带着公式

双表合并.py

@@ -0,0 +1,291 @@
+import pandas as pd
+import os
+
+
+def process_contracts(file_path):
+    print(f"正在读取并处理文件: {file_path} ...")
+
+    # --- 1. 读取CSV文件 (容错处理) ---
+    df = None
+    encodings = ['utf-8', 'gbk', 'gb18030']
+    for enc in encodings:
+        try:
+            df = pd.read_csv(file_path, encoding=enc)
+            break
+        except UnicodeDecodeError:
+            continue
+
+    if df is None:
+        try:
+            print("注意: 标准编码读取失败，正在尝试忽略乱码强制读取...")
+            df = pd.read_csv(file_path, encoding='gb18030', encoding_errors='replace')
+        except Exception as e:
+            print(f"读取文件彻底失败: {e}")
+            return
+
+    # --- 2. 确认厂家列名 ---
+    col_factory_general = '厂家'
+    col_factory_detail = '厂家.1'
+
+    if col_factory_detail not in df.columns:
+        print("警告: 未检测到第二个'厂家'列，明细表将被迫使用第一个'厂家'列。")
+        col_factory_detail = '厂家'
+    else:
+        print(f"厂家列识别成功：总表使用 '{col_factory_general}'，明细表使用 '{col_factory_detail}'")
+
+    # --- 3. 定义表头 ---
+
+    # 3.1 外贸/内贸 总表表头
+    columns_general = [
+        "合同编号", "签署公司", "外贸合同号", "收款情况", "合同签订日期",
+        "销售员", "最终用户单位", "最终用户信息联系人、电话、邮箱", "最终用户所在地",
+        "厂家", "型号/货号", "合同标的", "数量", "单位", "币种", "折扣率",
+        "合同", "总合同额", "外购", "已收款", "未收款", "收款日期",
+        "最晚发货期", "付款方式", "发货港", "目的港", "发货日期",
+        "买方单位", "买方信息联系人、电话、邮箱", "收货人信息"
+    ]
+    columns_domestic_general = [c if c != "外贸合同号" else "内贸合同号" for c in columns_general]
+
+    # 3.2 明细表表头
+    columns_detail = [
+        "合同编号", "销售员", "厂家", "合同标的", "货号", "产品描述", "数量", "单位",
+        "币种", "报价单价", "报价总价", "销售单价", "销售总价", "折扣率",
+        "外购", "合同币种/美元", "外购转美元", "报价总价美元", "净合同额美元"
+    ]
+
+    # 3.3 其他表表头
+    columns_other = [
+        "合同编号", "签署公司", "内贸合同号", "收款情况", "签订日期",
+        "销售员", "最终用户单位", "最终用户信息联系人、电话、邮箱", "最终用户所在地",
+        "买方单位", "买方信息联系人、电话、邮箱", "合同标的", "合同总额",
+        "已收款", "未收款", "收款日期"
+    ]
+
+    # --- 4. 辅助函数：安全转数字 ---
+    def safe_float(val):
+        try:
+            if isinstance(val, str):
+                val = val.replace(',', '').strip()
+                if val == '': return 0.0
+            return float(val)
+        except (ValueError, TypeError):
+            return 0.0
+
+    # --- 5. 数据转换逻辑 ---
+
+    # 5.1 外贸/内贸 总表转换逻辑
+    def transform_general_row(row, trade_type):
+        target_cols = columns_general if trade_type == '外贸' else columns_domestic_general
+        new_row = {col: "" for col in target_cols}
+
+        # 拆分合同号
+        order_no_raw = str(row.get('合同订单编号', ''))
+        parts_no = order_no_raw.split(' ')
+        new_row['合同编号'] = parts_no[0] if len(parts_no) > 0 else order_no_raw
+        contract_no_col = '外贸合同号' if trade_type == '外贸' else '内贸合同号'
+        new_row[contract_no_col] = parts_no[1] if len(parts_no) > 1 else ""
+
+        # 拆分合同标的 (不再从这里取总价)
+        target_raw = str(row.get('合同标的（品名/型号/数量/单价/总价）', ''))
+        parts_target = target_raw.split('/')
+        if len(parts_target) >= 1: new_row['合同标的'] = parts_target[0]
+        if len(parts_target) >= 2: new_row['型号/货号'] = parts_target[1]
+        if len(parts_target) >= 3: new_row['数量'] = parts_target[2]
+        if len(parts_target) >= 4: new_row['合同'] = parts_target[3]  # 单价
+
+        # 【修改点】总合同额：直接读取 CSV 中的“合同总额”列
+        new_row['总合同额'] = row.get('合同总额', '')
+
+        # 映射其他字段
+        new_row['签署公司'] = row.get('收款账户', '')
+        new_row['收款情况'] = row.get('收款状态', '')
+        new_row['合同签订日期'] = row.get('签约日期', '')
+        new_row['销售员'] = row.get('负责人', '')
+        new_row['最终用户单位'] = row.get('客户名称', '')
+        new_row['最终用户信息联系人、电话、邮箱'] = row.get('联系人姓名', '')
+        new_row['厂家'] = row.get(col_factory_general, '')
+        new_row['币种'] = row.get('货币(选完产品再改)', '')
+        new_row['外购'] = row.get('外购产品金额', '')
+        new_row['收款日期'] = row.get('最新收款日期', '')
+        new_row['最晚发货期'] = row.get('最晚发货期', '')
+        new_row['付款方式'] = row.get('付款比例及期限', '')
+        new_row['发货港'] = row.get('发货地', '')
+        new_row['目的港'] = row.get('目的港', '')
+        new_row['买方单位'] = row.get('合同买方（名称/联系人/电话/邮箱）', '')
+
+        return pd.Series(new_row)
+
+    # 5.2 明细表转换逻辑
+    def transform_detail_row(row):
+        new_row = {col: "" for col in columns_detail}
+
+        detail_manuf_val = str(row.get(col_factory_detail, ''))
+        order_no_raw = str(row.get('合同订单编号', ''))
+        new_row['合同编号'] = order_no_raw.split(' ')[0] if order_no_raw else ""
+        new_row['销售员'] = row.get('负责人', '')
+        new_row['厂家'] = detail_manuf_val
+        new_row['货号'] = row.get('产品编码', '')
+        new_row['数量'] = row.get('数量', '')
+        new_row['单位'] = ""
+        new_row['币种'] = row.get('原币种', '')
+        new_row['折扣率'] = ""
+
+        target_raw = str(row.get('合同标的（品名/型号/数量/单价/总价）', ''))
+        parts_target = target_raw.split('/')
+        new_row['合同标的'] = parts_target[0] if len(parts_target) >= 1 else ""
+
+        val_outsourcing_raw = safe_float(row.get('外购产品金额', 0))
+        val_rate = safe_float(row.get('汇率', 1))
+        if val_rate == 0: val_rate = 1
+
+        raw_price_unit = row.get('美元报价', '')
+        raw_price_total = row.get('产品小计', '')
+
+        if '外购' in detail_manuf_val:
+            new_row['外购'] = val_outsourcing_raw
+            new_row['产品描述'] = row.get('备注', '')
+            new_row['报价单价'] = ""
+            new_row['报价总价'] = ""
+            new_row['销售单价'] = ""
+            new_row['销售总价'] = ""
+            current_outsourcing_cost = val_outsourcing_raw
+        else:
+            new_row['外购'] = ""
+            new_row['产品描述'] = row.get('产品名称', '')
+            new_row['报价单价'] = raw_price_unit
+            new_row['报价总价'] = raw_price_total
+            new_row['销售单价'] = ""
+            new_row['销售总价'] = ""
+            current_outsourcing_cost = 0
+
+        new_row['合同币种/美元'] = ""
+
+        if current_outsourcing_cost > 0:
+            new_row['外购转美元'] = round(current_outsourcing_cost / val_rate, 2)
+        else:
+            new_row['外购转美元'] = ""
+
+        new_row['报价总价美元'] = ""
+        new_row['净合同额美元'] = ""
+
+        return pd.Series(new_row)
+
+    # 5.3 其他表转换逻辑
+    def transform_other_row(row):
+        new_row = {col: "" for col in columns_other}
+
+        # 拆分合同号
+        order_no_raw = str(row.get('合同订单编号', ''))
+        parts_no = order_no_raw.split(' ')
+        new_row['合同编号'] = parts_no[0] if len(parts_no) > 0 else order_no_raw
+        new_row['内贸合同号'] = parts_no[1] if len(parts_no) > 1 else ""
+
+        # 合同标的 (取第一部分)
