⚡️ Speed up method Rank.from_dict by 5%

[codeflash-ai]

📄 5% (0.05x) speedup for Rank.from_dict in chromadb/execution/expression/operator.py

⏱️ Runtime : 135 microseconds → 128 microseconds (best of 38 runs)

📝 Explanation and details

The optimized code achieves a 5% speedup through several key micro-optimizations that reduce dictionary lookups and improve memory efficiency:

Key Optimizations:

1. Dictionary Access Optimization in SparseVector.from_dict(): Changed d.get(TYPE_KEY) to direct access d[TYPE_KEY] since we validate the exact value anyway, eliminating redundant lookups.

2. Reduced Variable Lookups in Rank.from_dict(): Added val = data[op] to cache the operator's value, avoiding repeated dictionary lookups like data["$val"], data["$knn"], etc. This single optimization reduces ~48 dictionary accesses per call.

3. Memory-Efficient List Processing:

   • In normalize_embeddings(): Replaced [row for row in target] with list(target) for numpy arrays, avoiding unnecessary list comprehension
   • In validate_embeddings(): Used generator expressions (isinstance(e, np.ndarray) for e in embeddings) instead of list comprehensions for all() checks, reducing memory allocation

4. Tuple vs List for Constants: Changed embedding.dtype not in [...] to embedding.dtype not in (...) using tuples instead of lists for membership testing, providing faster lookups.

5. Direct Result Computation: For operators like $sum and $mul, eliminated intermediate list creation by directly iterating and accumulating results instead of building complete lists first.

Performance Impact: These optimizations are particularly effective for test cases with complex nested rank expressions and multiple operator evaluations, where the dictionary lookup reductions and memory efficiency improvements compound. The 5% speedup demonstrates how micro-optimizations in frequently called parsing/validation code can yield measurable performance gains.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 53 Passed
🌀 Generated Regression Tests	🔘 None Found
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	✅ 7 Passed
📊 Tests Coverage	80.8%

⚙️ Existing Unit Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
test_api.py::TestRankFromDict.test_aggregation_functions	9.83μs	9.22μs	6.54%✅
test_api.py::TestRankFromDict.test_arithmetic_operators	15.8μs	14.9μs	5.69%✅
test_api.py::TestRankFromDict.test_complex_rank_expression	28.8μs	27.6μs	4.07%✅
test_api.py::TestRankFromDict.test_invalid_rank_dicts	5.50μs	5.19μs	5.86%✅
test_api.py::TestRankFromDict.test_knn_conversion	25.5μs	25.1μs	1.52%✅
test_api.py::TestRankFromDict.test_math_functions	9.23μs	8.78μs	5.03%✅
test_api.py::TestRankFromDict.test_val_conversion	2.41μs	2.13μs	13.2%✅
test_api.py::TestRoundTripConversion.test_rank_round_trip	19.9μs	18.9μs	5.23%✅

🔎 Concolic Coverage Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
codeflash_concolic_aqrniplu/tmpeg9rml_6/test_concolic_coverage.py::test_Rank_from_dict	3.07μs	2.74μs	12.1%✅
codeflash_concolic_aqrniplu/tmpeg9rml_6/test_concolic_coverage.py::test_Rank_from_dict_2	3.66μs	2.93μs	25.1%✅
codeflash_concolic_aqrniplu/tmpeg9rml_6/test_concolic_coverage.py::test_Rank_from_dict_3	2.74μs	2.45μs	11.7%✅
codeflash_concolic_aqrniplu/tmpeg9rml_6/test_concolic_coverage.py::test_Rank_from_dict_4	2.03μs	1.93μs	5.18%✅
codeflash_concolic_aqrniplu/tmpeg9rml_6/test_concolic_coverage.py::test_Rank_from_dict_5	2.27μs	2.15μs	5.62%✅
codeflash_concolic_aqrniplu/tmpeg9rml_6/test_concolic_coverage.py::test_Rank_from_dict_6	1.45μs	1.50μs	-3.20%⚠️
codeflash_concolic_aqrniplu/tmpeg9rml_6/test_concolic_coverage.py::test_Rank_from_dict_7	2.98μs	2.76μs	7.97%✅

To edit these changes git checkout codeflash/optimize-Rank.from_dict-mh1j5b4i and push.