张翔
159 lines
6.0 KiB
Python
159 lines
6.0 KiB
Python
#!/usr/bin/env python3
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"""
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Woodpecker CI 最佳实践对比分析
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对比当前配置与 Woodpecker CI 官方最佳实践
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"""
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import yaml
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from pathlib import Path
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class BestPracticeAnalyzer:
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"""最佳实践分析器"""
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def __init__(self, config_path: str):
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self.config_path = Path(config_path)
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with open(self.config_path, 'r', encoding='utf-8') as f:
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self.config = yaml.safe_load(f)
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self.best_practices = {
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"分支策略": {
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"✅ 使用通配符": "支持 feature/**, release/** 等通配符",
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"✅ 分层触发": "不同分支触发不同深度的测试",
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"✅ 保护主分支": "main 分支只接收自动归档",
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"⚠️ 缺少分支保护": "建议在 Git 仓库设置分支保护规则"
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},
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"测试策略": {
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"✅ 分层测试": "feature(dev/smoke) < dev(standard) < release(full)",
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"✅ 快速反馈": "feature 分支使用 smoke test 快速验证",
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"✅ 质量门禁": "测试失败阻止合并/部署",
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"✅ 覆盖率检查": "单元测试包含覆盖率检查"
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},
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"部署安全": {
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"✅ 健康检查": "部署后执行健康检查",
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"✅ 自动回滚": "健康检查失败自动回滚",
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"✅ 备份机制": "部署前备份当前版本",
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"✅ Secret 管理": "使用 Secret 管理敏感信息",
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"✅ SSH 密钥": "使用 SSH 密钥进行 Git 操作"
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},
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"Docker 构建": {
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"✅ 镜像标签": "使用 commit SHA 和 latest 标签",
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"✅ Docker socket": "挂载 Docker socket",
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"✅ 镜像推送": "推送到私有仓库",
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"⚠️ 缺少镜像扫描": "建议添加容器安全扫描"
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},
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"归档策略": {
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"✅ 自动归档": "部署成功后自动归档到 main",
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"✅ 版本标签": "创建带时间戳的版本标签",
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"✅ 动态分支": "支持任意 release/** 分支归档",
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"✅ 重试机制": "推送失败自动重试 3 次"
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},
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"性能优化": {
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"⚠️ 缺少缓存": "建议添加 npm 依赖缓存",
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"⚠️ 缺少并行": "部分步骤可以并行执行",
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"✅ 浅克隆": "使用 depth: 1 减少克隆时间"
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},
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"通知与监控": {
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"⚠️ 缺少通知": "建议添加企业微信/钉钉通知",
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"⚠️ 缺少监控": "建议集成 APM 监控",
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"✅ 日志输出": "每个步骤都有清晰的日志"
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},
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"配置管理": {
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"✅ YAML 锚点": "使用锚点复用配置",
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"✅ 环境变量": "使用环境变量传递配置",
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"✅ 注释清晰": "配置文件有详细的注释",
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"✅ 结构清晰": "按阶段组织步骤"
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}
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}
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def analyze(self):
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"""执行分析"""
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print("\n" + "="*70)
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print("Woodpecker CI 最佳实践对比分析")
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print("="*70)
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for category, practices in self.best_practices.items():
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print(f"\n📋 {category}")
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print("-" * 70)
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for practice, description in practices.items():
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status = practice.split()[0]
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desc = description
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if status == "✅":
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print(f" {practice}")
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print(f" └─ {desc}")
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elif status == "⚠️":
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print(f" {practice}")
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print(f" └─ {desc}")
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elif status == "❌":
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print(f" {practice}")
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print(f" └─ {desc}")
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print("\n" + "="*70)
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print("改进建议优先级")
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print("="*70)
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recommendations = [
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("高优先级", [
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"添加 npm 依赖缓存，减少构建时间",
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"配置 Git 分支保护规则",
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"添加部署通知机制"
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]),
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("中优先级", [
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"添加容器镜像安全扫描",
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"集成 APM 性能监控",
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"优化并行执行策略"
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]),
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("低优先级", [
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"添加代码质量门禁（如 SonarQube）",
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"实现蓝绿部署",
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"添加多环境支持（staging）"
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])
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]
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for priority, items in recommendations:
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print(f"\n🎯 {priority}")
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for i, item in enumerate(items, 1):
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print(f" {i}. {item}")
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print("\n" + "="*70)
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print("总体评分")
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print("="*70)
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total_practices = sum(len(practices) for practices in self.best_practices.values())
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passed_practices = sum(
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1 for practices in self.best_practices.values()
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for practice in practices.keys()
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if practice.startswith("✅")
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)
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warning_practices = sum(
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1 for practices in self.best_practices.values()
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for practice in practices.keys()
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if practice.startswith("⚠️")
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)
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score = (passed_practices / total_practices) * 100
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print(f"\n✅ 符合最佳实践: {passed_practices}/{total_practices}")
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print(f"⚠️ 需要改进: {warning_practices}/{total_practices}")
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print(f"📊 总体评分: {score:.1f}/100")
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if score >= 80:
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print("✅ 配置质量优秀")
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elif score >= 60:
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print("⚠️ 配置质量良好，但有改进空间")
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else:
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print("❌ 配置需要重大改进")
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print("\n" + "="*70)
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def main():
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analyzer = BestPracticeAnalyzer(".woodpecker.yml")
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analyzer.analyze()
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if __name__ == "__main__":
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main()
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