⚡️ Speed up function get_java_runtime_setup_steps by 20% in PR #1199 (omni-java)#1239
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codeflash-ai[bot] wants to merge 1 commit intoomni-javafrom
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⚡️ Speed up function get_java_runtime_setup_steps by 20% in PR #1199 (omni-java)#1239codeflash-ai[bot] wants to merge 1 commit intoomni-javafrom
get_java_runtime_setup_steps by 20% in PR #1199 (omni-java)#1239codeflash-ai[bot] wants to merge 1 commit intoomni-javafrom
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This optimization achieves a **20% runtime improvement** (531μs → 441μs) by replacing conditional string concatenation with a precomputed dictionary lookup. **What changed:** - The original code builds strings dynamically on every function call, performing string concatenation operations based on conditional checks - The optimized version precomputes all possible string outputs once at module load time and stores them in a dictionary (`_JAVA_SETUP_MAP`) - The function now performs a simple O(1) dictionary lookup instead of executing string operations **Why it's faster:** 1. **Eliminates repeated string operations**: String concatenation in Python creates new string objects. The original code performs this work on every call, while the optimized version does it once at module initialization 2. **Reduces conditional branching**: The original code evaluates two conditional branches per call. The optimized version performs a single dictionary lookup, which is highly optimized in Python's C implementation 3. **Better CPU cache utilization**: Precomputed strings stored in memory are more likely to remain in CPU cache across multiple function calls **Performance characteristics by test case:** - **Single calls**: Show mixed results (some 3-15% slower per individual call) due to dictionary lookup overhead, but the overall benchmark shows 20% improvement - **Repeated calls (500 iterations)**: Show strong gains of 17-27% faster, where the optimization truly shines. This is where the elimination of repeated string operations matters most - **Subsequent calls**: Tests with multiple consecutive calls (result1, result2, result3) show increasing speedup on later calls (up to 25% faster), indicating better memory access patterns **Impact on workloads:** This function generates GitHub Actions workflow configuration. The optimization is most beneficial when: - The function is called multiple times during workflow generation (common in CI/CD setup scenarios) - Build configurations are generated in batch operations - The same build tool type is queried repeatedly The trade-off of slightly slower individual first-time calls is more than compensated by the significant gains in repeated execution scenarios, making this a net-positive optimization for typical usage patterns where configuration generation happens in batches or loops.
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⚡️ This pull request contains optimizations for PR #1199
If you approve this dependent PR, these changes will be merged into the original PR branch
omni-java.📄 20% (0.20x) speedup for
get_java_runtime_setup_stepsincodeflash/cli_cmds/init_java.py⏱️ Runtime :
531 microseconds→441 microseconds(best of203runs)📝 Explanation and details
This optimization achieves a 20% runtime improvement (531μs → 441μs) by replacing conditional string concatenation with a precomputed dictionary lookup.
What changed:
_JAVA_SETUP_MAP)Why it's faster:
Performance characteristics by test case:
Impact on workloads:
This function generates GitHub Actions workflow configuration. The optimization is most beneficial when:
The trade-off of slightly slower individual first-time calls is more than compensated by the significant gains in repeated execution scenarios, making this a net-positive optimization for typical usage patterns where configuration generation happens in batches or loops.
✅ Correctness verification report:
🌀 Click to see Generated Regression Tests
To edit these changes
git checkout codeflash/optimize-pr1199-2026-02-01T21.47.41and push.