1.新增gitignore文件

2.新启动脚本制作

.gitignore

@@ -0,0 +1,179 @@
+### Python template
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+### 默认 template
+# IntelliJ 文件
+.idea
+*.iml
+out
+gen
+
+# 数据文件
+*.csv
+*.xlsx
+*.xls
+
+# 环境文件
+.vscode
+.conda

app/module/F6_Plugin_module.py

@@ -9,12 +9,15 @@ F6 后台执行模块
 - 车辆信息管理
 - 项目信息批量启停
 - 材料信息批量修改
+- 项目信息批量修改
 
 依赖:
 - requests: HTTP 请求
 - pandas: Excel 文件处理
 - threading: 后台任务处理
 """
+import logging
+import traceback
 import requests
 from urllib.parse import quote
 import pandas as pd
@@ -36,6 +39,7 @@ from app.tasks.delete_tasks import (
 from app.tasks.material_tasks import (
     batch_disable_projects,
     batch_modify_materials,
+    batch_modify_projects
 )
 from app.tasks.customer_tasks import modify_customer_info_background
 from app.tasks.bi_tasks import bi_task_background
@@ -43,6 +47,8 @@ from app.tasks.bi_tasks import bi_task_background
 # 简道云 API 实例，用于调用简道云 API
 api_instance = API()
 
+logger = logging.getLogger('app')
+
 
 class F6PluginModule:
     """
@@ -170,8 +176,38 @@ class F6PluginModule:
                     else:
                         print("'msg':'文件上传格式错误'")
                         return {'msg': '文件上传格式错误'}
-                elif action == 'delete_cars':
+                elif action == 'disable_project':
-                    pass
+                    df1 = pd.read_excel(save_path, sheet_name=0)
+                    if "项目编码" in df1.columns[0]:  # 校验表头名字
+                        print('文件校验成功')
+                        return {'msg': f'{save_path}', 'check': '是'}
+                    else:
+                        print("'msg':'文件上传格式错误'")
+                        return {'msg': '文件上传格式错误'}
+                elif action == 'batch_modify_materials':
+                    df2 = pd.read_excel(save_path, sheet_name=0)
+                    required_columns = {'原材料编码', '新材料编码', '品牌', '名称', '规格'}
+                    actual_columns = set(df2.columns)
+                    if required_columns.issubset(actual_columns):
+                        print('文件校验成功')
+                        return {'msg': f'{save_path}', 'check': '是'}
+                    else:
+                        missing = required_columns - actual_columns
+                        print(f"文件上传格式错误：缺少列 {missing}")
+                        return {'msg': '文件上传格式错误'}
+
+                elif action == 'batch_modify_projects':
+                    df3 = pd.read_excel(save_path, sheet_name=0)
+                    required_columns = {'原项目编码', '新项目编码', '项目名称', '业务分类', '销项税率', '项目说明',
+                                        }
+                    actual_columns = set(df3.columns)
+                    if required_columns.issubset(actual_columns):
+                        print('文件校验成功')
+                        return {'msg': f'{save_path}', 'check': '是'}
+                    else:
+                        missing = required_columns - actual_columns
+                        print(f"文件上传格式错误：缺少列 {missing}")
+                        return {'msg': '文件上传格式错误'}
                 else:
                     pass
 
@@ -409,6 +445,7 @@ class F6PluginModule:
         Returns:
             Dict[str, str]: 包含执行状态的字典，{'msg': '正在执行', 'msg_details': '正在执行，请稍后看结果'}
         """
+        try:
             entry_data = api_instance.entry_data_get(data=data, replace=True)
             print('执行 项目批量停用/启用')
             username = entry_data['data']['账号']
@@ -419,30 +456,41 @@ class F6PluginModule:
 
             login_response = F6Module.login_in(username, password, company_name)
             if login_response is None:
+                logger.error(f"F6系统登录失败，用户名: {username}")
                 return {'msg': '登录失败'}
 
             try:
                 df = pd.read_excel(save_path, sheet_name=0, dtype='string')
             except Exception as e:
+                logger.error(f"读取Excel文件失败: {save_path}, 错误: {str(e)}, 堆栈: {traceback.format_exc()}")
                 return {'msg': f'读取Excel文件失败: {str(e)},文件路径：{save_path}'}
 
             cookies = requests.utils.dict_from_cookiejar(login_response.cookies)
+            logger.info("当前登录cookies:{}".format(cookies))
 
             try:
                 thread = threading.Thread(target=batch_disable_projects,
                                           args=(data, cookies, df, save_path, option))
                 thread.start()
             except Exception as e:
+                logger.error(f"创建线程失败: {str(e)}, 堆栈: {traceback.format_exc()}")
                 print(f'创建线程失败: {str(e)}')
+                return {'msg': f'创建后台线程失败: {str(e)}'}
 
             return {'msg': '正在执行', 'msg_details': '正在执行，请稍后看结果'}
+        except KeyError as e:
+            logger.error(f"数据字段缺失: {str(e)}, 堆栈: {traceback.format_exc()}")
+            return {'msg': f'数据字段缺失: {str(e)}'}
+        except Exception as e:
+            logger.error(f"项目批量启停任务执行失败: {str(e)}, 堆栈: {traceback.format_exc()}")
+            return {'msg': f'执行失败: {str(e)}'}
 
     @staticmethod
-    def disable_material(data: Dict[str, Any]) -> Dict[str, str]:
+    def modify_material(data: Dict[str, Any]) -> Dict[str, str]:
         """
-        材料批量启停
+        材料批量修改
 
-        从简道云获取材料批量启停请求，读取 Excel 文件，并在后台线程中批量启停材料。
+        从简道云获取材料批量修改请求，读取 Excel 文件，并在后台线程中批量修改材料。
         立即返回"正在执行"的提示，实际创建在后台线程中执行。
 