+        target_raw = str(row.get('合同标的（品名/型号/数量/单价/总价）', ''))
+        parts_target = target_raw.split('/')
+        if len(parts_target) >= 1:
+            new_row['合同标的'] = parts_target[0]
+
+        # 【修改点】合同总额：直接读取源CSV的“合同总额”列
+        new_row['合同总额'] = row.get('合同总额', '')
+
+        # 映射其他字段
+        new_row['签署公司'] = row.get('收款账户', '')
+        new_row['收款情况'] = row.get('收款状态', '')
+        new_row['签订日期'] = row.get('签约日期', '')
+        new_row['销售员'] = row.get('负责人', '')
+        new_row['最终用户单位'] = row.get('客户名称', '')
+        new_row['最终用户信息联系人、电话、邮箱'] = row.get('联系人姓名', '')
+        new_row['买方单位'] = row.get('合同买方（名称/联系人/电话/邮箱）', '')
+        new_row['收款日期'] = row.get('最新收款日期', '')
+
+        return pd.Series(new_row)
+
+    # --- 6. 主处理流程 ---
+
+    df[col_factory_general] = df[col_factory_general].fillna('').astype(str)
+    df['合同类型'] = df['合同类型'].fillna('').astype(str)
+
+    # 文件拆分逻辑
+    df_asd = df[df[col_factory_general].str.contains('ASD', case=False, na=False)]
+    df_non_asd = df[~df[col_factory_general].str.contains('ASD', case=False, na=False)]
+
+    def create_excel(dataframe, filename):
+        raw_foreign = dataframe[dataframe['合同类型'] == '外贸'].copy()
+        raw_domestic = dataframe[dataframe['合同类型'] == '内贸'].copy()
+        raw_other = dataframe[~dataframe['合同类型'].isin(['外贸', '内贸'])].copy()
+
+        # === 1. 生成外贸数据 ===
+        if not raw_foreign.empty:
+            df_gen = raw_foreign.apply(lambda row: transform_general_row(row, '外贸'), axis=1)
+            df_gen = df_gen[columns_general]
+            df_gen_unique = df_gen.drop_duplicates(subset=['合同编号'], keep='first')
+            df_gen_unique = df_gen_unique.sort_values(by='合同编号', ascending=True)
+
+            df_det = raw_foreign.apply(lambda row: transform_detail_row(row), axis=1)
+            df_det = df_det[columns_detail]
+            df_det = df_det.sort_values(by='合同编号', ascending=True)
+            mask_duplicates = df_det.duplicated(subset=['合同编号'], keep='first')
+            df_det.loc[mask_duplicates, '合同标的'] = ""
+
+        else:
+            df_gen_unique = pd.DataFrame(columns=columns_general)
+            df_det = pd.DataFrame(columns=columns_detail)
+
+        # === 2. 生成内贸数据 ===
+        if not raw_domestic.empty:
+            df_dom_gen = raw_domestic.apply(lambda row: transform_general_row(row, '内贸'), axis=1)
+            df_dom_gen = df_dom_gen[columns_domestic_general]
+            df_dom_gen_unique = df_dom_gen.drop_duplicates(subset=['合同编号'], keep='first')
+            df_dom_gen_unique = df_dom_gen_unique.sort_values(by='合同编号', ascending=True)
+
+            df_dom_det = raw_domestic.apply(lambda row: transform_detail_row(row), axis=1)
+            df_dom_det = df_dom_det[columns_detail]
+            df_dom_det = df_dom_det.sort_values(by='合同编号', ascending=True)
+            mask_duplicates_dom = df_dom_det.duplicated(subset=['合同编号'], keep='first')
+            df_dom_det.loc[mask_duplicates_dom, '合同标的'] = ""
+
+        else:
+            df_dom_gen_unique = pd.DataFrame(columns=columns_domestic_general)
+            df_dom_det = pd.DataFrame(columns=columns_detail)
+
+        # === 3. 生成其他数据 ===
+        if not raw_other.empty:
+            df_other = raw_other.apply(lambda row: transform_other_row(row), axis=1)
+            df_other = df_other[columns_other]
+            # 去重
+            df_other_unique = df_other.drop_duplicates(subset=['合同编号'], keep='first')
+            # 排序
+            df_other_unique = df_other_unique.sort_values(by='合同编号', ascending=True)
+        else:
+            df_other_unique = pd.DataFrame(columns=columns_other)
+
+        # === 4. 写入 Excel ===
+        try:
+            print(f"[{filename}] 正在写入Excel...")
+            with pd.ExcelWriter(filename, engine='openpyxl') as writer:
+                df_gen_unique.to_excel(writer, sheet_name='外贸总表', index=False)
+                df_det.to_excel(writer, sheet_name='外贸明细', index=False)
+                df_dom_gen_unique.to_excel(writer, sheet_name='内贸总表', index=False)
+                df_dom_det.to_excel(writer, sheet_name='内贸明细', index=False)
+                df_other_unique.to_excel(writer, sheet_name='其他', index=False)
+            print(f"成功生成文件: {filename}")
+        except Exception as e:
+            print(f"生成 {filename} 时发生错误: {e}")
+
+    # 执行生成
+    print("-" * 40)
+    create_excel(df_asd, 'ASD.xlsx')
+    print("-" * 40)
+    create_excel(df_non_asd, '非ASD.xlsx')
+    print("-" * 40)
+    print("全部处理完成！")
+
+
+# --- 运行入口 ---
+if __name__ == "__main__":
+    csv_file = 'test.csv'
+    if os.path.exists(csv_file):
+        process_contracts(csv_file)
+    else:
+        print(f"找不到文件: {csv_file}，请检查路径。")

拿取内容测试.py

@@ -1,91 +0,0 @@
-import requests
-import json
-import os
-
-# ================= 配置区域 =================
-base_url = "http://111.198.24.44:88/index.php"
-
-# 1. 登录信息
-login_payload = {
-    "module": "Users",
-    "action": "Authenticate",
-    "return_module": "Users",
-    "return_action": "Login",
-    "user_name": "你的用户名",  # <--- 记得填
-    "user_password": "你的密码",  # <--- 记得填
-    "login_theme": "newskin"
-}
-
-# 2. 抓取数据参数 (保留了你之前的筛选条件)
-data_payload = {
-    "module": "SalesOrder",
-    "action": "SalesOrderAjax",
-    "file": "ListViewData",
-    "sorder": "",
-    "start": "1",
-    "pagesize": "100",
-    "actionId": "1768546984243",
-    "isFilter": "true",
-    "search[viewscope]": "all_to_me",
-    "search[viewname]": "324126",
-    "filter[Fields0]": "subject",
-    "filter[Condition0]": "cts",
-    "filter[Srch_value0]": "W25A",
-    "filter[type0]": "text",
-    "filter[dateCondition1]": "prevfy",
-    "filter[Fields1]": "duedate",
-    "filter[Condition1]": "btwa",
-    "filter[Srch_value1]": "2025-01-01,2025-12-31",
-    "filter[type1]": "date",
-    "filter[Fields2]": "subject",
-    "filter[Condition2]": "dcts",
-    "filter[Srch_value2]": "取消",
-    "filter[type2]": "text",
-    "filter[search_cnt]": "3",
-    "filter[matchtype]": "all"
-}
-
-headers = {
-    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
-    "Referer": "http://111.198.24.44:88/index.php?module=SalesOrder&action=index"
-}
-
-# ================= 执行逻辑 =================
-session = requests.Session()
-
-try:
-    print("1. 正在登录...")
-    session.post(base_url, data=login_payload, headers=headers)
-
-    if 'PHPSESSID' in session.cookies:
-        print("   登录成功，Cookie已获取。")
-    else:
-        print("   ⚠️ 警告：可能登录失败 (未检测到PHPSESSID)。")
-
-    print("2. 正在获取数据并导出...")
