⚡️ Speed up function convert_camel_case_resource_noun_to_snake_case by 13%#36
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The optimized code achieves a **12% speedup** by **pre-compiling the regex pattern** at module scope instead of compiling it on every function call.
**Key optimization:**
- **Regex pre-compilation**: `_CAMEL_TO_SNAKE_RE = re.compile(r"([A-Z]+)")` is created once when the module loads, rather than calling `re.sub("([A-Z]+)", ...)` which compiles the pattern every time the function runs.
**Why this improves performance:**
In Python's `re` module, every call to `re.sub()` with a string pattern must first compile that pattern into a regex object. By pre-compiling the pattern once and reusing the compiled object via `_CAMEL_TO_SNAKE_RE.sub()`, we eliminate this repeated compilation overhead.
The line profiler shows the regex substitution line dropped from 11.9ms to 10.2ms (14% reduction), which represents 93% of the original function's total time. This optimization is particularly effective because:
- The same regex pattern `([A-Z]+)` is used repeatedly across all function calls
- Regex compilation has fixed overhead regardless of input size
- The function is called frequently (1377 times in the profiler)
**Test case benefits:**
- **Basic conversions** (single/multi-word): 12-21% faster
- **Large-scale tests** with long strings: 10-15% faster
- **Edge cases** with special characters: Up to 30% faster for simple cases
- **Batch processing**: 15% improvement when processing many strings
The optimization maintains identical behavior while providing consistent performance gains across all input types.
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📄 13% (0.13x) speedup for
convert_camel_case_resource_noun_to_snake_caseingoogle/cloud/aiplatform/utils/__init__.py⏱️ Runtime :
4.06 milliseconds→3.60 milliseconds(best of164runs)📝 Explanation and details
The optimized code achieves a 12% speedup by pre-compiling the regex pattern at module scope instead of compiling it on every function call.
Key optimization:
_CAMEL_TO_SNAKE_RE = re.compile(r"([A-Z]+)")is created once when the module loads, rather than callingre.sub("([A-Z]+)", ...)which compiles the pattern every time the function runs.Why this improves performance:
In Python's
remodule, every call tore.sub()with a string pattern must first compile that pattern into a regex object. By pre-compiling the pattern once and reusing the compiled object via_CAMEL_TO_SNAKE_RE.sub(), we eliminate this repeated compilation overhead.The line profiler shows the regex substitution line dropped from 11.9ms to 10.2ms (14% reduction), which represents 93% of the original function's total time. This optimization is particularly effective because:
([A-Z]+)is used repeatedly across all function callsTest case benefits:
The optimization maintains identical behavior while providing consistent performance gains across all input types.
✅ Correctness verification report:
🌀 Generated Regression Tests and Runtime
To edit these changes
git checkout codeflash/optimize-convert_camel_case_resource_noun_to_snake_case-mgkkldbsand push.