Skill: michealxie001/openclaw-perf (version 1.0.0)

--- name: performance description: Performance analysis and optimization. Profiles code execution, identifies bottlenecks, and suggests optimizations. --- # Performance - Performance Analysis 性能分析工具，分析代码执行、识别瓶颈、提供优化建议。 **Version**: 1.0 **Features**: 性能分析、瓶颈识别、优化建议、基准测试 --- ## Quick Start ### 1. 分析 Python 代码 ```bash # 分析函数执行时间 python3 scripts/main.py profile --file src/main.py --function process_data # 分析整个模块 python3 scripts/main.py profile --file src/main.py ``` ### 2. 识别瓶颈 ```bash # 扫描代码中的性能问题 python3 scripts/main.py analyze --file src/main.py # 分析目录 python3 scripts/main.py analyze --dir src/ ``` ### 3. 基准测试 ```bash # 运行基准测试 python3 scripts/main.py benchmark --file src/main.py --function heavy_computation ``` --- ## Commands | 命令 | 说明 | 示例 | |------|------|------| | `profile` | 性能分析 | `profile --file src.py` | | `analyze` | 瓶颈分析 | `analyze --file src.py` | | `benchmark` | 基准测试 | `benchmark --function foo` | --- ## Profile 输出 ```bash $ python3 scripts/main.py profile --file src/processor.py --function process_data 🔍 Performance Profile ====================== Function: process_data File: src/processor.py:45 Calls: 100 Total time: 2.34s Avg time: 23.4ms Top hotspots: 45% - database.query() (line 67) 30% - json.dumps() (line 89) 15% - data transformation (line 78) 10% - other Recommendations: ⚠️ Consider caching database results ⚠️ Use orjson instead of json for better performance ``` --- ## 瓶颈分析 ```bash $ python3 scripts/main.py analyze --file src/api.py 🔍 Performance Analysis ======================= File: src/api.py Issues found: 3 🔴 High Impact: Line 34: Nested loop O(n²) for user in users: for order in orders: # ← N+1 query pattern Suggestion: Use JOIN query instead 🟡 Medium Impact: Line 67: String concatenation in loop result += item # ← Use list + join instead 🟢 Low Impact: Line 89: Unused import import heavy_module # ← Remove if not used ``` --- ## 基准测试 ```bash $ python3 scripts/main.py benchmark --file src/sort.py --function quicksort ⏱️ Benchmark Results ==================== Function: quicksort Iterations: 1000 Time (ms): Mean: 12.34 Median: 11.89 Min: 8.45 Max: 45.67 P95: 18.90 P99: 32.10 Memory (MB): Mean: 2.45 Peak: 4.12 Comparison: vs bubble sort: 45x faster vs merge sort: 1.2x faster ``` --- ## 检测的优化模式 ### 代码层面 | 问题 | 检测 | 建议 | |------|------|------| | N+1 查询 | ✅ | 使用 JOIN / select_related | | 循环内字符串拼接 | ✅ | 使用 list + join | | 未使用的导入 | ✅ | 移除导入 | | 嵌套循环 | ✅ | 优化算法或使用哈希 | | 重复计算 | ✅ | 缓存结果 | ### Python 特定 | 问题 | 检测 | 建议 | |------|------|------| | list vs generator | ✅ | 大数据用 generator | | dict.get() vs [] | ✅ | 使用 .get() 避免 KeyError | | 列表推导式 | ✅ | 替代 map/filter | --- ## Configuration `.performance.json`: ```json { "benchmark_iterations": 1000, "warmup_iterations": 10, "profile_lines": true, "check_patterns": [ "n_plus_one", "string_concat_in_loop", "unused_imports" ] } ``` --- ## CI/CD 集成 ```yaml # .github/workflows/performance.yml name: Performance Check on: [pull_request] jobs: perf: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - name: Analyze Performance run: python3 skills/performance/scripts/main.py analyze --dir src/ - name: Run Benchmarks run: python3 skills/performance/scripts/main.py benchmark --all ``` --- ## Files ``` skills/performance/ ├── SKILL.md # 本文件 └── scripts/ ├── main.py # ⭐ 统一入口 ├── profiler.py # 性能分析器 └── analyzer.py # 瓶颈分析器 ``` --- ## Roadmap - [x] Basic profiling - [x] Bottleneck detection - [x] Benchmark runner - [ ] Memory profiling - [ ] Flame graph generation


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