-    resp = session.post(base_url, data=data_payload, headers=headers)
-
-    # === 关键修改：保存文件 ===
-    try:
-        # 尝试解析 JSON
-        json_data = resp.json()
-
-        # 定义文件名
-        filename = "result.json"
-
-        # 写入文件
-        # ensure_ascii=False 保证中文能正常显示，而不是显示成 \u53d6\u6d88
-        with open(filename, 'w', encoding='utf-8') as f:
-            json.dump(json_data, f, ensure_ascii=False, indent=4)
-
-        print(f"\n✅ 成功！数据已保存到当前目录下的: 【{filename}】")
-        print(f"   文件路径: {os.path.abspath(filename)}")
-
-    except json.JSONDecodeError:
-        print("\n❌ 失败：服务器返回的不是 JSON 格式。")
-        print("可能是 HTML 页面，已保存为 'error_page.html' 供检查。")
-        with open("error_page.html", "w", encoding="utf-8") as f:
-            f.write(resp.text)
-
-except Exception as e:
-    print(f"发生错误: {e}")

登录测试.py

@@ -1,56 +0,0 @@
-import requests
-
-# 1. 准备登录信息
-login_url = "http://111.198.24.44:88/index.php"
-
-# 这是你刚刚抓到的 Payload 数据
-payload = {
-    "error": "",
-    "login_theme": "newskin",
-    "module": "Users",
-    "action": "Authenticate",
-    "return_module": "Users",
-    "return_action": "Login",
-    "user_name": "TEST",  # 在这里填入真实的用户名
-    "user_password": "test",  # 在这里填入真实的密码
-    "code": "",
-    "user_validate": ""
-}
-
-# 伪装成浏览器（这很重要，防止被反爬虫拦截）
-headers = {
-    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
-}
-
-# 2. 创建一个 Session (会话)
-# Session 的作用就像一个浏览器窗口，它会自动保存 Cookie
-session = requests.Session()
-
-try:
-    # 3. 发送登录请求
-    # allow_redirects=True 会自动跟随 301 跳转到主页，就像浏览器一样
-    response = session.post(login_url, data=payload, headers=headers, allow_redirects=True)
-
-    # 4. 检查结果
-    print(f"状态码: {response.status_code}")
-
-    # 获取到的 Cookie
-    print("获取到的 Cookies:")
-    print(session.cookies.get_dict())
-
-    # 简单的验证：如果返回的网页里包含了'退出'或用户名的字样，说明登录成功了
-    if "logout" in response.text.lower() or "退出" in response.text:
-        print("\n==> 登录成功！ <==")
-
-        # 【进阶】: 登录成功后，你可以直接用这个 session 访问其他页面
-        # 比如访问主页获取数据，它会自动带上刚才拿到的 cookie
-        # home_page = session.get("http://111.198.24.44:88/index.php?module=Home&action=index")
-        # print(home_page.text[:200])
-
-    else:
-        print("\n可能登录失败，请检查用户名密码。")
-        # 如果失败，打印一部分返回内容看看原因
-        print("返回内容预览:", response.text[:500])
-
-except Exception as e:
-    print(f"发生错误: {e}")

页面.py

@@ -0,0 +1,965 @@
+import pandas as pd
+import tkinter as tk
+from tkinter import ttk, filedialog, messagebox, simpledialog
+import os
+import numpy as np
+import re
+from datetime import datetime
+
+
+# ==========================================
+# 第一部分：业务逻辑核心
+# ==========================================
+
+class DataProcessor:
+    def __init__(self):
+        # ==================== 1. 外贸总表表头 ====================
+        self.cols_asd_foreign_general = [
+            "合同编号", "签署公司", "外贸合同号", "收款情况", "合同签订日期", "销售员",
+            "最终用户单位", "最终用户信息\n联系人、电话、邮箱", "最终用户所在地",
+            "厂家", "型号/货号", "合同标的", "数量", "单位", "币种", "折扣率",
+            "合同额", "总合同额", "外购", "已收款", "未收款", "收款日期",
+            "最晚发货期", "付款方式", "发货港", "目的港", "发货日期",
+            "买方单位", "买方信息\n联系人、电话、邮箱", "收货人信息",
+            "转为美元净合同额", "转为美元总合同额"
+        ]
+
+        self.cols_nonasd_foreign_general = [
+            "合同编号", "签署公司", "外贸合同号", "收款情况", "合同签订日期", "销售员",
+            "最终用户单位", "最终用户信息\n联系人、电话、邮箱", "最终用户所在地",
+            "厂家", "型号/货号", "合同标的", "数量", "单位", "币种", "折扣率",
+            "合同额", "总合同额", "外购", "已收款", "未收款", "收款日期",
+            "最晚发货期", "付款方式", "发货港", "目的港", "发货日期",
+            "买方单位", "买方信息\n联系人、电话、邮箱", "收货人信息",
+            "合同币种/美元", "转为美元净合同额", "转为美元总合同额"
+        ]
+
+        # ==================== 2. 内贸总表表头 ====================
+        self.cols_domestic_general = [
+            "合同编号", "签署公司", "内贸合同号", "收款情况", "签订日期", "销售员",
+            "最终用户单位", "最终用户信息\n联系人、电话、邮箱", "最终用户所在地",
+            "买方单位", "买方信息\n联系人、电话、邮箱",
+            "厂家", "型号", "合同标的", "数量", "单位", "折扣率（％）",
+            "合同额", "合同总额", "外购", "付款方式", "最晚发货期",
+            "已收款", "未收款", "收款日期",
+            "转为美元净合同额", "转为美元总合同额"
+        ]
+
+        # ==================== 3. 外贸明细表头 ====================
+        self.cols_foreign_detail = [
+            "合同编号", "销售员", "合同标的", "厂家", "货号", "产品描述", "数量", "单位",
+            "币种", "报价单价", "报价总价", "销售单价", "销售总价", "折扣率",
+            "外购", "合同币种/美元", "外购转美元", "报价总价美元", "净合同额美元"
+        ]
+
+        # ==================== 4. 内贸明细表头 ====================
+        self.cols_domestic_detail = [
+            "合同编号", "销售员", "合同标的", "厂家", "货号", "产品描述", "数量", "单位",
+            "外币币种", "外币报价单价", "报价RMB单价", "报价RMB总价",
+            "售价RMB单价", "售价RMB总价", "折扣率（％）", "外购",
+            "计算汇率", "外购转美元", "报价总价美元", "净合同额美元"
+        ]
+
+        # ==================== 5. OM合同表头 ====================
+        self.cols_om = [
+            "合同编号", "签署公司", "内贸合同号", "收款情况", "签订日期", "销售员",
+            "最终用户单位", "最终用户信息\n联系人、电话、邮箱", "最终用户所在地",
+            "买方单位", "买方信息\n联系人、电话、邮箱", "合同标的",
+            "合同总额", "已收款", "未收款", "收款日期"
+        ]
+
+        # [逻辑] 只写在“第一行”（单价最高行）的列
+        self.header_only_cols = set([
+            "总合同额", "合同总额", "外购", "付款方式", "最晚发货期",
+            "已收款", "未收款", "收款日期", "收款情况",
+            "转为美元净合同额", "转为美元总合同额"
+        ])
+
+        # [逻辑] 金额列 (保留两位小数)
+        self.money_cols = set([
+            "合同额", "总合同额", "合同总额", "外购", "已收款", "未收款",
+            "净合同额美元", "外购转美元", "报价总价美元",
+            "外币报价单价", "报价RMB单价", "报价RMB总价",
+            "售价RMB单价", "售价RMB总价", "外购产品金额",
+            "转为美元净合同额", "转为美元总合同额", "报价单价", "报价总价", "销售单价", "销售总价"
+        ])
+
+        # [逻辑] 比率列 (百分比展示)
+        self.percent_cols = set([
+            "折扣率", "折扣率（％）", "计算汇率", "合同币种/美元"
+        ])
+
+        # [新增逻辑] 日期列 (需要去除时分秒)
+        self.date_cols = set([
+            "合同签订日期", "签订日期", "收款日期", "最晚发货期", "发货日期"
+        ])
+
+        # [逻辑] 旧表头映射 (用于读取旧Excel时兼容)
+        self.legacy_map = {
+            "外币币种": "币种",
+            "汇率": "计算汇率",
+            "折扣率(%)": "折扣率",
+            "折扣率（%）": "折扣率（％）",
+            "合同": "合同额"
+        }
+
+        # [核心] 构建所有标准列名的快速查找字典 (清洗后的key -> 标准带换行的key)
+        # 目的：无论Excel里是 "最终用户信息联系人..." 还是 "最终用户信息\n联系人...", 都能映射回标准
+        self.standard_col_map = {}
+        all_lists = [
+            self.cols_asd_foreign_general, self.cols_nonasd_foreign_general,
+            self.cols_domestic_general, self.cols_foreign_detail,
+            self.cols_domestic_detail, self.cols_om
+        ]
+        for lst in all_lists:
+            for col in lst:
+                clean_key = self.clean_header_key(col)
+                self.standard_col_map[clean_key] = col
+
+    def clean_header_key(self, text):
+        """清洗表头：去除换行、空格、制表符，只保留纯文本"""
+        if not isinstance(text, str): return str(text)
+        return re.sub(r'[\s\n\r]+', '', text)
+
+    def safe_float(self, val):
+        try:
+            if isinstance(val, str):
+                val = val.replace(',', '').replace('¥', '').replace('$', '').strip()
+                if val == '': return 0.0
+            if pd.isna(val): return 0.0
+            return float(val)
+        except:
+            return 0.0
+
+    def format_money_str(self, val):
+        if pd.isna(val) or str(val).strip() == "": return ""
+        try:
+            f_val = self.safe_float(val)
+            return "{:.2f}".format(f_val)
+        except:
+            return str(val)
+
+    def format_percent_str(self, val):
+        if pd.isna(val) or str(val).strip() == "": return ""
+        try:
+            s_val = str(val).strip()
