indexing operation has overhead in Python. The optimized version performs each indexing only once, storing the results in local variables that are then reused.This micro-optimization is particularly effective because:
The test results show the optimization performs best on large-scale operations (5-7% speedup on batch processing tests like
test_bbox_to_polygon_many_boxesandtest_bbox_to_polygon_stress_randomized) where the indexing overhead compounds across many function calls. Individual function calls show mixed but generally positive results, with the overall 5% speedup representing meaningful performance gains for high-frequency geometric operations.✅ Correctness verification report:
⚙️ Existing Unit Tests and Runtime
common/test_utils_geometry.py::test_bbox_to_polygon🌀 Generated Regression Tests and Runtime
To edit these changes
git checkout codeflash/optimize-bbox_to_polygon-mg7ryhciand push.