⚡️ Speed up method _PreChunkAccumulator.will_fit by 38%
#55
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📄 38% (0.38x) speedup for
_PreChunkAccumulator.will_fitinunstructured/chunking/base.py⏱️ Runtime :
458 nanoseconds→333 nanoseconds(best of38runs)📝 Explanation and details
The optimization replaces an expensive string materialization operation with a direct length calculation method.
Key Change: The original code calls
len(self.combine(pre_chunk)._text)which creates a full combined text string just to measure its length. The optimized version introduces_combined_text_length()that calculates the same length without building the actual string.Why It's Faster: String concatenation and materialization in Python is expensive, especially for larger text chunks. The new method:
Performance Impact: The line profiler shows the critical line in
can_combinedropped from 173,000ns to 100,000ns (42% improvement), contributing to the overall 37% speedup. This optimization is particularly effective for:Behavioral Preservation: The optimization maintains identical logic and return values - it's purely an implementation efficiency gain without changing the chunking behavior or API contract.
This type of optimization is especially valuable in text processing pipelines where chunking operations may be called thousands of times on large documents.
✅ Correctness verification report:
⚙️ Existing Unit Tests and Runtime
🔎 Concolic Coverage Tests and Runtime
codeflash_concolic_e8goshnj/tmpayrn317z/test_concolic_coverage.py::test__PreChunkAccumulator_will_fitTo edit these changes
git checkout codeflash/optimize-_PreChunkAccumulator.will_fit-mjdrcu8sand push.