         Args:
@@ -451,38 +499,100 @@ class F6PluginModule:
         Returns:
             Dict[str, str]: 包含执行状态的字典，{'msg': '正在执行', 'msg_details': '正在执行，请稍后看结果'}
         """
+        try:
             entry_data = api_instance.entry_data_get(data=data, replace=True)
-        print('执行 材料批量停用/启用')
+            print('执行 材料信息批量修改')
             username = entry_data['data']['账号']
             password = entry_data['data']['密码']
             company_name = entry_data['data']['公司名称']
             save_path = entry_data['data']['文件保存地址']
-        option = entry_data['data']['项目材料批量操作']
 
             login_response = F6Module.login_in(username, password, company_name)
             if login_response is None:
+                logger.error(f"F6系统登录失败，用户名: {username}")
                 return {'msg': '登录失败'}
 
             try:
                 df = pd.read_excel(save_path, sheet_name=0, dtype='string')
             except Exception as e:
+                logger.error(f"读取Excel文件失败: {save_path}, 错误: {str(e)}, 堆栈: {traceback.format_exc()}")
                 return {'msg': f'读取Excel文件失败: {str(e)},文件路径：{save_path}'}
 
             cookies = requests.utils.dict_from_cookiejar(login_response.cookies)
 
             try:
                 thread = threading.Thread(target=batch_modify_materials,
-                                      args=(data, cookies, df, save_path, option))
+                                          args=(data, cookies, df, save_path))
                 thread.start()
             except Exception as e:
+                logger.error(f"创建线程失败: {str(e)}, 堆栈: {traceback.format_exc()}")
                 print(f'创建线程失败: {str(e)}')
+                return {'msg': f'创建后台线程失败: {str(e)}'}
 
             return {'msg': '正在执行', 'msg_details': '正在执行，请稍后看结果'}
+        except KeyError as e:
+            logger.error(f"数据字段缺失: {str(e)}, 堆栈: {traceback.format_exc()}")
+            return {'msg': f'数据字段缺失: {str(e)}'}
+        except Exception as e:
+            logger.error(f"材料批量修改任务执行失败: {str(e)}, 堆栈: {traceback.format_exc()}")
+            return {'msg': f'执行失败: {str(e)}'}
+
+    @staticmethod
+    def modify_project(data: Dict[str, Any]) -> Dict[str, str]:
+        """
+        项目批量修改
+
+        从简道云获取项目批量修改请求，读取 Excel 文件，并在后台线程中批量修改项目。
+        立即返回"正在执行"的提示，实际创建在后台线程中执行。
+
+        Args:
+            data: 包含表单ID(api_key)、表单ID(entry_id)、数据ID(data_id)的字典
+
+        Returns:
+            Dict[str, str]: 包含执行状态的字典，{'msg': '正在执行', 'msg_details': '正在执行，请稍后看结果'}
+        """
+        try:
+            entry_data = api_instance.entry_data_get(data=data, replace=True)
+            print('执行 项目信息批量修改')
+            username = entry_data['data']['账号']
+            password = entry_data['data']['密码']
+            company_name = entry_data['data']['公司名称']
+            save_path = entry_data['data']['文件保存地址']
+
+            login_response = F6Module.login_in(username, password, company_name)
+            if login_response is None:
+                logger.error(f"F6系统登录失败，用户名: {username}")
+                return {'msg': '登录失败'}
+
+            try:
+                df = pd.read_excel(save_path, sheet_name=0, dtype='string')
+            except Exception as e:
+                logger.error(f"读取Excel文件失败: {save_path}, 错误: {str(e)}, 堆栈: {traceback.format_exc()}")
+                return {'msg': f'读取Excel文件失败: {str(e)},文件路径：{save_path}'}
+
+            cookies = requests.utils.dict_from_cookiejar(login_response.cookies)
+
+            try:
+                thread = threading.Thread(target=batch_modify_projects,
+                                          args=(data, cookies, df, save_path))
+                thread.start()
+            except Exception as e:
+                logger.error(f"创建线程失败: {str(e)}, 堆栈: {traceback.format_exc()}")
+                print(f'创建线程失败: {str(e)}')
+                return {'msg': f'创建后台线程失败: {str(e)}'}
+
+            return {'msg': '正在执行', 'msg_details': '正在执行，请稍后看结果'}
+        except KeyError as e:
+            logger.error(f"数据字段缺失: {str(e)}, 堆栈: {traceback.format_exc()}")
+            return {'msg': f'数据字段缺失: {str(e)}'}
+        except Exception as e:
+            logger.error(f"项目批量修改任务执行失败: {str(e)}, 堆栈: {traceback.format_exc()}")
+            return {'msg': f'执行失败: {str(e)}'}
 
     @staticmethod
     def bi_task(data: Dict[str, Any]) -> Dict[str, str]:
         """
-        BI任务
+        BI任务（示例）
         
         从简道云获取BI任务请求，读取 Excel 文件（如果需要），并在后台线程中执行BI任务。
         立即返回"正在执行"的提示，实际执行在后台线程中完成。

app/tasks/__init__.py

@@ -30,6 +30,7 @@ from app.tasks.customer_tasks import modify_customer_info_background
 from app.tasks.bi_tasks import bi_task_background
 
 from app.tasks.material_tasks import ( \
+    batch_modify_projects,
     batch_modify_materials,
     batch_disable_projects
 )
@@ -51,4 +52,5 @@ __all__ = [
     # 项目材料任务
     'batch_disable_projects',
     'batch_modify_materials',
+    'batch_modify_projects',
 ]

app/tasks/common.py

@@ -137,7 +137,7 @@ def execute_failure_handler(data: Dict[str, Any]):
     api_instance.data_batch_create(pay_load)
 
 
-def get_operate_org_id(cookies: Dict[str, str]) -> Optional[str]:
+def get_operate_org_id(cookies: Dict[str, str], data: Dict[str, str] = None) -> Optional[str]:
     """
     获取操作门店ID
 
@@ -145,6 +145,7 @@ def get_operate_org_id(cookies: Dict[str, str]) -> Optional[str]:
 
     Args:
         cookies: 用户登录 F6 系统的 cookies 信息
+        data:数据id等
 
     Returns:
         Optional[str]: 门店ID，如果获取失败返回 None
@@ -156,13 +157,22 @@ def get_operate_org_id(cookies: Dict[str, str]) -> Optional[str]:
 
     try:
         org_res = requests.get(url=org_url, cookies=cookies)
+        logger.info(org_res.json())
         org_data = org_res.json().get("data", {})
         org_list = org_data.get("list", [])
 
         if not org_list or len(org_list) == 0:
             logger.error("未获取到门店信息")
             return None
-        
+        if data:
+            entry_data = api_instance.entry_data_get(data=data, replace=True)
+            org_name = entry_data.get("data", {}).get("门店名称")
+            operate_org_id = [
+                item["orgId"]
+                for item in org_list
+                if item.get("abbrName") == org_name
+            ]
+        else:
             operate_org_id = org_list[0].get("orgId")
         if not operate_org_id:
             logger.error("门店ID为空")
@@ -217,6 +227,7 @@ def get_card_list(
         if extract_func is None:
             def default_extract(card_item: Dict) -> Optional[str]:
                 return card_item.get("idCustomer")
+
             extract_func = default_extract
 
