- 引入 CaseEntity 包装器,实现数据模型与执行上下文解耦。 - 移除加载阶段的 deepcopy,优化大规模参数化用例的内存占用。 - 实现 perform 阶段的局部变量注入,确保参数化数据优先级高于全局缓存。
91 lines
2.7 KiB
Python
91 lines
2.7 KiB
Python
import shutil
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import datetime
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from pathlib import Path
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import pytest
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from core.settings import LOG_SOURCE, LOG_BACKUP_DIR, ALLURE_TEMP
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# from core.enums import AppPlatform
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from utils.dirs_manager import ensure_dirs_ok
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from utils.report_handler import generate_allure_report
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# netstat -ano | findstr :4723
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# taskkill /PID 12345 /F
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def _archive_logs():
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"""
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在测试开始前,归档上一次运行的日志文件。
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此时没有任何句柄占用,move 操作是 100% 安全的。
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"""
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# 4. 备份日志 (无论测试是否崩溃都执行)
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if LOG_SOURCE.exists() and LOG_SOURCE.stat().st_size > 0:
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now = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')
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backup_path = LOG_BACKUP_DIR / f"pytest_{now}.log"
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try:
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# 移动并重命名
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shutil.move(str(LOG_SOURCE), str(backup_path))
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print(f"已自动归档上次运行的日志: {backup_path}")
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# shutil.copy2(LOG_SOURCE, backup_path)
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# print(f"日志已备份至: {backup_path}")
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_clean_old_logs(LOG_BACKUP_DIR)
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except Exception as e:
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print(f"归档旧日志失败 (可能被外部编辑器打开): {e}")
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else:
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print("未找到原始日志文件,跳过备份。")
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# 日志清理
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def _clean_old_logs(backup_dir, keep_count=10):
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files = sorted(Path(backup_dir).glob("pytest_*.log"), key=lambda p: p.stat().st_mtime)
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while len(files) > keep_count:
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file_to_remove = files.pop(0)
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try:
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file_to_remove.unlink(missing_ok=True)
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except OSError as e:
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print(f"清理旧日志失败 {file_to_remove}: {e}")
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def _clean_temp_dirs():
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"""
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可选:如果你想在测试前清理掉旧的临时文件
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"""
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if ALLURE_TEMP.exists():
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shutil.rmtree(ALLURE_TEMP)
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# 加上 ignore_errors 是为了防止文件被占用导致整个测试无法启动
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shutil.rmtree(ALLURE_TEMP, ignore_errors=True)
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ALLURE_TEMP.mkdir(parents=True, exist_ok=True)
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def main():
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try:
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# 1. 创建目录
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ensure_dirs_ok()
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# 2. 处理日志
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_archive_logs()
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# 3. 执行 Pytest
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args = [
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"test_cases",
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"-x", # 注意:-x 表示遇到错误立即停止,如果是全量回归建议去掉 -x
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"-v",
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f"--alluredir={ALLURE_TEMP}",
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# f"--platform={AppPlatform.ANDROID.value}",
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# "--caps_name=wan_android"
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]
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pytest.main(args)
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# 4. 生成报告
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generate_allure_report()
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except Exception as e:
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print(f"自动化测试执行过程中发生异常: {e}")
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finally:
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print("Time-of-check to Time-of-use")
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if __name__ == "__main__":
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main()
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