From b518e6aacfa8bdd57824efac926affdddfa0616c Mon Sep 17 00:00:00 2001 From: "shengyudong@yunqueai.net" <“shengyudong@yunqueai.net”> Date: Fri, 16 Jan 2026 18:36:52 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E5=AE=8C=E5=96=84=E4=BB=A3=E7=90=86?= =?UTF-8?q?=E9=87=8D=E8=AF=95=E6=9C=BA=E5=88=B6=EF=BC=8C=E6=B7=BB=E5=8A=A0?= =?UTF-8?q?=E6=95=B0=E6=8D=AE=E9=AA=8C=E8=AF=81=E5=91=8A=E8=AD=A6=EF=BC=8C?= =?UTF-8?q?=E6=96=B0=E5=A2=9EREADME=E6=96=87=E6=A1=A3?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 396 + add_single_cookie_to_db.py | 440 + ai_sms/ai_sms/.env.example | 6 + ai_sms/ai_sms/.gitignore | 5 + ai_sms/ai_sms/README.md | 57 + ai_sms/ai_sms/RUN_INSTRUCTIONS.md | 94 + ai_sms/ai_sms/START_HERE.md | 79 + ai_sms/ai_sms/alibabacloud_sample/__init__.py | 1 + ai_sms/ai_sms/alibabacloud_sample/abc.py | 73 + .../alibabacloud_sample/sample - 副本 (2).py | 87 + .../alibabacloud_sample/sample - 副本.py | 87 + ai_sms/ai_sms/alibabacloud_sample/sample.py | 90 + ai_sms/ai_sms/requirements.txt | 1 + ai_sms/ai_sms/run_with_credentials.py | 63 + ai_sms/ai_sms/set_credentials.ps1 | 45 + ai_sms/ai_sms/setup.py | 76 + ai_sms/ai_sms/setup_credentials.py | 41 + ai_sms/ai_sms/test_credentials.py | 83 + ai_sms/ai_sms/快速运行指南.md | 100 + ai_sms/ai_sms/成功运行说明.md | 91 + ai_sms/ai_sms/配置说明.md | 69 + ai_statistics_days.csv | 195 +- batch_import_history.py | 548 + bjh_analytics.py | 296 +- bjh_analytics_date.py | 809 + bjh_daemon.service | 19 +- bjh_data_daemon.py | 8 +- bjh_integrated_data.json | 34564 +--------------- calc_ip.py | 0 data_sync_daemon.py | 221 +- data_validation.py | 769 + data_validation_with_sms.py | 441 + db/ai_statistics_days.sql | 65 +- db/ai_statistics_monthly.sql | 45 + db/ai_statistics_weekly.sql | 45 + deploy_daemon.sh | 105 + export_to_csv.py | 355 +- fetch_date_statistics.py | 680 + import_csv_to_database.py | 200 +- input.txt | 0 query_statistics.py | 0 sms_config.json | 15 + sync_cookies_to_db.py | 73 +- test_validation_sms.bat | 40 + test_validation_sms.sh | 47 + update_day_revenue.py | 151 + validation_report_20251230_102131.txt | 8 + validation_report_20251230_113338.txt | 34 + 参考代码/ai_keyword_crawl/baidu_crawl.py | 6 +- .../ai_keyword_crawl/baidu_crawl_again.py | 6 +- 备份/captured_account_cookies-6677.json | 5619 +++ 安装守护进程服务.bat | 0 手动启动守护进程任务.bat | 0 数据验证短信告警README.md | 341 + 数据验证短信告警使用说明.md | 294 + 55 files changed, 13202 insertions(+), 34781 deletions(-) create mode 100644 README.md create mode 100644 add_single_cookie_to_db.py create mode 100644 ai_sms/ai_sms/.env.example create mode 100644 ai_sms/ai_sms/.gitignore create mode 100644 ai_sms/ai_sms/README.md create mode 100644 ai_sms/ai_sms/RUN_INSTRUCTIONS.md create mode 100644 ai_sms/ai_sms/START_HERE.md create mode 100644 ai_sms/ai_sms/alibabacloud_sample/__init__.py create mode 100644 ai_sms/ai_sms/alibabacloud_sample/abc.py create mode 100644 ai_sms/ai_sms/alibabacloud_sample/sample - 副本 (2).py create mode 100644 ai_sms/ai_sms/alibabacloud_sample/sample - 副本.py create mode 100644 ai_sms/ai_sms/alibabacloud_sample/sample.py create mode 100644 ai_sms/ai_sms/requirements.txt create mode 100644 ai_sms/ai_sms/run_with_credentials.py