⚡️ Speed up function set_custom_labels by 49%#41
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codeflash-ai[bot] wants to merge 1 commit intomainfrom
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⚡️ Speed up function set_custom_labels by 49%#41codeflash-ai[bot] wants to merge 1 commit intomainfrom
set_custom_labels by 49%#41codeflash-ai[bot] wants to merge 1 commit intomainfrom
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The optimization achieves a **48% speedup** by addressing two key performance bottlenecks:
**1. Reduced Settings Lookups**
The original code called `get_settings()` twice per function invocation. The optimized version caches the result in a local variable `settings`, eliminating redundant context lookups and exception handling. This saves ~34% of the original execution time based on the profiler data.
**2. Efficient String Building for Large Label Sets**
The critical optimization replaces repeated string concatenation (`+=`) with list accumulation and a single `join()`. String concatenation in Python creates new string objects each time, leading to O(N²) complexity. The optimized approach:
- Collects formatted strings in `custom_labels_lines` list
- Performs single `''.join(custom_labels_lines)` operation
- Reduces the most expensive line from 20.9% to 11.5% of total execution time
**3. Eliminated Redundant Operations**
- Removed unused `counter` variable
- Cached `k.lower().replace(' ', '_')` computation as `key_minimal`
**Performance Impact by Test Scale:**
- Small datasets (1-2 labels): 15-28% faster
- Medium datasets (dozens of labels): 36-45% faster
- Large datasets (100+ labels): 44-92% faster
The optimization is particularly effective for applications with many custom labels, where string building dominates execution time. The list+join pattern scales linearly versus the quadratic growth of repeated concatenation.
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📄 49% (0.49x) speedup for
set_custom_labelsinpr_agent/algo/utils.py⏱️ Runtime :
1.17 milliseconds→787 microseconds(best of86runs)📝 Explanation and details
The optimization achieves a 48% speedup by addressing two key performance bottlenecks:
1. Reduced Settings Lookups
The original code called
get_settings()twice per function invocation. The optimized version caches the result in a local variablesettings, eliminating redundant context lookups and exception handling. This saves ~34% of the original execution time based on the profiler data.2. Efficient String Building for Large Label Sets
The critical optimization replaces repeated string concatenation (
+=) with list accumulation and a singlejoin(). String concatenation in Python creates new string objects each time, leading to O(N²) complexity. The optimized approach:custom_labels_lineslist''.join(custom_labels_lines)operation3. Eliminated Redundant Operations
countervariablek.lower().replace(' ', '_')computation askey_minimalPerformance Impact by Test Scale:
The optimization is particularly effective for applications with many custom labels, where string building dominates execution time. The list+join pattern scales linearly versus the quadratic growth of repeated concatenation.
✅ Correctness verification report:
🌀 Generated Regression Tests and Runtime
To edit these changes
git checkout codeflash/optimize-set_custom_labels-mgzf1xtaand push.