feat: 添加 Woodpecker CI 本地测试工具
ci/woodpecker/push/woodpecker Pipeline failed

- validate-woodpecker.sh: 全面验证配置文件
- test-step.sh: 单步测试工具,支持 Docker 隔离环境
- README.md: 详细使用文档和最佳实践

这些工具可以在本地验证和测试 CI/CD 配置,避免通过持续提交来测试
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张翔
2026-03-28 22:24:46 +08:00
parent d1e23cf519
commit 6797a1ee2d
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#!/bin/bash
set -e
WOODPECKER_FILE=".woodpecker.yml"
# 颜色定义
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m' # No Color
print_header() {
echo ""
echo -e "${BLUE}==========================================${NC}"
echo -e "${BLUE}$1${NC}"
echo -e "${BLUE}==========================================${NC}"
echo ""
}
print_success() {
echo -e "${GREEN}$1${NC}"
}
print_error() {
echo -e "${RED}$1${NC}"
}
print_warning() {
echo -e "${YELLOW}⚠️ $1${NC}"
}
print_info() {
echo -e "${BLUE}$1${NC}"
}
# 检查是否提供了步骤名称
if [ -z "$1" ]; then
print_header "Woodpecker CI 单步测试工具"
echo "用法: $0 <step_name> [--dry-run]"
echo ""
echo "示例:"
echo " $0 notify-wechat-success --dry-run # 仅显示命令,不执行"
echo " $0 lint # 执行 lint 步骤"
echo ""
echo "可用的步骤:"
python3 << 'PYTHON_SCRIPT'
import yaml
with open('.woodpecker.yml', 'r') as f:
config = yaml.safe_load(f)
steps = config.get('steps', {})
for i, (step_name, step_config) in enumerate(steps.items(), 1):
image = step_config.get('image', 'N/A')
print(f" {i}. {step_name:<25} (镜像: {image})")
PYTHON_SCRIPT
exit 1
fi
STEP_NAME="$1"
DRY_RUN="${2:-}"
print_header "测试步骤: $STEP_NAME"
# 检查步骤是否存在
STEP_EXISTS=$(python3 << PYTHON_SCRIPT
import yaml
import sys
with open('.woodpecker.yml', 'r') as f:
config = yaml.safe_load(f)
steps = config.get('steps', {})
step_name = "$STEP_NAME"
if step_name in steps:
print("yes")
else:
print("no")
PYTHON_SCRIPT
)
if [ "$STEP_EXISTS" != "yes" ]; then
print_error "步骤 '$STEP_NAME' 不存在"
exit 1
fi
print_success "步骤 '$STEP_NAME' 存在"
# 获取步骤配置
python3 << PYTHON_SCRIPT
import yaml
import json
import sys
with open('.woodpecker.yml', 'r') as f:
config = yaml.safe_load(f)
step_name = "$STEP_NAME"
step_config = config['steps'][step_name]
print(f"\n📦 镜像: {step_config.get('image', 'N/A')}")
# 显示环境变量
env = step_config.get('environment', {})
if env:
print("\n🔐 环境变量:")
for key, value in env.items():
if isinstance(value, dict) and 'from_secret' in value:
print(f" - {key}: from_secret:{value['from_secret']}")
else:
print(f" - {key}: {value}")
# 显示 when 条件
when = step_config.get('when', {})
if when:
print("\n📋 执行条件:")
if 'branch' in when:
branches = when['branch']
if isinstance(branches, list):
print(f" - 分支: {', '.join(branches)}")
else:
print(f" - 分支: {branches}")
if 'event' in when:
events = when['event']
if isinstance(events, list):
print(f" - 事件: {', '.join(events)}")
else:
print(f" - 事件: {events}")
if 'status' in when:
statuses = when['status']
if isinstance(statuses, list):
print(f" - 状态: {', '.join(statuses)}")
else:
print(f" - 状态: {statuses}")
# 显示命令
commands = step_config.get('commands', [])
if commands:
print("\n📝 命令:")
for i, cmd in enumerate(commands, 1):
# 显示前100个字符
if len(cmd) > 100:
print(f" {i}. {cmd[:100]}...")