+            if '%' in s_val: return s_val
+            f_val = self.safe_float(val)
+            return "{:.2f}%".format(f_val * 100)
+        except:
+            return str(val)
+
+    def format_date_str(self, val):
+        """格式化日期：去除时分秒，统一为 YYYY-MM-DD"""
+        if pd.isna(val) or str(val).strip() == "": return ""
+        try:
+            # 如果已经是短日期字符串，直接返回
+            s_val = str(val).strip()
+            # 尝试解析
+            dt = pd.to_datetime(val, errors='coerce')
+            if pd.isnull(dt):
+                return s_val  # 解析失败返回原样
+            return dt.strftime('%Y-%m-%d')
+        except:
+            return str(val)
+
+    def normalize_for_compare(self, val):
+        if pd.isna(val) or val is None: return ""
+        s_val = str(val).strip()
+        if s_val.lower() == 'nan': return ""
+        clean_val = s_val.replace(',', '').replace('%', '')
+        try:
+            f_val = float(clean_val)
+            return "{:.4f}".format(f_val)
+        except:
+            return s_val
+
+    def load_csv(self, file_path):
+        df = None
+        encodings = ['utf-8', 'gbk', 'gb18030']
+        for enc in encodings:
+            try:
+                df = pd.read_csv(file_path, encoding=enc)
+                break
+            except UnicodeDecodeError:
+                continue
+        if df is None:
+            try:
+                df = pd.read_csv(file_path, encoding='gb18030', encoding_errors='replace')
+            except:
+                return None, "无法读取文件，请检查编码。"
+
+        col_factory_general = '厂家'
+        col_factory_detail = '厂家.1' if '厂家.1' in df.columns else '厂家'
+
+        df[col_factory_general] = df[col_factory_general].fillna('').astype(str)
+        df['合同类型'] = df['合同类型'].fillna('').astype(str)
+
+        return df, (col_factory_general, col_factory_detail)
+
+    def parse_buyer_info(self, text):
+        info = {'name': '', 'contact_full': ''}
+        if not isinstance(text, str) or not text.strip(): return info
+        lines = [l.strip() for l in text.split('\n') if l.strip()]
+        if not lines: return info
+        info['name'] = lines[0]
+        info['contact_full'] = " ".join(lines[1:])
+        return info
+
+    def parse_single_line_subject(self, text):
+        res = {'name': '', 'model': '', 'qty': '', 'unit': '', 'price': '', 'sort_price': 0.0}
+        if not isinstance(text, str) or not text.strip(): return res
+        text = text.strip()
+
+        if '/' in text:
+            parts = [p.strip() for p in text.split('/')]
+            if len(parts) >= 1: res['name'] = parts[0]
+            if len(parts) >= 2: res['model'] = parts[1]
+            if len(parts) >= 3:
+                m_qty = re.match(r'^(\d+(\.\d+)?)\s*([\u4e00-\u9fa5a-zA-Z]+)?$', parts[2])
+                if m_qty:
+                    res['qty'] = m_qty.group(1)
+                    res['unit'] = m_qty.group(3) if m_qty.group(3) else ""
+                else:
+                    res['qty'] = parts[2]
+
+            if len(parts) >= 4:
+                res['price'] = parts[3]
+                res['sort_price'] = self.safe_float(parts[3])
+            return res
+
+        name_match = re.search(r'(?:中文品名|中文名称|名称|Name)[:：]\s*(.*?)(?:\n|$)', text, re.IGNORECASE)
+        if name_match:
+            res['name'] = name_match.group(1).strip()
+        else:
+            res['name'] = text.split('\n')[0]
+
+        nums = re.findall(r'\d+(?:\.\d+)?', text.replace(',', ''))
+        if nums:
+            res['sort_price'] = self.safe_float(nums[-1])
+            res['price'] = nums[-1]
+
+        return res
+
+    # === [核心] 总表处理逻辑 ===
+    def process_row_general_expanded(self, row, trade_type, trade_cols, col_factory):
+        # 使用传入的 trade_cols (已是根据ASD/NonASD选择好的标准表头)
+        target_cols = trade_cols
+
+        base_data = {}
+        order_no_raw = str(row.get('合同订单编号', '')).strip()
+        parts_no = order_no_raw.split()
+        base_data['合同编号'] = parts_no[0] if len(parts_no) > 0 else order_no_raw
+        contract_no_col = '外贸合同号' if trade_type == '外贸' else '内贸合同号'
+        base_data[contract_no_col] = " ".join(parts_no[1:]) if len(parts_no) > 1 else ""
+
+        # 财务数据
+        total_amount = self.format_money_str(row.get('合同总额', ''))
+        status = str(row.get('收款状态', '')).strip()
+        received = ""
+        unreceived = ""
+        if '已收' in status:
+            received = total_amount
+            unreceived = self.format_money_str(0)
+
+        # 买方信息
+        if trade_type == '内贸':
+            buyer_raw = str(row.get('合同买方（名称/联系人/电话/邮箱）', ''))
+        else:
+            buyer_raw = str(row.get('进口代理（名称/USCI/地址/联系人/电话/邮箱）', ''))
+            if buyer_raw == '' or buyer_raw == 'nan':
+                buyer_raw = str(row.get('合同买方（名称/联系人/电话/邮箱）', ''))
+        parsed_buyer = self.parse_buyer_info(buyer_raw)
+
+        # 解析标的
+        target_raw = str(row.get('合同标的（品名/型号/数量/单价/总价）', ''))
+        lines = [line.strip() for line in target_raw.split('\n') if line.strip()]
+
+        parsed_items = []
+        if not lines:
+            parsed_items.append({'name': '', 'model': '', 'qty': '', 'unit': '', 'price': '', 'sort_price': 0})
+        else:
+            for line in lines:
+                parsed_items.append(self.parse_single_line_subject(line))
+
+        # 排序并只取第一行
+        parsed_items.sort(key=lambda x: x['sort_price'], reverse=True)
+        best_item = parsed_items[0]
+
+        new_row = {col: "" for col in target_cols}
+
+        new_row['合同编号'] = base_data['合同编号']
+        new_row[contract_no_col] = base_data[contract_no_col]
+        new_row['签署公司'] = row.get('收款账户', '')
+
+        # 日期 (使用新格式化函数)
+        date_raw = row.get('签约日期', '')
+        if '合同签订日期' in new_row: new_row['合同签订日期'] = self.format_date_str(date_raw)
+        if '签订日期' in new_row: new_row['签订日期'] = self.format_date_str(date_raw)
+
+        new_row['销售员'] = row.get('负责人', '')
+        new_row['最终用户单位'] = row.get('客户名称', '')
+
+        # 处理带换行符的列名映射
+        # 通过遍历 target_cols 找到匹配的列
+        for col in target_cols:
+            if "最终用户信息" in col: new_row[col] = row.get('联系人姓名', '')
+            if "买方信息" in col: new_row[col] = parsed_buyer['contact_full']
+
+        new_row['厂家'] = row.get(col_factory, '')
+
+        if '币种' in new_row: new_row['币种'] = row.get('货币(选完产品再改)', '')
+        if '发货港' in new_row: new_row['发货港'] = row.get('发货地', '')
+        if '目的港' in new_row: new_row['目的港'] = row.get('目的港', '')
+
+        new_row['买方单位'] = parsed_buyer['name']
+        if '收货人信息' in new_row: new_row['收货人信息'] = parsed_buyer['name']
+
+        discount_col = '折扣率' if '折扣率' in new_row else '折扣率（％）'
+        if discount_col in new_row: new_row[discount_col] = self.format_percent_str(row.get('折扣率', ''))
+
+        new_row['合同标的'] = best_item['name']
+        if '型号/货号' in new_row: new_row['型号/货号'] = best_item['model']
+        if '型号' in new_row: new_row['型号'] = best_item['model']
+        new_row['数量'] = best_item['qty']
+        new_row['单位'] = best_item['unit']
+        # 合同额 (单行价格)
+        if '合同额' in new_row: new_row['合同额'] = self.format_money_str(best_item['price'])
+
+        # 财务总额 (整单)
+        total_col_name = '总合同额' if '总合同额' in new_row else '合同总额'
+        new_row[total_col_name] = total_amount
+
+        new_row['收款情况'] = status
+        new_row['外购'] = self.format_money_str(row.get('外购产品金额', ''))
+        new_row['已收款'] = received
+        new_row['未收款'] = unreceived
+        new_row['收款日期'] = self.format_date_str(row.get('最新收款日期', ''))
