Files
assist/.claude/skills/http-error-analyzer/scripts/analyze_http_errors.py
zhaojie 0bee1c86fc feat: 新增 AI 指标报告助手与配置健康检查功能
- 新增 `ai-metrics-report` 技能,自动生成 AI 成功率、错误率与 Token 成本的综合报告,帮助评估智能助手表现。
- 新增 `config-audit` 技能,检查当前环境配置的完整性与可用性,输出健康检查报告,确保系统稳定运行。
- 相关脚本已实现,支持从项目根目录执行并输出结构化结果。
2026-02-11 00:59:55 +08:00

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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
HTTP 错误日志分析脚本
扫描 logs/*/dashboard.log统计常见 4xx/5xx HTTP 状态码(如 404/500
并输出按状态码分组的出现次数与若干示例行,供 http-error-analyzer Skill 使用。
"""
import os
import re
from pathlib import Path
from typing import Dict, List, Tuple
LOG_ROOT = Path("logs")
LOG_FILENAME = "dashboard.log"
MAX_FILES = 5 # 最多分析最近 N 个日志文件
# 简单匹配常见 HTTP 错误码;根据你实际日志格式可以再调整
ERROR_CODES = [404, 500, 502, 503]
CODE_PATTERNS: Dict[int, re.Pattern] = {
code: re.compile(rf"\b{code}\b") for code in ERROR_CODES
}
def find_log_files() -> List[Path]:
if not LOG_ROOT.exists():
return []
candidates: List[Tuple[float, Path]] = []
for root, dirs, files in os.walk(LOG_ROOT):
if LOG_FILENAME in files:
p = Path(root) / LOG_FILENAME
try:
mtime = p.stat().st_mtime
except OSError:
continue
candidates.append((mtime, p))
candidates.sort(key=lambda x: x[0], reverse=True)
return [p for _, p in candidates[:MAX_FILES]]
def analyze_file(path: Path):
"""
返回:
counts: {status_code: 次数}
samples: {status_code: [示例行1, 示例行2, ...]}
"""
counts: Dict[int, int] = {code: 0 for code in ERROR_CODES}
samples: Dict[int, List[str]] = {code: [] for code in ERROR_CODES}
try:
with path.open("r", encoding="utf-8", errors="ignore") as f:
for line in f:
for code, pattern in CODE_PATTERNS.items():
if pattern.search(line):
counts[code] += 1
# 只收集每个状态码前若干条示例
if len(samples[code]) < 5:
samples[code].append(line.strip()[:300])
break
except OSError as e:
print(f"[!] 读取日志失败 {path}: {e}")
return None
return counts, samples
def main():
log_files = find_log_files()
if not log_files:
print("未找到任何日志文件logs/*/dashboard.log")
return
overall_counts: Dict[int, int] = {code: 0 for code in ERROR_CODES}
overall_samples: Dict[int, List[str]] = {code: [] for code in ERROR_CODES}
print(f"=== HTTP 错误日志分析(最近最多 {MAX_FILES} 个日志文件)===\n")
for idx, path in enumerate(log_files, start=1):
print(f"[{idx}] 日志文件: {path}")
result = analyze_file(path)
if result is None:
print(" 无法读取该日志文件。\n")
continue
counts, samples = result
any_error = any(counts[code] > 0 for code in ERROR_CODES)
if not any_error:
print(" 未发现 404/500/502/503 等 HTTP 错误。")
print()
continue
for code in ERROR_CODES:
c = counts[code]
if c == 0:
continue
overall_counts[code] += c
overall_samples[code].extend(samples[code])
print(f" 状态码 {code}: {c}")
if samples[code]:
print(" 示例:")
for line in samples[code]:
print(f" {line}")
print()
print("=== 汇总统计 ===")
any_overall = any(overall_counts[code] > 0 for code in ERROR_CODES)
if not any_overall:
print(" 未在最近的日志文件中发现任何配置的 HTTP 错误状态码。")
return
for code in ERROR_CODES:
c = overall_counts[code]
if c == 0:
continue
print(f" 状态码 {code}: {c}")
print("\n提示:以上为按状态码汇总的次数与部分示例行,")
print("你可以结合 URL 路径、接口名称、堆栈片段来推断可能的路由配置问题、权限问题或后端异常。")
if __name__ == "__main__":
main()