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@codeflash-ai codeflash-ai bot commented Jan 30, 2026

📄 17% (0.17x) speedup for bit_insert in aerospike_helpers/operations/bitwise_operations.py

⏱️ Runtime : 14.7 microseconds 12.5 microseconds (best of 5 runs)

📝 Explanation and details

The optimization achieves a 17% runtime improvement (from 14.7μs to 12.5μs) by caching the aerospike.OP_BIT_INSERT constant as a module-level variable _OP_BIT_INSERT.

What changed:
A single line was added at module scope: _OP_BIT_INSERT = aerospike.OP_BIT_INSERT, and the function now references this cached value instead of performing the attribute lookup each time.

Why this is faster:
In Python, attribute access like aerospike.OP_BIT_INSERT requires:

  1. Looking up the aerospike name in the global namespace
  2. Performing an attribute lookup on the module object to retrieve OP_BIT_INSERT

By caching this constant at module load time, the function only needs a single LOAD_GLOBAL operation instead of LOAD_GLOBAL + LOAD_ATTR on every invocation. The line profiler shows this improvement clearly: the line with the OP_KEY assignment dropped from 16,253ns to 14,752ns (~9% faster for that line alone).

Impact:
This optimization benefits any workload that calls bit_insert repeatedly, as the per-call overhead is reduced. Since this function creates operation dictionaries that are likely used in batch operations or loops when working with Aerospike's bitwise operations, the cumulative savings can be significant. The 17% speedup compounds when the function is called thousands of times in typical database operation scenarios.

The optimization is purely mechanical with no behavioral changes—the same constant value is used, just accessed more efficiently.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 139 Passed
🌀 Generated Regression Tests 🔘 None Found
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
⚙️ Click to see Existing Unit Tests
Test File::Test Function Original ⏱️ Optimized ⏱️ Speedup
test_bitwise_operations.py::TestBitwiseOperations.test_bit_insert 1.92μs 1.59μs 20.5%✅
test_bitwise_operations.py::TestBitwiseOperations.test_bit_insert_bad_arg_type 1.76μs 1.59μs 11.0%✅
test_bitwise_operations.py::TestBitwiseOperations.test_bit_insert_multiple_bytes 1.90μs 1.66μs 14.8%✅
test_bitwise_operations.py::TestBitwiseOperations.test_bit_insert_multiple_bytes_with_offset 1.83μs 1.52μs 20.3%✅
test_bitwise_operations.py::TestBitwiseOperations.test_bit_insert_nonexistent_bin_name 1.80μs 1.57μs 14.8%✅
test_bitwise_operations.py::TestBitwiseOperations.test_bit_insert_offset_out_of_range 1.89μs 1.58μs 19.8%✅
test_bitwise_operations.py::TestBitwiseOperations.test_bit_insert_value_byte_size_smaller_than_value 1.80μs 1.51μs 19.1%✅
test_bitwise_operations.py::TestBitwiseOperations.test_bit_insert_value_byte_size_too_large 1.80μs 1.52μs 18.3%✅

To edit these changes git checkout codeflash/optimize-bit_insert-ml0jidhf and push.

Codeflash Static Badge

The optimization achieves a **17% runtime improvement** (from 14.7μs to 12.5μs) by caching the `aerospike.OP_BIT_INSERT` constant as a module-level variable `_OP_BIT_INSERT`.

**What changed:**
A single line was added at module scope: `_OP_BIT_INSERT = aerospike.OP_BIT_INSERT`, and the function now references this cached value instead of performing the attribute lookup each time.

**Why this is faster:**
In Python, attribute access like `aerospike.OP_BIT_INSERT` requires:
1. Looking up the `aerospike` name in the global namespace
2. Performing an attribute lookup on the module object to retrieve `OP_BIT_INSERT`

By caching this constant at module load time, the function only needs a single LOAD_GLOBAL operation instead of LOAD_GLOBAL + LOAD_ATTR on every invocation. The line profiler shows this improvement clearly: the line with the OP_KEY assignment dropped from 16,253ns to 14,752ns (~9% faster for that line alone).

**Impact:**
This optimization benefits any workload that calls `bit_insert` repeatedly, as the per-call overhead is reduced. Since this function creates operation dictionaries that are likely used in batch operations or loops when working with Aerospike's bitwise operations, the cumulative savings can be significant. The 17% speedup compounds when the function is called thousands of times in typical database operation scenarios.

The optimization is purely mechanical with no behavioral changes—the same constant value is used, just accessed more efficiently.
@codeflash-ai codeflash-ai bot requested a review from aseembits93 January 30, 2026 07:06
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: Medium Optimization Quality according to Codeflash labels Jan 30, 2026
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