+
+        if '最晚发货期' in new_row: new_row['最晚发货期'] = self.format_date_str(row.get('最晚发货期', ''))
+        if '付款方式' in new_row: new_row['付款方式'] = row.get('付款比例及期限', '')
+        if '发货日期' in new_row: new_row['发货日期'] = ""  # 初始为空
+
+        if '合同币种/美元' in new_row:
+            new_row['合同币种/美元'] = row.get('合同币种/美元', '')
+
+        new_row['_sort_price'] = best_item['sort_price']
+
+        return [new_row]
+
+    # === [核心] 通用总表聚合行生成逻辑 (用于处理多行CSV聚合) ===
+    def generate_general_row_aggregated(self, contract_id, group_df, target_cols, trade_type, is_asd, col_factory):
+        first_row = group_df.iloc[0]
+        # 直接复用单行处理逻辑，因为核心差异在标的聚合，我们在这里做聚合解析
+        # 实际上 process_row_general_expanded 已经包含了标的解析和 Top 1 选取
+        # 但如果是多行CSV记录（例如3行CSV对应同一个合同号），我们需要把所有标的收集起来排序
+
+        all_items = []
+        for _, row in group_df.iterrows():
+            target_raw = str(row.get('合同标的（品名/型号/数量/单价/总价）', ''))
+            lines = [line.strip() for line in target_raw.split('\n') if line.strip()]
+            if lines:
+                for line in lines:
+                    all_items.append(self.parse_single_line_subject(line))
+
+        if not all_items:
+            all_items.append({'name': '', 'model': '', 'qty': '', 'unit': '', 'price': '', 'sort_price': 0})
+
+        all_items.sort(key=lambda x: x['sort_price'], reverse=True)
+        best_item = all_items[0]
+
+        # 构造一个合成的 row，大部分信息取 first_row，标的信息替换为 best_item
+        # 为了复用 process_row_general_expanded 的大量字段映射逻辑，我们构造一个 Series
+        # 但 process_row_general_expanded 内部又会解析一次标的...
+        # 简便做法：修改 process_row_general_expanded 让它接受 item 参数
+        # 或者我们在这里手动构造
+
+        # 重新利用 process_row_general_expanded 生成骨架，然后修正标的数据
+        rows = self.process_row_general_expanded(first_row, trade_type, target_cols, col_factory)
+        final_row = rows[0]
+
+        # 修正标的字段为全局最优
+        final_row['合同标的'] = best_item['name']
+        if '型号/货号' in final_row: final_row['型号/货号'] = best_item['model']
+        if '型号' in final_row: final_row['型号'] = best_item['model']
+        final_row['数量'] = best_item['qty']
+        final_row['单位'] = best_item['unit']
+        if '合同额' in final_row: final_row['合同额'] = self.format_money_str(best_item['price'])
+        final_row['_sort_price'] = best_item['sort_price']
+
+        return final_row
+
+    # === 明细表处理逻辑 ===
+    def process_row_detail(self, row, col_factory, trade_type):
+        if trade_type == '外贸':
+            target_cols = self.cols_foreign_detail
+        else:
+            target_cols = self.cols_domestic_detail
+
+        new_row = {col: "" for col in target_cols}
+        detail_manuf_val = str(row.get(col_factory, ''))
+
+        order_no_raw = str(row.get('合同订单编号', '')).strip()
+        parts_no = order_no_raw.split()
+        new_row['合同编号'] = parts_no[0] if len(parts_no) > 0 else order_no_raw
+        new_row['销售员'] = row.get('负责人', '')
+        new_row['厂家'] = detail_manuf_val
+        new_row['货号'] = row.get('产品编码', '')
+
+        if trade_type == '外贸':
+            new_row['币种'] = row.get('原币种', '')
+        else:
+            new_row['外币币种'] = row.get('原币种', '')
+
+        target_raw = str(row.get('合同标的（品名/型号/数量/单价/总价）', ''))
+        if '/' in target_raw:
+            new_row['合同标的'] = target_raw.split('/')[0].strip()
+        else:
+            new_row['合同标的'] = target_raw.split('\n')[0].strip()
+
+        csv_qty = str(row.get('数量', '')).strip()
+        if csv_qty and csv_qty.lower() != 'nan':
+            new_row['数量'] = csv_qty
+
+        val_product_subtotal = self.safe_float(row.get('产品小计', 0))
+        if '外购' in detail_manuf_val:
+            new_row['外购'] = self.format_money_str(val_product_subtotal)
+            remark = str(row.get('备注', '')).strip()
+            if not remark or remark.lower() == 'nan':
+                outsourced = str(row.get('外购产品明细', '')).strip()
+                new_row['产品描述'] = outsourced if outsourced.lower() != 'nan' else ""
+            else:
+                new_row['产品描述'] = remark
+        else:
+            new_row['外购'] = ""
+            new_row['产品描述'] = row.get('产品名称', '')
+            if '外币报价单价' in new_row: new_row['外币报价单价'] = self.format_money_str(row.get('美元报价', ''))
+            if '报价单价' in new_row: new_row['报价单价'] = self.format_money_str(row.get('美元报价', ''))
+
+            if '报价RMB总价' in new_row: new_row['报价RMB总价'] = self.format_money_str(row.get('产品小计', ''))
+            if '报价总价' in new_row: new_row['报价总价'] = self.format_money_str(row.get('产品小计', ''))
+
+        if '计算汇率' in new_row: new_row['计算汇率'] = self.format_percent_str(row.get('汇率', ''))
+        if '合同币种/美元' in new_row: new_row['合同币种/美元'] = self.format_percent_str(row.get('汇率', ''))
+
+        discount_col = '折扣率' if '折扣率' in new_row else '折扣率（％）'
+        if discount_col in new_row: new_row[discount_col] = self.format_percent_str(row.get('折扣率', ''))
+
+        if '售价RMB单价' in new_row: new_row['售价RMB单价'] = self.format_money_str(row.get('销售单价', ''))
+        if '销售单价' in new_row: new_row['销售单价'] = self.format_money_str(row.get('销售单价', ''))
+
+        if '售价RMB总价' in new_row: new_row['售价RMB总价'] = self.format_money_str(row.get('销售总价', ''))
+        if '销售总价' in new_row: new_row['销售总价'] = self.format_money_str(row.get('销售总价', ''))
+
+        new_row['外购转美元'] = self.format_money_str(row.get('外购转美元', ''))
+        new_row['报价总价美元'] = self.format_money_str(row.get('报价总价美元', ''))
+        new_row['净合同额美元'] = self.format_money_str(row.get('净合同额美元', ''))
+
+        if '报价RMB单价' in new_row: new_row['报价RMB单价'] = self.format_money_str(row.get('报价RMB单价', ''))
+
+        return pd.Series(new_row)
+
+    # OM表处理 (使用聚合)
+    def generate_om_row_aggregated(self, contract_id, group_df, target_cols):
+        first_row = group_df.iloc[0]
+
+        all_items = []
+        for _, row in group_df.iterrows():
+            target_raw = str(row.get('合同标的（品名/型号/数量/单价/总价）', ''))
+            lines = [line.strip() for line in target_raw.split('\n') if line.strip()]
+            if lines:
+                for line in lines:
+                    all_items.append(self.parse_single_line_subject(line))
+
+        if not all_items: all_items.append({'name': '', 'price': '', 'sort_price': 0})
+        all_items.sort(key=lambda x: x['sort_price'], reverse=True)
+        best_item = all_items[0]
+
+        new_row = {col: "" for col in target_cols}
+
+        order_no_raw = str(first_row.get('合同订单编号', '')).strip()
+        parts_no = order_no_raw.split()
+        new_row['合同编号'] = parts_no[0] if len(parts_no) > 0 else order_no_raw
+        new_row['内贸合同号'] = " ".join(parts_no[1:]) if len(parts_no) > 1 else ""
+
+        total_amount = self.format_money_str(first_row.get('合同总额', ''))
+        status = str(first_row.get('收款状态', '')).strip()
+        received = ""
+        unreceived = ""
+        if '已收' in status:
+            received = total_amount
+            unreceived = self.format_money_str(0)
+
+        new_row['签署公司'] = first_row.get('收款账户', '')
+        new_row['签订日期'] = self.format_date_str(first_row.get('签约日期', ''))
+        new_row['销售员'] = first_row.get('负责人', '')
+        new_row['最终用户单位'] = first_row.get('客户名称', '')
+
+        contact_col = '最终用户信息\n联系人、电话、邮箱'
+        if contact_col in new_row: new_row[contact_col] = first_row.get('联系人姓名', '')
+
+        buyer_raw = str(first_row.get('合同买方（名称/联系人/电话/邮箱）', ''))
+        parsed_buyer = self.parse_buyer_info(buyer_raw)
+        new_row['买方单位'] = parsed_buyer['name']
+