         # 分页获取所有会员卡数据
@@ -240,5 +251,3 @@ def get_card_list(
     except Exception as e:
         logger.error(f"获取会员卡列表时发生错误: {e}")
         return card_list
-
-

app/tasks/material_tasks.py

@@ -11,11 +11,9 @@ import logging
 import traceback
 import requests
 import time
-from typing import Dict, Any, List, Optional
+from typing import Dict, Any
-from datetime import datetime
 from tqdm import tqdm
-from app.tasks.common import update_jiandaoyun, approve_workflow, get_operate_org_id, get_card_list, \
+from app.tasks.common import update_jiandaoyun, approve_workflow, get_operate_org_id
-    execute_failure_handler
 import pandas as pd
 import os
 
@@ -25,7 +23,7 @@ logger = logging.getLogger('app')
 def batch_disable_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.DataFrame, save_path: str,
                            option) -> None:
     """
-        项目批量停用后台任务
+        项目批量启停后台任务
 
         在后台线程中批量停用项目，从 Excel 文件中读取项目编码。
         执行完成后会更新简道云表单并自动提交工作流。
@@ -45,53 +43,105 @@ def batch_disable_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd
             - 执行完成后会自动删除上传的文件
             - 执行结果会更新到简道云表单
         """
+    logger.info(f"开始执行项目批量启停任务，操作类型: {option}, 文件路径: {save_path}, 数据行数: {len(df)}")
     if option == "批量启用":
         type_ = 0  # 1 停用,0启用
+        ob_type = 1
     else:
         type_ = 1
+        ob_type = 0
+    logger.info(f"操作类型设置完成: type_={type_}, ob_type={ob_type}")
     df = df.where(pd.notnull(df), None)
 
     # 获取门店id
-    org_id = get_operate_org_id(data)
+    logger.info("正在获取门店ID...")
+    try:
+        org_id = get_operate_org_id(cookies)
+        logger.info(f"门店ID获取成功: {org_id}")
+    except Exception as e:
+        logger.error(f"获取门店ID失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+        raise
+    
     # 获取项目信息
+    logger.info("开始获取项目列表...")
     json_data = {
         'param': '',
         'name': '',
         'customCode': '',
         'currentPage': 1,
         'pageSize': 100,
-        'isDel': -type_,
+        'isDel': ob_type,
         'customInvoiceCategory': 0,
         'idOwnOrg': org_id,
     }
 
+    try:
         response = requests.post(
             'https://ids-goods.f6car.cn/f6-ids-goods/service/getServiceList',
             cookies=cookies,
             json=json_data,
         )
+        time.sleep(1)
+        response.raise_for_status()
         all_project_list = []
-    total_pages = response.json().get("data", {}).get("totalPages", "")
+        total_pages = response.json().get("data", {}).get("totalPages", 0)
+        logger.info(f"获取项目列表响应: {response.json()}")
+        try:
+            total_pages = int(total_pages)
+        except (ValueError, TypeError):
+            logger.error(f"无法解析总页数: {total_pages}, 类型: {type(total_pages)}")
+            total_pages = 0
+        logger.info(f"项目列表总页数: {total_pages}")
+        
         for page in tqdm(range(1, total_pages + 1)):
-        json_data['currentPage'] = str(page)
+            json_data['currentPage'] = page
+            try:
                 response = requests.post(
                     'https://ids-goods.f6car.cn/f6-ids-goods/service/getServiceList',
                     cookies=cookies,
                     json=json_data,
                 )
+                time.sleep(1)
+                response.raise_for_status()
                 project_list = response.json().get("data", {}).get("records", [])
                 all_project_list.extend(project_list)
-
+                logger.debug(f"第{page}页获取到{len(project_list)}条项目")
+            except requests.exceptions.RequestException as e:
+                logger.error(f"获取第{page}页项目列表失败: {str(e)}, 响应状态码: {getattr(e.response, 'status_code', 'N/A')}")
+                raise
+        logger.info(f"项目列表获取完成，总计: {len(all_project_list)}条项目")
+    except requests.exceptions.RequestException as e:
+        logger.error(f"获取项目列表失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+        raise
     # 遍历获取到的项目信息停用文件中的项目
     code_list = df.iloc[:, 0].dropna().astype(str).tolist()
-    res_data_list = []
+    logger.info(f"Excel文件中待处理的项目编码数量: {len(code_list)}")
     results = []
+    consecutive_failures = 0  # 连续失败计数器
+    MAX_CONSECUTIVE_FAILURES = 100  # 最大连续失败次数
+    success_count = 0
+    failure_count = 0
+    
+    logger.info("开始处理项目启停操作...")
     for item in tqdm(all_project_list):
         custom_code = item.get("customCode")
-        if not custom_code or str(custom_code) not in code_list or not code_list:
+        if not code_list or not custom_code or str(custom_code) not in code_list:
             continue
+        
+        logger.debug(f"正在处理项目编码: {custom_code}")
         info_id = item.get("infoId")
         pk_id = item.get("pkId")
+        if not info_id or not pk_id:
+            logger.warning(f"项目编码 {custom_code} 缺少必要字段: infoId={info_id}, pkId={pk_id}")
+            results.append({'项目编码': custom_code, '状态': '缺少必要字段(infoId或pkId)'})
+            failure_count += 1
+            consecutive_failures += 1
+            if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                results.append({'项目编码': '系统保护', '状态': '连续100次失败已终止'})
+                logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+                break
+            continue
+        
         json_data = {
             "orgIdList": [
                 org_id,
@@ -103,28 +153,70 @@ def batch_disable_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd
             "idOwnOrg": org_id
         }
         try:
+            logger.debug(f"发送启停请求，项目编码: {custom_code}, 操作类型: {type_}")
             response = requests.post(
                 'https://ids-goods.f6car.cn/f6-ids-goods/service/editAttributeByType',
                 cookies=cookies,
                 json=json_data,
             )
-            res_data_list.append(response.json())
+            time.sleep(2)
             response.raise_for_status()  # 抛出HTTP错误
-            results.append({'材料编码': custom_code, '状态': '停用/启用成功'})
+            # 检查业务响应码
+            resp_data = response.json()
+            if resp_data.get("code") == 200:
+                results.append({'项目编码': custom_code, '状态': '停用/启用成功'})
+                success_count += 1
+                consecutive_failures = 0  # 成功时重置计数器
+                logger.info(f"项目编码 {custom_code} 启停操作成功")
+            else:
+                msg = resp_data.get("message", "未知错误")
+                results.append({'项目编码': custom_code, '状态': f'停用/启用失败: {msg}'})
+                failure_count += 1
+                consecutive_failures += 1
+                logger.error(f"项目编码 {custom_code} 启停操作失败: {msg}, 响应数据: {resp_data}")
         except requests.exceptions.RequestException as e:
-            results.append({'材料编码': custom_code, '状态': f'停用/启用失败: {str(e)}'})
+            error_msg = str(e)
-            pass
+            results.append({'项目编码': custom_code, '状态': f'停用/启用失败: {error_msg}'})
+            failure_count += 1
+            consecutive_failures += 1
+            logger.error(f"项目编码 {custom_code} 启停操作请求异常: {error_msg}, 堆栈信息: {traceback.format_exc()}")
+        
+        # 检查连续失败次数
+        if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+            results.append({'项目编码': '系统保护', '状态': '连续100次失败已终止'})
+            logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+            break
+    
+    logger.info(f"项目启停处理完成，成功: {success_count}条, 失败: {failure_count}条, 总计: {len(results)}条")
 
