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Performance analysis and bottleneck detection tool
安装命令
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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 开始
1. 分析 Python 代码
# 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
# 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
# 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 |
个人资料 输出
$ 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
$ 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
$ 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:
{
"benchmark_iterations": 1000,
"warmup_iterations": 10,
"profile_lines": true,
"check_patterns": [
"n_plus_one",
"string_concat_in_loop",
"unused_imports"
]
}
CI/CD 集成
# .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 图形 generation