+        buyer_info_col = '买方信息\n联系人、电话、邮箱'
+        if buyer_info_col in new_row: new_row[buyer_info_col] = parsed_buyer['contact_full']
+
+        new_row['收款日期'] = self.format_date_str(first_row.get('最新收款日期', ''))
+        new_row['合同标的'] = best_item['name']
+        new_row['_sort_price'] = best_item['sort_price']
+
+        new_row['合同总额'] = total_amount
+        new_row['收款情况'] = status
+        new_row['已收款'] = received
+        new_row['未收款'] = unreceived
+
+        return new_row
+
+    def merge_datasets(self, old_dfs, csv_df, is_asd):
+        col_gen = '厂家'
+        col_det = '厂家.1' if '厂家.1' in csv_df.columns else '厂家'
+
+        if is_asd:
+            df_subset = csv_df[csv_df[col_gen].str.contains('ASD', case=False, na=False)]
+        else:
+            df_subset = csv_df[~csv_df[col_gen].str.contains('ASD', case=False, na=False)]
+
+        csv_foreign = df_subset[df_subset['合同类型'] == '外贸'].copy()
+        csv_domestic = df_subset[df_subset['合同类型'] == '内贸'].copy()
+        csv_om = df_subset[~df_subset['合同类型'].isin(['外贸', '内贸'])].copy()
+
+        result_dfs = {}
+
+        def merge_logic_expanded(old_df, new_rows_list, unique_col, target_columns):
+            if old_df is None or old_df.empty:
+                if not new_rows_list: return pd.DataFrame(columns=target_columns + ['_status'])
+                combined = pd.DataFrame(new_rows_list)
+                combined['_status'] = 'new'
+                return combined
+
+            combined = old_df.copy()
+            for col in target_columns:
+                if col not in combined.columns: combined[col] = ""
+            if '_sort_price' not in combined.columns: combined['_sort_price'] = 0.0
+
+            if unique_col in combined.columns:
+                combined[unique_col] = combined[unique_col].astype(str)
+            if '_status' not in combined.columns: combined['_status'] = ''
+
+            if not new_rows_list: return combined
+
+            new_rows_df = pd.DataFrame(new_rows_list)
+            if unique_col in new_rows_df.columns:
+                new_rows_df[unique_col] = new_rows_df[unique_col].astype(str)
+
+            new_contract_ids = new_rows_df[unique_col].unique()
+            rows_to_append = []
+
+            for cid in new_contract_ids:
+                new_subset = new_rows_df[new_rows_df[unique_col] == cid]
+                old_indices = combined[combined[unique_col] == cid].index
+
+                if len(old_indices) > 0:
+                    first_old_idx = old_indices[0]
+                    new_first_row = new_subset.iloc[0]
+
+                    has_changed = False
+                    for col in target_columns:
+                        if col in new_first_row:
+                            new_val = new_first_row[col]
+                            old_val = combined.at[first_old_idx, col]
+
+                            if str(new_val).strip() != "":
+                                if self.normalize_for_compare(old_val) != self.normalize_for_compare(new_val):
+                                    combined.at[first_old_idx, col] = new_val
+                                    has_changed = True
+
+                    if '_sort_price' in new_first_row:
+                        combined.at[first_old_idx, '_sort_price'] = new_first_row['_sort_price']
+
+                    if has_changed:
+                        combined.at[first_old_idx, '_status'] = 'modified'
+                else:
+                    new_subset_copy = new_subset.copy()
+                    new_subset_copy['_status'] = 'new'
+                    rows_to_append.append(new_subset_copy)
+
+            if rows_to_append:
+                combined = pd.concat([combined] + rows_to_append, ignore_index=True)
+
+            return combined
+
+        # --- 1. 外贸总表 (聚合) ---
+        new_gen_rows = []
+        target_cols_foreign = self.cols_asd_foreign_general if is_asd else self.cols_nonasd_foreign_general
+        if not csv_foreign.empty:
+            grouped = csv_foreign.groupby('合同订单编号')
+            for contract_id, group in grouped:
+                row_data = self.generate_general_row_aggregated(contract_id, group, target_cols_foreign, '外贸', is_asd,
+                                                                col_gen)
+                new_gen_rows.append(row_data)
+
+        old_gen = old_dfs.get('外贸', old_dfs.get('外贸总表', pd.DataFrame(columns=target_cols_foreign)))
+        result_dfs['外贸'] = merge_logic_expanded(old_gen, new_gen_rows, '合同编号', target_cols_foreign)
+
+        # --- 2. 外贸明细 ---
+        if not csv_foreign.empty:
+            new_det = csv_foreign.apply(lambda r: self.process_row_detail(r, col_det, '外贸'), axis=1)
+        else:
+            new_det = pd.DataFrame(columns=self.cols_foreign_detail)
+        old_det = old_dfs.get('外贸明细', pd.DataFrame(columns=self.cols_foreign_detail))
+        result_dfs['外贸明细'] = merge_logic_expanded(old_det, new_det.to_dict('records'), '合同编号',
+                                                      self.cols_foreign_detail)
+
+        # --- 3. 内贸总表 (聚合) ---
+        new_dom_rows = []
+        if not csv_domestic.empty:
+            grouped = csv_domestic.groupby('合同订单编号')
+            for contract_id, group in grouped:
+                row_data = self.generate_general_row_aggregated(contract_id, group, self.cols_domestic_general, '内贸',
+                                                                is_asd, col_gen)
+                new_dom_rows.append(row_data)
+        old_dom_gen = old_dfs.get('内贸', old_dfs.get('内贸总表', pd.DataFrame(columns=self.cols_domestic_general)))
+        result_dfs['内贸'] = merge_logic_expanded(old_dom_gen, new_dom_rows, '合同编号', self.cols_domestic_general)
+
+        # --- 4. 内贸明细 ---
+        if not csv_domestic.empty:
+            new_dom_det = csv_domestic.apply(lambda r: self.process_row_detail(r, col_det, '内贸'), axis=1)
+        else:
+            new_dom_det = pd.DataFrame(columns=self.cols_domestic_detail)
+        old_dom_det = old_dfs.get('内贸明细', pd.DataFrame(columns=self.cols_domestic_detail))
+        result_dfs['内贸明细'] = merge_logic_expanded(old_dom_det, new_dom_det.to_dict('records'), '合同编号',
+                                                      self.cols_domestic_detail)
+
+        # --- 5. OM (聚合) ---
+        new_om_rows = []
+        if not csv_om.empty:
+            grouped = csv_om.groupby('合同订单编号')
+            for contract_id, group in grouped:
+                row_data = self.generate_om_row_aggregated(contract_id, group, self.cols_om)
+                new_om_rows.append(row_data)
+        old_om = old_dfs.get('OM合同', old_dfs.get('其他', pd.DataFrame(columns=self.cols_om)))
+        result_dfs['OM合同'] = merge_logic_expanded(old_om, new_om_rows, '合同编号', self.cols_om)
+
+        return result_dfs
+
+    def apply_formatting_to_all(self, data_dict):
+        for sheet_name, df in data_dict.items():
+            if df.empty: continue
+            for col in self.money_cols:
+                if col in df.columns:
+                    df[col] = df[col].apply(self.format_money_str)
+            for col in self.percent_cols:
+                if col in df.columns:
+                    df[col] = df[col].apply(self.format_percent_str)
+            for col in self.date_cols:
+                if col in df.columns:
+                    df[col] = df[col].apply(self.format_date_str)
+        return data_dict
+
+
+# ==========================================
+# 第二部分：GUI 界面
+# ==========================================