     print({'msg': '已执行', 'msg_details': f'{results}'})
     logger.info(f"停用/启用结果: {results}")
-    os.remove(save_path)
-    print(f'{save_path}已删除')
-    # 调用api回写改掉 执行明细与执行状态
-    msg = update_jiandaoyun(data, f'{results}')
     
+    # 删除文件
+    logger.info(f"准备删除文件: {save_path}")
+    try:
+        os.remove(save_path)
+        logger.info(f"文件删除成功: {save_path}")
+        print(f'{save_path}已删除')
+    except Exception as e:
+        logger.error(f"删除文件失败: {save_path}, 错误信息: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+    
+    # 调用api回写改掉 执行明细与执行状态
+    logger.info("开始回写简道云表单...")
+    try:
+        msg = update_jiandaoyun(data, f'{results}')
+        logger.info(f"简道云表单回写结果: {msg}")
         if msg.get('msg'):
+            logger.info("开始自动提交工作流...")
             approve_workflow(data)
+            logger.info("工作流提交成功")
             print('表单已自动提交至下一步')
+        else:
+            logger.warning(f"简道云表单回写失败: {msg}")
+    except Exception as e:
+        logger.error(f"回写简道云表单失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+    
+    logger.info(f"项目批量启停任务执行完成，操作类型: {option}")
 
 
 def batch_modify_materials(data: Dict[str, Any], cookies: Dict[str, str], df: pd.DataFrame, save_path: str) -> None:
@@ -147,6 +239,7 @@ def batch_modify_materials(data: Dict[str, Any], cookies: Dict[str, str], df: pd
         - 执行完成后会自动删除上传的文件
         - 执行结果会更新到简道云表单
     """
+    logger.info(f"开始执行材料批量修改任务，文件: {save_path}，行数: {len(df)}")
 
     def safe_str(val):
         """将值转为字符串，NaN 返回空字符串"""
@@ -159,7 +252,13 @@ def batch_modify_materials(data: Dict[str, Any], cookies: Dict[str, str], df: pd
         return not (pd.isna(new_val) or (isinstance(new_val, str) and new_val.strip() == ""))
 
     # 获取门店id
-    org_id = get_operate_org_id(data)
+    logger.info("正在获取门店ID...")
+    try:
+        org_id = get_operate_org_id(cookies)
+        logger.info(f"门店ID获取成功: {org_id}")
+    except Exception as e:
+        logger.error(f"获取门店ID失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+        raise
 
     # 第一步：获取所有材料列表（分页）
     json_data = {
@@ -182,6 +281,7 @@ def batch_modify_materials(data: Dict[str, Any], cookies: Dict[str, str], df: pd
         'getThirdPlatformCode': 0,
     }
 
+    try:
         response = requests.post(
             'https://ids-goods.f6car.com/f6-ids-goods/part/getExactPartStockInfo',
             cookies=cookies,
@@ -189,24 +289,37 @@ def batch_modify_materials(data: Dict[str, Any], cookies: Dict[str, str], df: pd
         )
         response.raise_for_status()
         total_pages = response.json().get("data", {}).get("totalPages", 0)
+        logger.info(f"材料列表页数: {total_pages}")
 
         all_materials_list = []
+        total_pages = int(total_pages)
         for page in tqdm(range(1, total_pages + 1), desc="获取材料列表"):
             json_data['currentPage'] = page
+            try:
                 resp = requests.post(
                     'https://ids-goods.f6car.com/f6-ids-goods/part/getExactPartStockInfo',
                     cookies=cookies,
                     json=json_data,
                 )
+                time.sleep(1)
                 resp.raise_for_status()
                 records = resp.json().get("data", {}).get("records", [])
                 all_materials_list.extend(records)
+            except requests.exceptions.RequestException as e:
+                logger.error(f"获取第{page}页材料列表失败: {str(e)}, 响应状态码: {getattr(e.response, 'status_code', 'N/A')}")
+                raise
+        logger.info(f"材料列表获取完成，总计: {len(all_materials_list)}条")
+    except requests.exceptions.RequestException as e:
+        logger.error(f"获取材料列表失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+        raise
 
     # 第二步：构建 update_map（只存原始值，不预处理）
     update_map = {}
+    skipped_count = 0
     for _, row in df.iterrows():
         orig_code = row.iloc[0]  # 原材料编码
         if pd.isna(orig_code) or str(orig_code).strip() == "":
+            skipped_count += 1
             continue
         orig_code = str(orig_code).strip()
         update_map[orig_code] = {
@@ -215,9 +328,16 @@ def batch_modify_materials(data: Dict[str, Any], cookies: Dict[str, str], df: pd
             "new_name": row.iloc[3],
             "new_spec": row.iloc[4],
         }
+    logger.info(f"待更新材料数: {len(update_map)}，跳过空编码行: {skipped_count}")
 
