直角三角形计算

import pandas as pd
import os
import glob


def read_excel_data(file_path):
    """读取单个 Excel 文件的所有 Sheet,返回合并后的 DataFrame"""
    print(f"\n处理文件: {os.path.basename(file_path)}")
    
    if not os.path.exists(file_path):
        print(f"  错误: 文件不存在 - {file_path}")
        return None

    try:
        sheets_dict = pd.read_excel(file_path, sheet_name=None, engine='openpyxl')
        all_data = []
        
        print(f"  找到 {len(sheets_dict)} 个 Sheet 页")
        
        for sheet_name, df in sheets_dict.items():
            df.columns = [str(c).strip() for c in df.columns]
            print(f"    Sheet '{sheet_name}': {len(df)} 行")
            
            if '测试项' in df.columns and '接口耗时(ms)' in df.columns:
                subset = df[['测试项', '接口耗时(ms)']].copy()
                all_data.append(subset)
            elif df.shape[1] >= 2:
                print(f"      警告: 列名不匹配 {df.columns.tolist()},使用前两列")
                subset = df.iloc[:, :2].copy()
                subset.columns = ['测试项', '接口耗时(ms)']
                all_data.append(subset)
            else:
                print(f"      跳过: 列结构不符合要求")

        if all_data:
            return pd.concat(all_data, ignore_index=True)
        return None
        
    except Exception as e:
        print(f"  读取失败: {e}")
        return None


def process_multiple_excels(input_dir):
    """处理 input 目录下所有 Excel 文件"""
    print(f"扫描目录: {input_dir}")
    
    # 查找所有 xlsx 和 xls 文件
    xlsx_files = glob.glob(os.path.join(input_dir, '*.xlsx'))
    xls_files = glob.glob(os.path.join(input_dir, '*.xls'))
    all_files = xlsx_files + xls_files
    
    if not all_files:
        print("未找到任何 Excel 文件!")
        return
    
    print(f"找到 {len(all_files)} 个 Excel 文件:")
    for f in all_files:
        print(f"  - {os.path.basename(f)}")
    
    # 收集所有文件的数据
    all_data = []
    for file_path in all_files:
        df = read_excel_data(file_path)
        if df is not None:
            all_data.append(df)
    
    if not all_data:
        print("\n未提取到任何有效数据。")
        return
    
    # 合并所有数据
    full_df = pd.concat(all_data, ignore_index=True)
    
    print("\n" + "="*50)
    print("数据汇总:")
    print("="*50)
    original_count = len(full_df)
    
    # 数据清洗
    full_df['接口耗时(ms)_数值'] = pd.to_numeric(full_df['接口耗时(ms)'], errors='coerce')
    
    invalid_rows = full_df[full_df['接口耗时(ms)'].notna() & full_df['接口耗时(ms)_数值'].isna()]
    if not invalid_rows.empty:
        print(f"发现 {len(invalid_rows)} 行无效数据 (将被忽略):")
        print(invalid_rows[['测试项', '接口耗时(ms)']].to_string(index=False))
    
    clean_df = full_df.dropna(subset=['测试项', '接口耗时(ms)_数值']).copy()
    clean_df['接口耗时(ms)'] = clean_df['接口耗时(ms)_数值']
    
    print(f"原始总行数: {original_count}, 清洗后有效行数: {len(clean_df)}")

    if clean_df.empty:
        print("清洗后无有效数据。")
        return

    # 计算每个测试项的平均耗时
    print("\n" + "="*50)
    print("详细计算过程 (Debug):")
    print("="*50)
    
    unique_items = clean_df['测试项'].unique()
    final_results = []
    
    for item in unique_items:
        item_data = clean_df[clean_df['测试项'] == item]['接口耗时(ms)']
        values = item_data.tolist()
        avg_val = item_data.mean()
        sum_val = item_data.sum()
        count_val = len(item_data)
        
        print(f"\n测试项: [{item}]")
        print(f"  - 原始数值列表: {values}")
        print(f"  - 数据个数: {count_val}")
        print(f"  - 总耗时: {sum_val}")
        print(f"  - 平均耗时: {avg_val:.4f}")
        
        final_results.append({
            '测试项': item,
            '平均接口耗时(ms)': round(avg_val, 2)
        })

    result = pd.DataFrame(final_results)
    
    print("\n" + "="*50)
    print("最终结果摘要:")
    print("="*50)
    print(result.to_string(index=False))
    print("="*50)
    
    # 保存结果(保存到 input 同级目录)
    output_file = os.path.join(os.path.dirname(input_dir), 'result.xlsx')
    try:
        result.to_excel(output_file, index=False)
        print(f"\n结果已保存至: {output_file}")
    except Exception as e:
        print(f"\n保存文件失败: {e}")


if __name__ == "__main__":
    current_dir = os.path.dirname(os.path.abspath(__file__))
    input_dir = os.path.join(current_dir, 'input')
    
    if not os.path.exists(input_dir):
        print(f"错误: input 目录不存在 - {input_dir}")
        print("请创建 input 目录并放入 Excel 文件")
    else:
        process_multiple_excels(input_dir)