+
+class ContractApp:
+    def __init__(self, root):
+        self.root = root
+        self.root.title("合同数据处理系统 V3.8 (换行符修复版)")
+        self.root.geometry("1300x850")
+
+        self.style = ttk.Style()
+        self.style.theme_use('clam')
+        self.colors = {'bg': '#F5F6FA', 'primary': '#409EFF', 'success': '#67C23A', 'warning': '#E6A23C',
+                       'text': '#2C3E50', 'panel': '#FFFFFF'}
+        self.root.configure(bg=self.colors['bg'])
+        self.default_font = ("微软雅黑", 10)
+        self.header_font = ("微软雅黑", 11, "bold")
+        self.style.configure("TFrame", background=self.colors['bg'])
+        self.style.configure("Panel.TFrame", background=self.colors['panel'], relief="flat")
+        self.style.configure("TLabel", background=self.colors['panel'], foreground=self.colors['text'],
+                             font=self.default_font)
+        self.style.configure("Header.TLabel", font=("微软雅黑", 16, "bold"), background=self.colors['bg'],
+                             foreground=self.colors['text'])
+        self.style.configure("TButton", font=("微软雅黑", 10), borderwidth=0, padding=6)
+        self.style.map("TButton", background=[('active', '#E0E0E0')])
+        self.style.configure("Primary.TButton", background=self.colors['primary'], foreground='white')
+        self.style.map("Primary.TButton", background=[('active', '#66B1FF')])
+        self.style.configure("Success.TButton", background=self.colors['success'], foreground='white')
+        self.style.map("Success.TButton", background=[('active', '#85CE61')])
+        self.style.configure("Treeview", background="white", foreground="black", fieldbackground="white", rowheight=28,
+                             font=("微软雅黑", 9))
+        self.style.configure("Treeview.Heading", font=("微软雅黑", 10, "bold"), background="#EBEEF5",
+                             foreground="#606266")
+        self.style.map("Treeview", background=[('selected', '#409EFF')])
+
+        self.processor = DataProcessor()
+        self.csv_path = tk.StringVar()
+        self.asd_path = tk.StringVar()
+        self.non_asd_path = tk.StringVar()
+
+        self.final_data = {}
+        self.create_widgets()
+
+    def create_widgets(self):
+        header_frame = ttk.Frame(self.root)
+        header_frame.pack(fill="x", padx=20, pady=(20, 10))
+        ttk.Label(header_frame, text="📄 合同数据处理工具 (支持 OM合同)", style="Header.TLabel").pack(side="left")
+
+        input_panel = ttk.Frame(self.root, style="Panel.TFrame", padding=20)
+        input_panel.pack(fill="x", padx=20, pady=5)
+        ttk.Label(input_panel, text="文件配置 (若未选择旧文件，将自动生成新文件)", font=self.header_font).grid(row=0,
+                                                                                                              column=0,
+                                                                                                              columnspan=3,
+                                                                                                              sticky="w",
+                                                                                                              pady=(0,
+                                                                                                                    15))
+        self.create_file_row(input_panel, "📂 导入 CSV 源文件:", self.csv_path, 1)
+        self.create_file_row(input_panel, "📘 旧 ASD Excel 文件:", self.asd_path, 2)
+        self.create_file_row(input_panel, "📗 旧 非ASD Excel 文件:", self.non_asd_path, 3)
+        btn_frame = ttk.Frame(input_panel, style="Panel.TFrame")
+        btn_frame.grid(row=4, column=0, columnspan=3, pady=(15, 0), sticky="e")
+        ttk.Button(btn_frame, text="▶ 开始处理并预览", style="Primary.TButton", command=self.process_files).pack(
+            side="right")
+        self.notebook = ttk.Notebook(self.root)
+        self.notebook.pack(fill="both", expand=True, padx=20, pady=10)
+        bottom_bar = ttk.Frame(self.root, style="Panel.TFrame", padding=15)
+        bottom_bar.pack(fill="x", padx=20, pady=(0, 20))
+        legend_frame = ttk.Frame(bottom_bar, style="Panel.TFrame")
+        legend_frame.pack(side="left")
+        self.create_legend(legend_frame, "■ 新增数据", "#FFFFCC", "black")
+        self.create_legend(legend_frame, "■ 有修改/变动", "#ECF5FF", "#409EFF")
+        self.create_legend(legend_frame, "□ 无变动", "white", "black")
+        ttk.Button(bottom_bar, text="💾 保存更改至 Excel", style="Success.TButton", command=self.save_files).pack(
+            side="right")
+
+    def create_file_row(self, parent, label_text, var, row_idx):
+        ttk.Label(parent, text=label_text, width=20).grid(row=row_idx, column=0, sticky="w", pady=5)
+        entry = ttk.Entry(parent, textvariable=var, font=("微软雅黑", 9))
+        entry.grid(row=row_idx, column=1, sticky="ew", padx=10, pady=5)
+        ttk.Button(parent, text="浏览", command=lambda: self.browse_file(var)).grid(row=row_idx, column=2, padx=5)
+        parent.columnconfigure(1, weight=1)
+
+    def create_legend(self, parent, text, bg_color, fg_color):
+        lbl = tk.Label(parent, text=text, bg=bg_color, fg=fg_color, font=("微软雅黑", 9), padx=8, pady=3, borderwidth=1,
+                       relief="solid")
+        lbl.pack(side="left", padx=5)
+
+    def browse_file(self, variable):
+        f = filedialog.askopenfilename(filetypes=[("Excel/CSV Files", "*.csv;*.xlsx")])
+        if f: variable.set(f)
+
+    def load_excel_safe(self, path):
+        if not path or not os.path.exists(path):
+            return {}
+        try:
+            dfs = pd.read_excel(path, sheet_name=None)
+            clean_dfs = {}
+            for k, v in dfs.items():
+                # [关键修复] 智能表头匹配：重命名表头为标准格式
+                new_columns = []
+                for col in v.columns:
+                    clean_col = self.processor.clean_header_key(str(col))
+                    # 尝试在标准映射里找
+                    if clean_col in self.processor.standard_col_map:
+                        new_columns.append(self.processor.standard_col_map[clean_col])
+                    # 尝试在旧映射里找
+                    elif col in self.processor.legacy_map:
+                        new_columns.append(self.processor.legacy_map[col])
+                    else:
+                        new_columns.append(col)  # 找不到就保留原样
+                v.columns = new_columns
+
+                # 去重
+                v = v.loc[:, ~v.columns.duplicated()]
+
+                if '合同编号' in v.columns:
+                    v['合同编号'] = v['合同编号'].astype(str)
+                clean_dfs[k.strip()] = v
+            return clean_dfs
+        except Exception as e:
+            messagebox.showwarning("读取错误", f"读取旧文件失败: {path}\n错误: {str(e)}")
+            return {}
+
+    def process_files(self):
+        if not self.csv_path.get():
+            messagebox.showerror("提示", "请先选择 CSV 源文件！")
+            return
+        csv_df, headers = self.processor.load_csv(self.csv_path.get())
+        if csv_df is None:
+            messagebox.showerror("错误", headers)
+            return
+        self.final_data = {}
+
+        path_asd = self.asd_path.get()
+        asd_old = self.load_excel_safe(path_asd)
+        self.final_data['ASD'] = self.processor.merge_datasets(asd_old, csv_df, True)
+
+        path_non = self.non_asd_path.get()
+        non_old = self.load_excel_safe(path_non)
+        self.final_data['NonASD'] = self.processor.merge_datasets(non_old, csv_df, False)
+
+        self.final_data['ASD'] = self.processor.apply_formatting_to_all(self.final_data['ASD'])
