⚡️ Speed up function templates_path by 2,968%#3
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The optimization implements **lazy caching** to avoid repeated `Path` object construction. **Key changes:** - Added a module-level cache variable `_templates_path` initialized to `None` - First call computes and stores the path; subsequent calls return the cached `Path` object - Added explicit import of `ROOT_DIR` for clarity **Why it's faster:** The original code calls `Path(ROOT_DIR) / "static" / "templates"` on every invocation, which creates new `Path` objects and performs string concatenation operations each time. The optimized version does this expensive computation only once and returns the pre-computed `Path` object on subsequent calls. **Performance characteristics:** - **First call**: Slightly slower due to the conditional check and assignment (38.9μs vs 40.7μs per hit originally) - **Subsequent calls**: ~97% faster (827ns for the check + 465ns for the return vs 40.7μs for full computation) - **Overall speedup**: 2967% improvement when the function is called multiple times **Best suited for:** Applications where `templates_path()` is called repeatedly, as evidenced by the test results showing 3000%+ speedups on repeated calls. The caching strategy becomes more beneficial as the call frequency increases.
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📄 2,968% (29.68x) speedup for
templates_pathinhiggsfield/internal/util.py⏱️ Runtime :
48.0 microseconds→1.56 microsecondss(best of72runs)📝 Explanation and details
The optimization implements lazy caching to avoid repeated
Pathobject construction.Key changes:
_templates_pathinitialized toNonePathobjectROOT_DIRfor clarityWhy it's faster:
The original code calls
Path(ROOT_DIR) / "static" / "templates"on every invocation, which creates newPathobjects and performs string concatenation operations each time. The optimized version does this expensive computation only once and returns the pre-computedPathobject on subsequent calls.Performance characteristics:
Best suited for: Applications where
templates_path()is called repeatedly, as evidenced by the test results showing 3000%+ speedups on repeated calls. The caching strategy becomes more beneficial as the call frequency increases.✅ Correctness verification report:
🌀 Generated Regression Tests and Runtime
🔎 Concolic Coverage Tests and Runtime
codeflash_concolic_3jg4m0fg/tmpt464ndzh/test_concolic_coverage.py::test_templates_pathTo edit these changes
git checkout codeflash/optimize-templates_path-mgll4hzuand push.