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modify.py

+#!/usr/bin/env python3
+"""
+用法示例：
+python multi_folder.py folder1 folder2 folder3 --suffix MyTag
+"""
+import argparse
+import os
+import glob
+import pandas as pd
+from openpyxl import Workbook, load_workbook
+from openpyxl.styles import (
+    Alignment, Border, Side, Font, PatternFill
+)
+from openpyxl.utils import get_column_letter
+from openpyxl.utils.dataframe import dataframe_to_rows
+
+# ===== 英文 → 中文列名 =====
+COL_MAP = {
+    'tp': '张量并行度',
+    'data_type': '数据类型',
+    'batch': '并发数',
+    'prompt_tokens': '输入的 token 数',
+    'completion_tokens': '输出的 token 数',
+    'TOTAL_THROUGHPUT(toks/s)': '总吞吐量（tokens/秒）',
+    'generate_throughput(toks/s)': '生成吞吐量（tokens/秒）',
+    'TTFT(ms)': '首个 token 的延迟（毫秒）',
+    'TPOT(ms)': '每个输出 token 的延迟（毫秒）',
+    'ITL(ms)': '每 token 的间隔延迟（毫秒）'
+}
+
+# ===== 通用样式 =====
+thin   = Side(border_style='thin', color='BFBFBF')
+border = Border(top=thin, bottom=thin, left=thin, right=thin)
+center_wrap = Alignment(horizontal='center', vertical='center', wrap_text=True)
+
+def beautify(ws, title, df):
+    """统一美化：标题、表头、边框、斑马纹、自适应列宽"""
+    # 1. 合并标题行
+    ws.merge_cells(start_row=1, start_column=1, end_row=1, end_column=len(df.columns))
+    ws['A1'] = title
+    ws['A1'].font = Font(bold=True, size=13)
+    ws['A1'].alignment = center_wrap
+    ws.row_dimensions[1].height = 28
+
+    # 2. 表头
+    header_font = Font(bold=True, color='FFFFFF')
+    header_fill = PatternFill('solid', fgColor='4F81BD')
+    for cell in ws[2]:
+        cell.font = header_font
+        cell.fill = header_fill
+        cell.alignment = center_wrap
+        cell.border = border
+    ws.row_dimensions[2].height = 25
+
+    # 3. 数据区
+    for row in ws.iter_rows(min_row=3, max_row=ws.max_row):
+        fill = PatternFill('solid', fgColor='F8F9FA') if row[0].row % 2 == 0 else None
+        for cell in row:
+            cell.alignment = center_wrap
+            cell.border = border
+            if fill:
+                cell.fill = fill
+
+    # 4. 自适应列宽
+    for col_idx in range(1, len(df.columns) + 1):
+        col_letter = get_column_letter(col_idx)
+        max_len = max(len(str(ws.cell(r, col_idx).value or '')) for r in range(1, ws.max_row + 1))
+        width = max(max_len + 2, 10) * 1.1
+        ws.column_dimensions[col_letter].width = width
+
+    # 5. 冻结首行
+    ws.freeze_panes = ws["A3"]
+
+def process_folder(folder, suffix):
+    csv_files = glob.glob(os.path.join(folder, '*.csv'))
+    if not csv_files:
+        print(f'【{folder}】未找到 csv，跳过')
+        return
+
+    out_dir = os.path.join(folder, 'standardized_output')
+    os.makedirs(out_dir, exist_ok=True)
+
+    summary_path = os.path.join(out_dir, 'summary.xlsx')
+    summary_wb = load_workbook(summary_path) if os.path.exists(summary_path) else Workbook()
+    for sh in list(summary_wb.sheetnames):
+        del summary_wb[sh]
+
+    for csv_path in csv_files:
+        df = pd.read_csv(csv_path)
+        if 'TPOT(ms)' not in df.columns:
+            continue
+        # 新增两列
+        df['单路生成吞吐(toks/s)']   = (1000 / df['TPOT(ms)']).round(2)
+        df['不带首字的生成吞吐（tok/s）'] = (df['单路生成吞吐(toks/s)'] * df['batch']).round(2)
+        df.rename(columns=COL_MAP, inplace=True)
+
+        base_name  = os.path.splitext(os.path.basename(csv_path))[0]
+        sheet_name = f'{base_name}_{suffix}'[:31]
+
+        # 1) 独立 Excel
+        single_xlsx = os.path.join(out_dir, f'{sheet_name}.xlsx')
+        df.to_excel(single_xlsx, index=False, header=True, startrow=1)
+        wb = load_workbook(single_xlsx)
+        ws = wb.active
+        beautify(ws, sheet_name, df)
+        wb.save(single_xlsx)
+        print(f'独立文件：{os.path.relpath(single_xlsx)}')
+
+        # 2) 汇总 Excel
+        if sheet_name in summary_wb.sheetnames:
+            del summary_wb[sheet_name]
+        ws_sum = summary_wb.create_sheet(title=sheet_name)
+        for r_idx, row in enumerate(dataframe_to_rows(df, index=False, header=True), start=2):
+            for c_idx, value in enumerate(row, start=1):
+                ws_sum.cell(row=r_idx, column=c_idx, value=value)
+        beautify(ws_sum, sheet_name, df)
+
+    summary_wb.save(summary_path)
+    print(f'汇总文件：{os.path.relpath(summary_path)}  已生成！')
+
+def main():
+    parser = argparse.ArgumentParser(description='批量处理多个文件夹内的 CSV')
+    parser.add_argument('folders', nargs='+', help='要处理的文件夹列表')
+    parser.add_argument('--suffix', '-s', default=None, help='统一后缀（缺省用文件夹名）')
+    args = parser.parse_args()
+
+    for folder in args.folders:
+        if not os.path.isdir(folder):
+            print(f'目录不存在：{folder}')
+            continue
+        suffix = args.suffix or os.path.basename(folder)
+        process_folder(folder, suffix)
+
+if __name__ == '__main__':
+    main()
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