else:
print(f" {i}. {cmd}")
# 输出 JSON 配置(用于后续处理)
print("\n" + json.dumps(step_config))
PYTHON_SCRIPT
# 如果是 dry-run 模式,只显示信息,不执行
if [ "$DRY_RUN" = "--dry-run" ]; then
print_info "Dry-run 模式,不执行命令"
exit 0
fi
# 询问是否继续执行
echo ""
read -p "是否继续执行此步骤?(y/N) " -n 1 -r
echo ""
if [[ ! $REPLY =~ ^[Yy]$ ]]; then
print_info "已取消执行"
exit 0
fi
# 执行步骤
print_header "执行步骤"
# 获取镜像
IMAGE=$(python3 << PYTHON_SCRIPT
import yaml
with open('.woodpecker.yml', 'r') as f:
config = yaml.safe_load(f)
step_name = "$STEP_NAME"
print(config['steps'][step_name].get('image', ''))
PYTHON_SCRIPT
)
if [ -z "$IMAGE" ]; then
print_error "无法获取镜像信息"
exit 1
fi
print_info "使用镜像: $IMAGE"
# 拉取镜像
print_info "拉取镜像..."
docker pull "$IMAGE" || {
print_warning "镜像拉取失败,尝试使用本地镜像"
}
# 获取命令
COMMANDS=$(python3 << 'PYTHON_SCRIPT'
import yaml
import json
with open('.woodpecker.yml', 'r') as f:
config = yaml.safe_load(f)
step_name = "$STEP_NAME"
commands = config['steps'][step_name].get('commands', [])
# 将命令转换为 JSON 字符串
print(json.dumps(commands))
PYTHON_SCRIPT
)
# 执行命令
print_info "执行命令..."
# 创建临时脚本
TEMP_SCRIPT=$(mktemp)
trap "rm -f $TEMP_SCRIPT" EXIT
# 写入命令
python3 << PYTHON_SCRIPT > "$TEMP_SCRIPT"
import yaml
import json
with open('.woodpecker.yml', 'r') as f:
config = yaml.safe_load(f)
step_name = "$STEP_NAME"
commands = config['steps'][step_name].get('commands', [])
for cmd in commands:
print(cmd)
PYTHON_SCRIPT
chmod +x "$TEMP_SCRIPT"
# 设置环境变量(模拟 Woodpecker CI
export CI="true"
export CI_COMMIT_BRANCH="${CI_COMMIT_BRANCH:-release/v1.0.0}"
export CI_COMMIT_SHA="${CI_COMMIT_SHA:-$(git rev-parse HEAD 2>/dev/null || echo 'abc123def456')}"
export CI_COMMIT_MESSAGE="${CI_COMMIT_MESSAGE:-$(git log -1 --pretty=%B 2>/dev/null || echo 'Test commit')}"
export CI_COMMIT_AUTHOR="${CI_COMMIT_AUTHOR:-$(git log -1 --pretty=%an 2>/dev/null || echo 'Test Author')}"
export CI_PIPELINE_NUMBER="${CI_PIPELINE_NUMBER:-999}"
export CI_REPO_ID="${CI_REPO_ID:-1}"
print_info "环境变量:"
echo " CI_COMMIT_BRANCH: $CI_COMMIT_BRANCH"
echo " CI_COMMIT_SHA: $CI_COMMIT_SHA"
echo " CI_COMMIT_MESSAGE: $CI_COMMIT_MESSAGE"
echo " CI_COMMIT_AUTHOR: $CI_COMMIT_AUTHOR"
echo " CI_PIPELINE_NUMBER: $CI_PIPELINE_NUMBER"
echo ""
# 使用 Docker 执行
docker run --rm \
-v "$(pwd):/woodpecker/src" \
-w /woodpecker/src \
-e CI \
-e CI_COMMIT_BRANCH \
-e CI_COMMIT_SHA \
-e CI_COMMIT_MESSAGE \
-e CI_COMMIT_AUTHOR \
-e CI_PIPELINE_NUMBER \
-e CI_REPO_ID \
"$IMAGE" \
sh -c "$(cat "$TEMP_SCRIPT")"
if [ $? -eq 0 ]; then
print_success "步骤执行成功"
else
print_error "步骤执行失败"
exit 1
fi