     # 第三步：遍历材料，按需更新
     results = []
+    consecutive_failures = 0  # 连续失败计数器
+    MAX_CONSECUTIVE_FAILURES = 100  # 最大连续失败次数
+    success_count = 0
+    failure_count = 0
+    skip_count = 0
+    
     for item in tqdm(all_materials_list, desc="处理材料更新"):
         custom_code = item.get("customCode")
         if not custom_code or str(custom_code) not in update_map:
@@ -225,7 +345,15 @@ def batch_modify_materials(data: Dict[str, Any], cookies: Dict[str, str], df: pd
 
         part_id = item.get("partId")
         if not part_id:
-            results.append({'材料编码': custom_code, '状态': '缺少 partId'})
+            error_msg = '缺少 partId'
+            results.append({'材料编码': custom_code, '状态': error_msg})
+            failure_count += 1
+            consecutive_failures += 1
+            logger.warning(f"材料编码 {custom_code} 跳过/失败: {error_msg}")
+            if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                results.append({'材料编码': '系统保护', '状态': '连续100次失败已终止'})
+                logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+                break
             continue
 
         try:
@@ -240,13 +368,30 @@ def batch_modify_materials(data: Dict[str, Any], cookies: Dict[str, str], df: pd
                 params=params,
                 cookies=cookies,
             )
+            time.sleep(1)
             if materials_response.status_code != 200:
-                results.append({'材料编码': custom_code, '状态': f'获取明细失败: {materials_response.status_code}'})
+                error_msg = f'获取明细失败: {materials_response.status_code}'
+                results.append({'材料编码': custom_code, '状态': error_msg})
+                failure_count += 1
+                consecutive_failures += 1
+                logger.error(f"材料编码 {custom_code} {error_msg}, 响应内容: {materials_response.text[:200]}")
+                if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                    results.append({'材料编码': '系统保护', '状态': '连续100次失败已终止'})
+                    logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+                    break
                 continue
 
             detail = materials_response.json().get("data")
             if not detail:
-                results.append({'材料编码': custom_code, '状态': '明细为空'})
+                error_msg = '明细为空'
+                results.append({'材料编码': custom_code, '状态': error_msg})
+                failure_count += 1
+                consecutive_failures += 1
+                logger.error(f"材料编码 {custom_code} {error_msg}, 响应JSON: {materials_response.json()}")
+                if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                    results.append({'材料编码': '系统保护', '状态': '连续100次失败已终止'})
+                    logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+                    break
                 continue
 
             updates = update_map[str(custom_code)]
@@ -277,33 +422,84 @@ def batch_modify_materials(data: Dict[str, Any], cookies: Dict[str, str], df: pd
                 cookies=cookies,
                 json=detail
             )
+            time.sleep(2)
 
             if update_resp.status_code == 200 and update_resp.json().get("code") == 200:
                 results.append({'材料编码': custom_code, '状态': '修改成功'})
+                success_count += 1
+                consecutive_failures = 0  # 成功时重置计数器
             else:
                 msg = update_resp.json().get("message", "未知错误")
-                results.append({'材料编码': custom_code, '状态': f'修改失败: {msg}'})
+                error_msg = f'修改失败: {msg}'
+                results.append({'材料编码': custom_code, '状态': error_msg})
+                failure_count += 1
+                consecutive_failures += 1
+                logger.error(f"材料编码 {custom_code} {error_msg}, 响应数据: {update_resp.json()}")
 
         except requests.exceptions.RequestException as e:
-            results.append({'材料编码': custom_code, '状态': f'请求异常: {str(e)}'})
+            error_msg = f'请求异常: {str(e)}'
+            results.append({'材料编码': custom_code, '状态': error_msg})
+            failure_count += 1
+            consecutive_failures += 1
+            logger.error(f"材料编码 {custom_code} {error_msg}, 堆栈信息: {traceback.format_exc()}")
         except Exception as e:
-            results.append({'材料编码': custom_code, '状态': f'内部错误: {str(e)}'})
+            error_msg = f'内部错误: {str(e)}'
+            results.append({'材料编码': custom_code, '状态': error_msg})
+            failure_count += 1
+            consecutive_failures += 1
+            logger.error(f"材料编码 {custom_code} {error_msg}, 堆栈信息: {traceback.format_exc()}")
+        
+        # 检查连续失败次数
+        if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+            results.append({'材料编码': '系统保护', '状态': '连续100次失败已终止'})
+            logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+            break
+    
+    # 统计汇总（总行数 / 待处理 / 成功 / 失败 / 跳过）
+    total_rows = len(df)
+    to_process = len(update_map)
+    # results 里可能包含 “缺少 partId” 等失败信息；这里跳过数按空编码行计数即可
+    skip_count = skipped_count
+    summary = {
+        "总行数": total_rows,
+        "待处理": to_process,
+        "成功": success_count,
+        "失败": failure_count,
+        "跳过": skip_count,
+    }
+    results.insert(0, {"汇总": summary})
+    logger.info(f"材料修改汇总: {summary}")
 
     # 第四步：清理与回写
     print({'msg': '已执行', 'msg_details': results})
-    logger.info(f"材料批量修改结果: {results}")
+    # 结果回写包含汇总 + 明细
+    logger.info("材料批量修改完成，开始回写结果")
 
+    # 删除文件
+    logger.info(f"准备删除文件: {save_path}")
     try:
         os.remove(save_path)
+        logger.info(f"文件删除成功: {save_path}")
         print(f'{save_path} 已删除')
     except Exception as e:
-        logger.error(f"删除文件失败: {e}")
+        logger.error(f"删除文件失败: {save_path}, 错误信息: {str(e)}, 堆栈信息: {traceback.format_exc()}")
 
     # 回写简道云
+    logger.info("开始回写简道云表单...")
+    try:
         msg = update_jiandaoyun(data, str(results))
+        logger.info(f"简道云表单回写结果: {msg}")
         if msg.get('msg'):
+            logger.info("开始自动提交工作流...")
             approve_workflow(data)
+            logger.info("工作流提交成功")
             print('表单已自动提交至下一步')
+        else:
+            logger.warning(f"简道云表单回写失败: {msg}")
+    except Exception as e:
+        logger.error(f"回写简道云表单失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+    
+    logger.info("材料批量修改任务执行完成")
 
 
 def batch_modify_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.DataFrame, save_path: str) -> None:
@@ -317,16 +513,18 @@ def batch_modify_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.
         data: 包含表单ID(api_key)、表单ID(entry_id)、数据ID(data_id)的字典
         cookies: 用户登录 F6 系统的 cookies 信息
         df: Excel 文件读取的内容，DataFrame 格式，列顺序为：
-            [0:原项目编码, 1:新项目编码, 2:新项目名称, 3:业务分类,
+            [0:原项目编码, 1:新项目编码, 2:新项目名称, 3:业务分类, 4:销项税率, 5:项目说明]
-             4:销项税率, 5:项目说明, 6:车辆分类, 7:工时单价, 8:工时]
         save_path: Excel 文件保存的地址，执行完成后会删除此文件
 