+        self.final_data['NonASD'] = self.processor.apply_formatting_to_all(self.final_data['NonASD'])
+
+        self.refresh_preview()
+        messagebox.showinfo("完成", "数据处理完成！\n请查看预览，确认无误后点击下方保存。")
+
+    def refresh_preview(self):
+        for tab in self.notebook.tabs():
+            self.notebook.forget(tab)
+
+        for file_type in ['ASD', 'NonASD']:
+            if file_type not in self.final_data: continue
+
+            data_dict = self.final_data[file_type]
+            main_frame = ttk.Frame(self.notebook, style="Panel.TFrame")
+            self.notebook.add(main_frame, text=f" {file_type} 文件预览 ")
+            inner_notebook = ttk.Notebook(main_frame)
+            inner_notebook.pack(fill="both", expand=True, padx=5, pady=5)
+
+            sheet_order = ['外贸', '外贸明细', '内贸', '内贸明细', 'OM合同']
+            for sheet_name in sheet_order:
+                if sheet_name in data_dict:
+                    df = data_dict[sheet_name]
+                    if not df.empty:
+                        if '合同编号' in df.columns:
+                            df['合同编号'] = df['合同编号'].astype(str)
+
+                            sort_cols = ['合同编号']
+                            asc_order = [True]
+                            if '_sort_price' in df.columns:
+                                sort_cols.append('_sort_price')
+                                asc_order.append(False)
+                            df = df.sort_values(by=sort_cols, ascending=asc_order)
+
+                            if '明细' in sheet_name:
+                                mask = df.duplicated(subset=['合同编号'], keep='first')
+                                df.loc[mask, '合同标的'] = ""
+
+                        standard_cols = []
+                        is_asd = (file_type == 'ASD')
+
+                        if sheet_name == '外贸':
+                            standard_cols = self.processor.cols_asd_foreign_general if is_asd else self.processor.cols_nonasd_foreign_general
+                        elif sheet_name == '内贸':
+                            standard_cols = self.processor.cols_domestic_general
+                        elif sheet_name == 'OM合同':
+                            standard_cols = self.processor.cols_om
+                        elif sheet_name == '外贸明细':
+                            standard_cols = self.processor.cols_foreign_detail
+                        elif sheet_name == '内贸明细':
+                            standard_cols = self.processor.cols_domestic_detail
+
+                        self.create_treeview(inner_notebook, df, sheet_name, standard_cols)
+
+    def create_treeview(self, parent, df, title, target_cols):
+        frame = ttk.Frame(parent)
+        parent.add(frame, text=title)
+
+        scroll_y = ttk.Scrollbar(frame, orient="vertical")
+        scroll_x = ttk.Scrollbar(frame, orient="horizontal")
+
+        # 仅显示标准列
+        display_cols = target_cols
+
+        tree = ttk.Treeview(frame, columns=display_cols, show='headings',
+                            yscrollcommand=scroll_y.set, xscrollcommand=scroll_x.set)
+
+        scroll_y.config(command=tree.yview)
+        scroll_x.config(command=tree.xview)
+        scroll_y.pack(side="right", fill="y")
+        scroll_x.pack(side="bottom", fill="x")
+        tree.pack(fill="both", expand=True)
+
+        for col in display_cols:
+            # 清洗显示名称（换行变空格，防止表头太高）
+            clean_header = col.replace('\n', ' ')
+            tree.heading(col, text=clean_header)
+            tree.column(col, width=120, anchor="center")
+
+        tree.tag_configure('new', background='#FFFFCC')
+        tree.tag_configure('modified', background='#ECF5FF', foreground='#409EFF')
+
+        if not df.empty:
+            df_display = df.fillna("")
+            last_contract_id = None
+
+            for idx, row in df_display.iterrows():
+                values = []
+                for col in display_cols:
+                    val = row.get(col, "")
+                    if '明细' in title and col == '合同标的':
+                        current_id = row.get('合同编号', '')
+                        if current_id == last_contract_id:
+                            val = ""
+                    values.append(val)
+
+                if '明细' in title:
+                    last_contract_id = row.get('合同编号', '')
+
+                status = row.get('_status', '')
+                tree.insert("", "end", values=values, tags=(status,))
+
+        tree.bind("<Double-1>", lambda event: self.on_double_click(event, tree, df))
+
+    def on_double_click(self, event, tree, df):
+        region = tree.identify("region", event.x, event.y)
+        if region != "cell": return
+        column = tree.identify_column(event.x)
+        row_id = tree.identify_row(event.y)
+        col_idx = int(column.replace('#', '')) - 1
+        col_name = tree['columns'][col_idx]
+        current_val = tree.item(row_id, "values")[col_idx]
+        new_val = simpledialog.askstring("快速编辑", f"修改 [{col_name}]:", initialvalue=current_val, parent=self.root)
+        if new_val is not None:
+            current_values = list(tree.item(row_id, "values"))
+            current_values[col_idx] = new_val
+            tree.item(row_id, values=current_values)
+
+    def save_files(self):
+        if not self.final_data: return
+        base_dir = os.path.dirname(self.csv_path.get()) if self.csv_path.get() else ""
+        try:
+            for file_type, sheets in self.final_data.items():
+                target_path = ""
+                if file_type == 'ASD':
+                    target_path = self.asd_path.get()
+                    if not target_path: target_path = os.path.join(base_dir, "ASD_Combined.xlsx")
+                elif file_type == 'NonASD':
+                    target_path = self.non_asd_path.get()
+                    if not target_path: target_path = os.path.join(base_dir, "NonASD_Combined.xlsx")
+
+                with pd.ExcelWriter(target_path, engine='openpyxl') as writer:
+                    valid_sheets = ['外贸', '外贸明细', '内贸', '内贸明细', 'OM合同']
+                    for sheet_name in valid_sheets:
+                        if sheet_name in sheets:
+                            df = sheets[sheet_name]
+
+                            if '合同编号' in df.columns:
+                                sort_cols = ['合同编号']
+                                asc_order = [True]
+                                if '_sort_price' in df.columns:
+                                    sort_cols.append('_sort_price')
+                                    asc_order.append(False)
+                                df = df.sort_values(by=sort_cols, ascending=asc_order)
+
+                            save_df = df.drop(columns=['_status', '_sort_price'], errors='ignore')
+
+                            if not save_df.empty:
+                                if '明细' in sheet_name:
+                                    mask = save_df.duplicated(subset=['合同编号'], keep='first')
+                                    save_df.loc[mask, '合同标的'] = ""
+                                save_df.to_excel(writer, sheet_name=sheet_name, index=False)
+            messagebox.showinfo("成功", f"文件保存成功！\n位置: {base_dir or '当前目录'}")
+        except PermissionError:
+            messagebox.showerror("保存失败", "文件被占用！\n请先关闭 Excel 文件后再点击保存。")
+        except Exception as e:
+            messagebox.showerror("保存失败", str(e))
+
+
+if __name__ == "__main__":
+    root = tk.Tk()
+    app = ContractApp(root)
+    root.mainloop()