⚡️ Speed up method S3VectorsConfig.validate_extra_fields by 72%
#24
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📄 72% (0.72x) speedup for
S3VectorsConfig.validate_extra_fieldsinmem0/configs/vector_stores/s3_vectors.py⏱️ Runtime :
9.15 microseconds→5.33 microseconds(best of50runs)📝 Explanation and details
The optimized code achieves a 71% speedup through class-level caching of allowed fields. The key optimization is storing
cls.model_fields.keys()in_allowed_fields_cacheon first access, eliminating repeated computation of the same field names on every validation call.Key Changes:
hasattr()check to cache allowed fields as a tuple in_allowed_fields_cache, computed only once per classset(values) - set(allowed_fields)for extra field detectionWhy This Works:
In Pydantic model validation,
cls.model_fields.keys()accesses the class's field registry every time. For a BaseModel with fixed fields like S3VectorsConfig (5 fields: vector_bucket_name, collection_name, etc.), this is pure overhead. The tuple cache eliminates dictionary attribute access and key extraction on repeated calls, while set conversion for the difference operation remains fast for small field counts.Performance Context:
This optimization is particularly valuable for configuration classes that undergo frequent validation, such as during object initialization or parameter validation in data processing pipelines. The 71% improvement (9.15μs → 5.33μs) compounds significantly when validation occurs in loops or high-frequency operations.
✅ Correctness verification report:
⏪ Replay Tests and Runtime
test_pytest_testsconfigstest_prompts_py_testsvector_storestest_weaviate_py_testsllmstest_deepseek_py_test__replay_test_0.py::test_mem0_configs_vector_stores_s3_vectors_S3VectorsConfig_validate_extra_fieldsTo edit these changes
git checkout codeflash/optimize-S3VectorsConfig.validate_extra_fields-mhln1zo8and push.