     注意:
         - 无效的项目编码（None、空字符串）会被跳过
         - Excel 中某字段为空（NaN 或空字符串）时，保留原始项目中的对应字段
+        - 如果新项目名称与系统已有项目名称重复，则跳过处理
+        - 如果Excel中多个行的新项目名称重复，只执行第一条数据，后续重复的会被跳过
         - 执行完成后会自动删除上传的文件
         - 执行结果会更新到简道云表单
     """
+    logger.info(f"开始执行项目批量修改任务，文件: {save_path}，行数: {len(df)}")
 
     def safe_str(val):
         """将值转为字符串，NaN 返回空字符串"""
@@ -347,20 +545,43 @@ def batch_modify_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.
         """判断是否应该用 new_val 更新：非 NaN 且非空字符串"""
         return not (pd.isna(new_val) or (isinstance(new_val, str) and new_val.strip() == ""))
 
+    def safe_iloc(row, idx, default=None):
+        """安全按索引取行值，列数不足时返回 default，避免 IndexError"""
+        try:
+            if idx < len(row):
+                return row.iloc[idx]
+        except (IndexError, KeyError):
+            pass
+        return default
+
     # 获取门店id
-    org_id = get_operate_org_id(data)
+    logger.info("获取门店ID...")
+    try:
+        org_id = get_operate_org_id(cookies)
+        logger.info(f"门店ID获取成功: {org_id}")
+    except Exception as e:
+        logger.error(f"获取门店ID失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+        raise
 
     # 获取服务分类（用于映射业务分类名称 → pkId）
+    logger.info("获取服务分类列表...")
+    try:
         init_add_resp = requests.post(
             'https://ids-goods.f6car.cn/f6-ids-goods/service/initAdd',
             cookies=cookies,
             data={'idOwnOrg': org_id}
         )
+        time.sleep(1)
         init_add_resp.raise_for_status()
         service_category_list = init_add_resp.json().get("data", {}).get("serviceCategory", [])
         category_name_to_pk = {item["name"]: item["pkId"] for item in service_category_list}
+        logger.info(f"服务分类列表获取成功，共{len(category_name_to_pk)}个分类")
+    except requests.exceptions.RequestException as e:
+        logger.error(f"获取服务分类列表失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+        raise
 
     # 第一步：获取所有项目列表（分页）
+    logger.info("获取项目列表...")
     json_data = {
         'param': '',
         'name': '',
@@ -372,6 +593,7 @@ def batch_modify_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.
         'idOwnOrg': org_id,
     }
 
+    try:
         response = requests.post(
             'https://ids-goods.f6car.cn/f6-ids-goods/service/getServiceList',
             cookies=cookies,
@@ -379,57 +601,116 @@ def batch_modify_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.
         )
         response.raise_for_status()
         total_pages = response.json().get("data", {}).get("totalPages", 0)
+        logger.info(f"项目列表总页数: {total_pages}")
 
         all_project_list = []
+        total_pages = int(total_pages)
         for page in tqdm(range(1, total_pages + 1), desc="获取项目列表"):
             json_data['currentPage'] = page
+            try:
                 resp = requests.post(
                     'https://ids-goods.f6car.cn/f6-ids-goods/service/getServiceList',
                     cookies=cookies,
                     json=json_data,
                 )
+                time.sleep(1)
                 resp.raise_for_status()
                 records = resp.json().get("data", {}).get("records", [])
                 all_project_list.extend(records)
+            except requests.exceptions.RequestException as e:
+                logger.error(f"获取第{page}页项目列表失败: {str(e)}, 响应状态码: {getattr(e.response, 'status_code', 'N/A')}")
+                raise
+        logger.info(f"项目列表获取完成，总计: {len(all_project_list)}条项目")
+    except requests.exceptions.RequestException as e:
+        logger.error(f"获取项目列表失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+        raise
+
+    # 构建系统已有项目名称集合（用于检查重复）
+    existing_project_names = set()
+    for project in all_project_list:
+        project_name = project.get("name")
+        if project_name:
+            existing_project_names.add(str(project_name).strip())
+    logger.info(f"系统已有项目名称数: {len(existing_project_names)}")
 
     # 第二步：构建 update_map
+    logger.info("构建更新映射表...")
     update_map = {}
-    for _, row in df.iterrows():
+    skipped_count = 0
-        orig_code = row.iloc[0]
+    category_not_found_count = 0
+    duplicate_name_in_df_count = 0  # DataFrame中重复的新项目名称数量
+    duplicate_name_in_system_count = 0  # 与系统已有项目名称重复的数量
+    seen_new_names = {}  # 用于跟踪DataFrame中已出现的新项目名称，key为新名称，value为第一次出现的原项目编码
+    results = []  # 提前创建results，用于记录跳过的信息
+    
+    for idx, row in df.iterrows():
+        orig_code = safe_iloc(row, 0)
         if pd.isna(orig_code) or str(orig_code).strip() == "":
+            skipped_count += 1
+            results.append({'项目编码': '', '状态': '跳过: 项目编码为空'})
             continue
         orig_code = str(orig_code).strip()
 
-        # 计算工时费 = 单价 * 工时
+        # 检查新项目名称（第2列，索引为2）
-        price = safe_float(row.iloc[7])
+        new_name = safe_iloc(row, 2)
-        work_hour = safe_float(row.iloc[8])
+        if should_update(new_name):
-        amount = None
+            new_name_clean = safe_str(new_name)
-        if price is not None and work_hour is not None:
+            
-            amount = round(price * work_hour, 2)
+            # 检查DataFrame中是否有重复的新项目名称
+            if new_name_clean in seen_new_names:
+                duplicate_name_in_df_count += 1
+                logger.warning(f"DataFrame中项目名称重复，跳过: 原项目编码={orig_code}, 新项目名称={new_name_clean}, 首次出现在原项目编码={seen_new_names[new_name_clean]}")
+                results.append({'项目编码': orig_code, '状态': f'跳过: DataFrame中项目名称重复(首次出现在原项目编码={seen_new_names[new_name_clean]})'})
+                continue
+            
+            # 检查新项目名称是否与系统已有项目名称重复
+            if new_name_clean in existing_project_names:
+                duplicate_name_in_system_count += 1
+                logger.warning(f"新项目名称与系统已有项目名称重复，跳过: 原项目编码={orig_code}, 新项目名称={new_name_clean}")
+                results.append({'项目编码': orig_code, '状态': f'跳过: 新项目名称与系统已有项目名称重复({new_name_clean})'})
+                continue
+            
+            # 记录这个新名称
+            seen_new_names[new_name_clean] = orig_code
 
