CoverageConversionTool/覆盖率转换工具.py

import re
import openpyxl
from pathlib import Path
import time
import sys
import os

def txt_to_xlsx():
    try:
        print("正在启动覆盖率转换工具...")
        print("正在搜索目录中的txt文件...")
        
        # 获取当前工作目录（兼容打包前后）
        if getattr(sys, 'frozen', False):
            # 如果是打包后的exe运行
            current_dir = Path(os.path.dirname(sys.executable))
        else:
            # 如果是直接运行Python脚本
            current_dir = Path(__file__).parent
        
        print(f"当前工作目录: {current_dir}")
        
        # 查找当前目录下的所有txt文件
        txt_files = list(current_dir.glob("*.txt"))
        
        # 检查是否存在txt文件
        if not txt_files:
            print("没有文件，请将txt文件放入当前目录后重试")
            return
        
        print(f"找到 {len(txt_files)} 个txt文件，正在处理第一个文件: {txt_files[0].name}")
        
        # 使用找到的第一个txt文件
        txt_path = txt_files[0]
        xlsx_path = current_dir / "coverage_summary.xlsx"
        
        text = txt_path.read_text(encoding="utf-8")

        # 创建Excel工作簿
        wb = openpyxl.Workbook()
        ws = wb.active
        ws.title = "Coverage Summary"

        # 表头 - 只包含指标名称和覆盖率
        headers = [
            "File",
            "Stmts", "Stmts % Covered",
            "Branches", "Branches % Covered",
            "FEC Condition Terms", "FEC Condition Terms % Covered",
            "FEC Expression Terms", "FEC Expression Terms % Covered",
            "FSM States", "FSM States % Covered",
            "FSM Transitions", "FSM Transitions % Covered"
        ]
        ws.append(headers)

        # 按文件分割内容
        files = re.split(r"={80}\n=== File: (.+?)\n={80}", text)
        
        # 解析每个文件内容
        for i in range(1, len(files), 2):
            file_path = files[i].strip()
            content = files[i+1]
            
            # 提取文件名（去掉路径）
            file_name = Path(file_path).name
            
            # 初始化行数据
            row = [file_name]
            
            # 定义要提取的指标
            metrics = [
                "Stmts",
                "Branches", 
                "FEC Condition Terms",
                "FEC Expression Terms",
                "States",  # FSM States
                "Transitions"  # FSM Transitions
            ]
            
            # 为每个指标提取数据
            for metric in metrics:
                # 构建正则表达式模式
                pattern = rf"^\s*{re.escape(metric)}\b\s+(\d+)\s+\d+\s+\d+\s+([\d\.]+)%?$"
                
                # 查找匹配项
                match = re.search(pattern, content, flags=re.M)
                
                if match:
                    count, percent = match.groups()
                    row.extend([count, f"{percent}%"])
                else:
                    # 如果没有找到特定指标，统一填入 "/"
                    row.extend(["/", "/"])
            
            ws.append(row)

        # 自动调整列宽
        for col in ws.columns:
            max_len = max(len(str(cell.value or "")) for cell in col)
            ws.column_dimensions[col[0].column_letter].width = max(10, min(50, max_len + 2))

        # 保存Excel文件
        wb.save(xlsx_path)
        print(f"完成转换: {xlsx_path}")
        
    except Exception as e:
        print(f"发生错误: {e}")
        import traceback
        traceback.print_exc()
    finally:
        # 等待10秒防止窗口闪退
        print("程序将在10秒后退出...")
        time.sleep(10)


# 直接调用函数，无需传入参数
if __name__ == "__main__":
    txt_to_xlsx()