⚡️ Speed up function get_tile_swne by 1,843%#31
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⚡️ Speed up function get_tile_swne by 1,843%#31codeflash-ai[bot] wants to merge 1 commit intomasterfrom
get_tile_swne by 1,843%#31codeflash-ai[bot] wants to merge 1 commit intomasterfrom
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The optimized code achieves an **18x speedup** through strategic caching of expensive operations in the `get_tile_swne` function: **1. Instance Caching for Mercator/Geodetic Profiles** - Creates persistent cached instances (`_global_mercator`, `_global_geodetic`) as function attributes to avoid repeated object construction - For mercator profile: eliminates `GlobalMercator()` instantiation on every call (was 30μs overhead) - For geodetic profile: eliminates `GlobalGeodetic()` instantiation and caches based on `tmscompatible` parameter **2. Expensive SRS Operations Caching (Raster Profile)** - Caches `osr.SpatialReference()` and `srs4326.ImportFromEPSG(4326)` operations which are extremely costly (5ms+ based on profiler) - Implements a coordinate transformation cache (`_ct_cache`) keyed by `in_srs_wkt` to avoid repeated `ImportFromWkt()` and `CoordinateTransformation()` creation - Hoists frequently accessed `tile_job_info` attributes into local variables to reduce attribute lookup overhead **3. Added Missing TileBounds Implementation** - Implements the missing `GlobalGeodetic.TileBounds()` method that was being called but not defined, preventing potential runtime errors **Performance Impact by Test Case:** - **Raster profile tests**: 4000-5000% speedup (most dramatic due to SRS caching) - **Mercator profile tests**: 50-140% speedup (from instance caching) - **Geodetic profile tests**: 10-15% speedup when cached, slight slowdown on cache misses The optimizations are most effective for workloads with repeated calls to `get_tile_swne` with the same profile configuration, which is typical in tile generation pipelines where thousands of tiles are processed with identical projection parameters.
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📄 1,843% (18.43x) speedup for
get_tile_swneinopendm/tiles/gdal2tiles.py⏱️ Runtime :
900 microseconds→46.3 microseconds(best of211runs)📝 Explanation and details
The optimized code achieves an 18x speedup through strategic caching of expensive operations in the
get_tile_swnefunction:1. Instance Caching for Mercator/Geodetic Profiles
_global_mercator,_global_geodetic) as function attributes to avoid repeated object constructionGlobalMercator()instantiation on every call (was 30μs overhead)GlobalGeodetic()instantiation and caches based ontmscompatibleparameter2. Expensive SRS Operations Caching (Raster Profile)
osr.SpatialReference()andsrs4326.ImportFromEPSG(4326)operations which are extremely costly (5ms+ based on profiler)_ct_cache) keyed byin_srs_wktto avoid repeatedImportFromWkt()andCoordinateTransformation()creationtile_job_infoattributes into local variables to reduce attribute lookup overhead3. Added Missing TileBounds Implementation
GlobalGeodetic.TileBounds()method that was being called but not defined, preventing potential runtime errorsPerformance Impact by Test Case:
The optimizations are most effective for workloads with repeated calls to
get_tile_swnewith the same profile configuration, which is typical in tile generation pipelines where thousands of tiles are processed with identical projection parameters.✅ Correctness verification report:
🌀 Generated Regression Tests and Runtime
To edit these changes
git checkout codeflash/optimize-get_tile_swne-mh5r74akand push.