         # 业务分类映射
-        category_name = row.iloc[3]
+        category_name = safe_iloc(row, 3)
         category_pk = None
+        category_not_found = False
         if should_update(category_name):
             cat_name_clean = safe_str(category_name)
             category_pk = category_name_to_pk.get(cat_name_clean)
             if category_pk is None:
-                logger.warning(f"业务分类 '{cat_name_clean}' 未在系统中找到")
+                logger.warning(f"业务分类 '{cat_name_clean}' 未在系统中找到，项目编码: {orig_code}")
+                category_not_found = True
+                category_not_found_count += 1
+
+        # 列 6/7/8（车辆分类、工时单价、工时）不再传入，固定为 None，不更新这些字段
+        car_category_name = None
+        price = None
+        work_hour = None
+        amount = None
 
         update_map[orig_code] = {
-            "new_customCode": row.iloc[1],
+            "new_customCode": safe_iloc(row, 1),   # 新项目编码
-            "new_name": row.iloc[2],
+            "new_name": safe_iloc(row, 2),         # 新项目名称
             "new_serviceCategoryId": category_pk,
-            "new_taxRate": row.iloc[4],
+            "new_taxRate": safe_iloc(row, 4),
-            "new_memo": row.iloc[5],
+            "new_memo": safe_iloc(row, 5),
-            "new_carCategoryName": row.iloc[6],
+            "new_carCategoryName": car_category_name,
             "new_price": price,
             "new_workHour": work_hour,
             "new_amount": amount,
         }
+    logger.info(f"映射表完成: 待处理={len(update_map)}, 跳过空编码={skipped_count}, 分类未找到={category_not_found_count}, DF重复名={duplicate_name_in_df_count}, 系统重名={duplicate_name_in_system_count}")
 
     # 第三步：遍历项目，按需更新
-    results = []
+    logger.info("开始处理项目更新...")
+    consecutive_failures = 0  # 连续失败计数器
+    MAX_CONSECUTIVE_FAILURES = 100  # 最大连续失败次数
+    success_count = 0
+    failure_count = 0
+    
     for item in tqdm(all_project_list, desc="处理项目更新"):
         custom_code = item.get("customCode")
         if not custom_code or str(custom_code) not in update_map:
@@ -437,7 +718,15 @@ def batch_modify_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.
 
         service_id = item.get("pkId")  # 项目主键
         if not service_id:
-            results.append({'项目编码': custom_code, '状态': '缺少 pkId'})
+            error_msg = '缺少 pkId'
+            results.append({'项目编码': custom_code, '状态': error_msg})
+            failure_count += 1
+            consecutive_failures += 1
+            logger.warning(f"项目编码 {custom_code} {error_msg}")
+            if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                results.append({'项目编码': '系统保护', '状态': '连续100次失败已终止'})
+                logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+                break
             continue
 
         try:
@@ -451,13 +740,30 @@ def batch_modify_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.
                 params=params,
                 cookies=cookies,
             )
+            time.sleep(1)
             if detail_resp.status_code != 200:
-                results.append({'项目编码': custom_code, '状态': f'获取明细失败: {detail_resp.status_code}'})
+                error_msg = f'获取明细失败: {detail_resp.status_code}'
+                results.append({'项目编码': custom_code, '状态': error_msg})
+                failure_count += 1
+                consecutive_failures += 1
+                logger.error(f"项目编码 {custom_code} {error_msg}, 响应内容: {detail_resp.text[:200]}")
+                if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                    results.append({'项目编码': '系统保护', '状态': '连续100次失败已终止'})
+                    logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+                    break
                 continue
 
             detail = detail_resp.json().get("data")
             if not detail:
-                results.append({'项目编码': custom_code, '状态': '明细为空'})
+                error_msg = '明细为空'
+                results.append({'项目编码': custom_code, '状态': error_msg})
+                failure_count += 1
+                consecutive_failures += 1
+                logger.error(f"项目编码 {custom_code} {error_msg}, 响应JSON: {detail_resp.json()}")
+                if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                    results.append({'项目编码': '系统保护', '状态': '连续100次失败已终止'})
+                    logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+                    break
                 continue
 
             updates = update_map[str(custom_code)]
@@ -467,6 +773,18 @@ def batch_modify_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.
                 detail["customCode"] = safe_str(updates["new_customCode"])
             if should_update(updates["new_name"]):
                 name_val = safe_str(updates["new_name"])
+                # 再次检查新项目名称是否与系统已有项目名称重复（防止在构建update_map后系统状态发生变化）
+                if name_val in existing_project_names:
+                    error_msg = f'跳过: 新项目名称与系统已有项目名称重复({name_val})'
+                    results.append({'项目编码': custom_code, '状态': error_msg})
+                    failure_count += 1
+                    consecutive_failures += 1
+                    logger.warning(f"项目编码 {custom_code} {error_msg}")
+                    if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                        results.append({'项目编码': '系统保护', '状态': '连续100次失败已终止'})
+                        logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+                        break
+                    continue
                 detail["name"] = name_val
                 if "showName" in detail:
                     detail["showName"] = name_val
@@ -496,30 +814,79 @@ def batch_modify_projects(data: Dict[str, Any], cookies: Dict[str, str], df: pd.
                 cookies=cookies,
                 json=detail
             )
+            time.sleep(2)
 
             if update_resp.status_code == 200 and update_resp.json().get("code") == 200:
                 results.append({'项目编码': custom_code, '状态': '修改成功'})
+                success_count += 1
+                consecutive_failures = 0  # 成功时重置计数器
             else:
                 msg = update_resp.json().get("message", "未知错误")
-                results.append({'项目编码': custom_code, '状态': f'修改失败: {msg}'})
+                error_msg = f'修改失败: {msg}'
+                results.append({'项目编码': custom_code, '状态': error_msg})
+                failure_count += 1
+                consecutive_failures += 1
+                logger.error(f"项目编码 {custom_code} {error_msg}, 响应数据: {update_resp.json()}")
 
