添加中行

check_boc.py

@@ -0,0 +1,6 @@
+import pandas as pd
+
+df = pd.read_excel(r'D:\project\caiwu\rijizhang\中行HISXLS-20260128-20260129-0804715541775272430.xls')
+print('所有行数据:')
+for i in range(len(df)):
+    print(f'行{i}:', df.iloc[i].tolist())

check_boc_columns.py

@@ -0,0 +1,6 @@
+import pandas as pd
+
+df = pd.read_excel(r'D:\project\caiwu\rijizhang\中行HISXLS-20260128-20260129-0804715541775272430.xls', header=8)
+print('所有列名:')
+for i, col in enumerate(df.columns):
+    print(f'{i}: {col}')

check_boc_data.py

@@ -0,0 +1,12 @@
+import pandas as pd
+
+df = pd.read_excel(r'D:\project\caiwu\rijizhang\中行HISXLS-20260128-20260129-0804715541775272430.xls', header=8)
+print('数据行数:', len(df))
+print('\n关键字段数据:')
+for i in range(len(df)):
+    print(f'\n行{i}:')
+    print(f'  交易类型: {df.iloc[i]["交易类型[ Transaction Type ]"]}')
+    print(f'  收款人名称: {df.iloc[i]["收款人名称[ Payee\'s Name ]"]}')
+    print(f'  收款人开户行名: {df.iloc[i]["收款人开户行名[ Beneficiary account bank ]"]}')
+    print(f'  摘要: {df.iloc[i]["摘要[ Reference ]"]}')
+    print(f'  交易金额: {df.iloc[i]["交易金额[ Trade Amount ]"]}')

check_params.py

@@ -0,0 +1,5 @@
+import pandas as pd
+
+df = pd.read_excel(r'D:\project\caiwu\rijizhang\参数表.xlsx', sheet_name='账户信息参数', header=1)
+print('参数表中的公司列表:')
+print(df['公司'].tolist())

main.py

@@ -63,6 +63,85 @@ def parse_ccb_flow(flow_file_path):
         messagebox.showerror("错误", f"解析建行流水失败：{str(e)}")
         return None
 
+def parse_boc_flow(flow_file_path):
+    """解析中国银行流水文件，返回标准化的流水数据"""
+    try:
+        # 读取中国银行流水（列名在第8行）
+        flow_df = pd.read_excel(flow_file_path, dtype=str, header=8)
+        
+        # 去除列名中的空格
+        flow_df.columns = flow_df.columns.str.strip()
+        
+        # 检查必要列是否存在
+        required_columns = [
+            "交易类型[ Transaction Type ]",
+            "交易日期[ Transaction Date ]",
+            "交易时间[ Transaction time ]",
+            "交易金额[ Trade Amount ]",
+            "交易后余额[ After-transaction balance ]",
+            "摘要[ Reference ]",
+            "收款人名称[ Payee's Name ]",
+            "收款人开户行名[ Beneficiary account bank ]",
+            "付款人名称[ Payer's Name ]",
+            "付款人开户行名[ Payer account bank ]"
+        ]
+        
+        missing_fields = [k for k in required_columns if k not in flow_df.columns]
+        if missing_fields:
+            messagebox.showerror("错误", f"中国银行流水缺少必要列：{missing_fields}")
+            return None
+        
+        # 构建标准化流水数据
+        standard_flow = []
+        for _, row in flow_df.iterrows():
+            transaction_type = str(row["交易类型[ Transaction Type ]"]).strip()
+            transaction_date = str(row["交易日期[ Transaction Date ]"]).strip()
+            transaction_time = str(row["交易时间[ Transaction time ]"]).strip()
+            amount = pd.to_numeric(row["交易金额[ Trade Amount ]"], errors='coerce')
+            balance = str(row["交易后余额[ After-transaction balance ]"]).strip()
+            reference = str(row["摘要[ Reference ]"]).strip()
+            payee_name = str(row["收款人名称[ Payee's Name ]"]).strip()
+            payee_bank = str(row["收款人开户行名[ Beneficiary account bank ]"]).strip()
+            payer_name = str(row["付款人名称[ Payer's Name ]"]).strip()
+            payer_bank = str(row["付款人开户行名[ Payer account bank ]"]).strip()
+            
+            # 跳过空行
+            if pd.isna(amount) or amount == 0:
+                continue
+            
+            # 根据交易类型确定收支
+            if transaction_type == "往账":
+                income = 0
+                expense = abs(amount)
+                opponent_name = payee_name
+                opponent_bank = payee_bank
+            elif transaction_type == "来账":
+                income = abs(amount)
+                expense = 0
+                opponent_name = payer_name
+                opponent_bank = payer_bank
+            else:
+                continue
+            
+            # 合并日期和时间
+            transaction_datetime = f"{transaction_date} {transaction_time}"
+            
+            standard_flow.append({
+                "交易时间": transaction_datetime,
+                "对方户名": opponent_name,
+                "摘要": reference,
+                "收入": income,
+                "支出": expense,
+                "对方开户机构": opponent_bank,
+                "备注": opponent_bank,
+                "余额": balance
+            })
+        
+        return pd.DataFrame(standard_flow)
+    except Exception as e:
+        messagebox.showerror("错误", f"解析中国银行流水失败：{str(e)}")
+        return None
+
 def generate_journal_data(company_name, bank_name, param_file, flow_file):
     """核心：生成日记账数据"""
     # 1. 加载参数表
@@ -70,8 +149,15 @@ def generate_journal_data(company_name, bank_name, param_file, flow_file):
     if account_params is None:
         return None
     
-    # 2. 解析建行流水
-    flow_df = parse_ccb_flow(flow_file)
+    # 2. 根据银行名称选择不同的解析函数
+    if "中国银行" in bank_name:
+        flow_df = parse_boc_flow(flow_file)
+    elif "建设银行" in bank_name:
+        flow_df = parse_ccb_flow(flow_file)
+    else:
+        messagebox.showerror("错误", f"不支持的银行：{bank_name}")
+        return None
+    
     if flow_df is None:
         return None
     
@@ -145,6 +231,7 @@ def generate_journal_data(company_name, bank_name, param_file, flow_file):
         
         # 基础字段
         journal_row = {
+            "编号": account_code,
             "简称": account_short_name,
             "企业": company_name_full,
             "日期": formatted_date,
@@ -173,8 +260,8 @@ def generate_journal_data(company_name, bank_name, param_file, flow_file):
                 journal_row["资金分类-1级"] = "结算支出"
                 journal_row["资金分类-2级"] = "结算支出"
                 journal_row["资金分类-3级"] = "结算支出"
-        # 规则2：摘要含"手续费" → 财务费用-财务费用-手续费
-        elif "手续费" in str(row["摘要"]):
+        # 规则2：摘要含"手续费"或"对公跨行转账汇款手续费" → 财务费用-财务费用-手续费
+        elif "手续费" in str(row["摘要"]) or "对公跨行转账汇款手续费" in str(row["摘要"]):
             journal_row["资金分类-1级"] = "财务费用"
             journal_row["资金分类-2级"] = "财务费用"
             journal_row["资金分类-3级"] = "手续费"
@@ -198,7 +285,7 @@ def generate_journal_data(company_name, bank_name, param_file, flow_file):
     journal_df = pd.DataFrame(journal_data)
     # 确保列顺序匹配参考日记账
     journal_columns = [
-        "简称", "企业", "日期", "月份", "收支",
+        "编号", "简称", "企业", "日期", "月份", "收支",
         "资金分类-1级", "资金分类-2级", "资金分类-3级", "对手户", "备注", "发生额", "余额", "备注.1"
     ]
     journal_df = journal_df[journal_columns]
@@ -217,8 +304,9 @@ def select_param_file():
 
 def select_flow_file():
     """选择银行流水文件"""
+    bank = bank_var.get()
     file_path = filedialog.askopenfilename(
-        title="选择建行流水文件",
+        title=f"选择{bank}流水文件",
         filetypes=[("Excel文件", "*.xlsx *.xls"), ("所有文件", "*.*")]
     )
     if file_path:
@@ -270,7 +358,7 @@ def generate_journal():
 
 # 初始化GUI
 root = tk.Tk()
-root.title("出纳日记账生成工具（建行版）")
+root.title("出纳日记账生成工具")
 root.geometry("600x300")
 
 # 变量定义
@@ -285,7 +373,7 @@ frame_company = ttk.Frame(root, padding="10")
 frame_company.pack(fill=tk.X)
 ttk.Label(frame_company, text="公司名称：").pack(side=tk.LEFT)
 company_combo = ttk.Combobox(frame_company, textvariable=company_var, state="readonly")
-company_combo["values"] = ["成都锦高量科科技有限公司"]  # 后续可扩展其他公司
+company_combo["values"] = ["成都锦高量科科技有限公司", "成都云启寰宇科技有限公司", "成都橙风有量科技有限公司"]
 company_combo.pack(side=tk.LEFT, padx=5)
 
 # 2. 银行选择
@@ -293,7 +381,7 @@ frame_bank = ttk.Frame(root, padding="10")
 frame_bank.pack(fill=tk.X)
 ttk.Label(frame_bank, text="开户银行：").pack(side=tk.LEFT)
 bank_combo = ttk.Combobox(frame_bank, textvariable=bank_var, state="readonly")
-bank_combo["values"] = ["建设银行"]  # 后续可扩展其他银行
+bank_combo["values"] = ["建设银行", "中国银行"]
 bank_combo.pack(side=tk.LEFT, padx=5)
 
 # 3. 参数表选择