+        except requests.exceptions.RequestException as e:
+            error_msg = f"请求异常: {str(e)}"
+            logger.error(f"项目编码 {custom_code} {error_msg}, 堆栈信息: {traceback.format_exc()}")
+            results.append({'项目编码': custom_code, '状态': error_msg})
+            failure_count += 1
+            consecutive_failures += 1
         except Exception as e:
             error_msg = f"异常: {str(e)}"
-            logger.error(f"项目 {custom_code} 更新出错: {traceback.format_exc()}")
+            logger.error(f"项目编码 {custom_code} 更新出错: {traceback.format_exc()}")
             results.append({'项目编码': custom_code, '状态': error_msg})
+            failure_count += 1
+            consecutive_failures += 1
+        
+        # 检查连续失败次数
+        if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+            results.append({'项目编码': '系统保护', '状态': '连续100次失败已终止'})
+            logger.warning(f"连续失败{MAX_CONSECUTIVE_FAILURES}次，已中止任务执行")
+            break
+    
+    # 汇总插入到结果顶部，便于简道云直接看到统计
+    total_rows = len(df)
+    to_process = len(update_map)
+    skip_count = skipped_count + duplicate_name_in_df_count + duplicate_name_in_system_count
+    summary = {
+        "总行数": total_rows,
+        "待处理": to_process,
+        "成功": success_count,
+        "失败": failure_count,
+        "跳过": skip_count,
+    }
+    results.insert(0, {"汇总": summary})
+    logger.info(f"项目修改汇总: {summary}")
 
     # 第四步：清理与回写
     print({'msg': '已执行', 'msg_details': results})
-    logger.info(f"项目批量修改结果: {results}")
+    logger.info("项目批量修改完成，开始回写结果")
 
+    # 删除文件
+    logger.info(f"准备删除文件: {save_path}")
     try:
         os.remove(save_path)
+        logger.info(f"文件删除成功: {save_path}")
         print(f'{save_path} 已删除')
     except Exception as e:
-        logger.error(f"删除文件失败: {e}")
+        logger.error(f"删除文件失败: {save_path}, 错误信息: {str(e)}, 堆栈信息: {traceback.format_exc()}")
 
     # 回写简道云
+    logger.info("开始回写简道云表单...")
+    try:
         msg = update_jiandaoyun(data, str(results))
+        logger.info(f"简道云表单回写结果: {msg}")
         if msg.get('msg'):
+            logger.info("开始自动提交工作流...")
             approve_workflow(data)
+            logger.info("工作流提交成功")
             print('表单已自动提交至下一步')
+        else:
+            logger.warning(f"简道云表单回写失败: {msg}")
+    except Exception as e:
+        logger.error(f"回写简道云表单失败: {str(e)}, 堆栈信息: {traceback.format_exc()}")
+    
+    logger.info("项目批量修改任务执行完成")

main.py

@@ -74,6 +74,12 @@ async def lifespan(app: FastAPI):
                                  description='短信签名状态')
     core_manager.register_action('modify_customer_info', f6_plugin_module.modify_customer_info, 'f6_plugin_module',
                                  description='修改客户信息')
+    core_manager.register_action('disable_project', f6_plugin_module.disable_projects, 'f6_plugin_module',
+                                 description='项目信息批量启停')
+    core_manager.register_action('batch_modify_materials', f6_plugin_module.modify_material, 'f6_plugin_module',
+                                 description='材料信息批量修改')
+    core_manager.register_action('batch_modify_projects', f6_plugin_module.modify_project, 'f6_plugin_module',
+                                 description='项目信息批量修改')
     core_manager.register_action('bi_task', f6_plugin_module.bi_task, 'f6_plugin_module',
                                  description='BI任务')
     
@@ -86,7 +92,6 @@ async def lifespan(app: FastAPI):
         app.state.app_tools.scheduler.shutdown(wait=False)
     app.state.logger.info("应用关闭")
 
-
 app = FastAPI(
     title="简道云FastAPI服务",
     description="简道云插件后端服务，提供数据同步和处理功能",
@@ -202,8 +207,6 @@ async def general_exception_handler(request: Request, exc: Exception):
             error_code="INTERNAL_ERROR"
         ).model_dump(),
     )
-
-
 # 路由已移动到 app/api/routes.py
 
 
@@ -214,8 +217,8 @@ if __name__ == '__main__':
     当直接运行此文件时，启动 uvicorn 服务器。
     默认配置：
     - 主机: 0.0.0.0 (监听所有网络接口)
-    - 端口: 5003
+    - 端口: 5000
     - 热重载: 关闭 (生产环境建议关闭)
     """
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=5003, reload=False)
+    uvicorn.run(app, host="0.0.0.0", port=5000, reload=False)

requirements.txt

@@ -9,3 +9,4 @@ pytesseract==0.3.13
 Requests==2.32.5
 tqdm==4.67.1
 uvicorn==0.40.0
+openpyxl

start_prod.bat

@@ -0,0 +1,54 @@
+@echo off
+title 简道云监听服务 端口5000
+
+:: 切换到应用所在目录（与原始脚本一致）
+cd /d "C:\Users\Administrator\Desktop\简道云\简道云"
+
+:: 激活Anaconda基础环境（或你指定的环境）
+call C:\ProgramData\anaconda3\Scripts\activate.bat
+if %errorlevel% neq 0 (
+    echo 激活Anaconda环境失败，请检查环境配置。
+    pause
+    exit /b 1
+)
+
+:: 验证Python是否可用
+python --version >nul 2>&1
+if %errorlevel% neq 0 (
+    echo 无法找到Python，请检查Anaconda环境是否正确安装。
+    pause
+    exit /b 1
+)
+
+:: 验证uvicorn是否已安装（可选但推荐）
+python -c "import uvicorn" >nul 2>&1
+if %errorlevel% neq 0 (
+    echo 错误：未检测到 uvicorn。请运行以下命令安装：
+    echo     conda install -c conda-forge uvicorn fastapi
+    echo  或
+    echo     pip install "uvicorn[standard]" fastapi
+    pause
+    exit /b 1
+)
+
+:: 设置默认参数（允许通过环境变量覆盖）
+if "%HOST%"=="" set HOST=0.0.0.0
+if "%PORT%"=="" set PORT=5000
+if "%WORKERS%"=="" set WORKERS=1
+if "%LOG_LEVEL%"=="" set LOG_LEVEL=info
+
+set APP_MODULE=main:app
+
+echo.
+echo 启动简道云 FastAPI 服务...
+echo   模块:     %APP_MODULE%
+echo   地址:     http://%HOST%:%PORT%
+echo   进程数:   %WORKERS% （Windows建议设为1）
+echo   日志级别: %LOG_LEVEL%
+echo.
+
+:: 使用 python -m uvicorn 确保调用当前环境中的 uvicorn
+python -m uvicorn %APP_MODULE% --host %HOST% --port %PORT% --workers %WORKERS% --log-level %LOG_LEVEL%
+
+:: 服务退出后暂停，便于查看日志
+pause