create mode 100644 ai_sms/ai_sms/set_credentials.ps1 create mode 100644 ai_sms/ai_sms/setup.py create mode 100644 ai_sms/ai_sms/setup_credentials.py create mode 100644 ai_sms/ai_sms/test_credentials.py create mode 100644 ai_sms/ai_sms/快速运行指南.md create mode 100644 ai_sms/ai_sms/成功运行说明.md create mode 100644 ai_sms/ai_sms/配置说明.md create mode 100644 batch_import_history.py create mode 100644 bjh_analytics_date.py create mode 100644 calc_ip.py create mode 100644 data_validation.py create mode 100644 data_validation_with_sms.py create mode 100644 db/ai_statistics_monthly.sql create mode 100644 db/ai_statistics_weekly.sql create mode 100644 deploy_daemon.sh create mode 100644 fetch_date_statistics.py create mode 100644 input.txt create mode 100644 query_statistics.py create mode 100644 sms_config.json create mode 100644 test_validation_sms.bat create mode 100644 test_validation_sms.sh create mode 100644 update_day_revenue.py create mode 100644 validation_report_20251230_102131.txt create mode 100644 validation_report_20251230_113338.txt create mode 100644 备份/captured_account_cookies-6677.json create mode 100644 安装守护进程服务.bat create mode 100644 手动启动守护进程任务.bat create mode 100644 数据验证短信告警README.md create mode 100644 数据验证短信告警使用说明.md diff --git a/README.md b/README.md new file mode 100644 index 0000000..b539642 --- /dev/null +++ b/README.md @@ -0,0 +1,396 @@ +# 百家号数据采集与分析系统 + +## 项目简介 + +本项目是一个面向百家号平台的自动化数据采集、分析与监控系统，支持多账号管理、定时数据同步、数据验证和短信告警等功能。 + +## 核心功能 + +### 1. 数据采集 +- **Cookie管理**：通过mitmproxy自动捕获账号Cookie，支持批量同步至数据库 +- **文章抓取**：抓取百家号文章数据，包括标题、内容、发布时间等 +- **统计数据获取**：获取发文统计（曝光量、阅读量、点击率）和收入数据 + +### 2. 数据分析 +- **多维度统计**：按日/周/月维度生成统计报表 +- **环比计算**：自动计算周环比、月环比增长率 +- **数据导出**：支持导出为CSV格式，便于数据分析 + +### 3. 数据同步 +- **守护进程**：systemd服务，定时自动同步数据 +- **批量导入**：支持历史数据批量导入 +- **增量更新**：支持指定日期的增量数据更新 + +### 4. 数据验证与监控 +- **数据一致性验证**：校验JSON/CSV/数据库三个数据源的一致性 +- **短信告警**：集成阿里云短信服务，数据异常时自动发送告警（错误代码2222） +- **验证报告**：生成详细的验证报告，支持保存到专门目录 + +### 5. 代理管理 +- **天启代理集成**：支持HTTP代理，避免IP限制 +- **智能重试机制**： + - 同一代理最多尝试3次 + - 超时/连接错误立即更换代理 + - 最多更换3次代理（共尝试4个不同代理） +- **错误处理**：自动识别errno=10000015（异常请求），立即更换代理 + +## 技术栈 + +- **Python 3.8+** +- **数据库**：MySQL 8.0+ (pymysql) +- **网络请求**：requests, urllib3 +- **抓包工具**：mitmproxy 10.0+ +- **定时任务**：schedule +- **短信服务**：阿里云短信SDK (alibabacloud_dysmsapi20170525) + +## 项目结构 + +``` +xhh_baijiahao/ +├── db/ # 数据库SQL脚本 +│ ├── ai_articles.sql # 文章表 +│ ├── ai_authors.sql # 作者表 +│ ├── ai_statistics_days.sql # 日统计表 +│ ├── ai_statistics_weekly.sql # 周统计表 +│ └── ai_statistics_monthly.sql # 月统计表 +│ +├── ai_sms/ # 阿里云短信服务 +│ └── ai_sms/ # 短信SDK示例代码 +│ +├── 核心模块 +├── bjh_analytics.py # 百家号数据分析API（主要） +├── bjh_analytics_date.py # 指定日期数据抓取 +├── bjh_articles_crawler.py # 文章爬虫 +├── export_to_csv.py # 数据导出CSV +├── import_csv_to_database.py # CSV导入数据库 +│ +├── Cookie管理 +├── mitmproxy_capture.py # mitmproxy Cookie捕获 +├── 一键捕获Cookie.py # 快速Cookie捕获工具 +├── sync_cookies_to_db.py # 批量Cookie同步 +├── add_single_cookie_to_db.py # 单账号Cookie导入 +├── add_account_from_cookie.py # 从Cookie添加账号 +│ +├── 守护进程与定时任务 +├── data_sync_daemon.py # 数据同步守护进程（主要） +├── bjh_data_daemon.py # 备用守护进程 +├── bjh_daemon.service # systemd服务配置 +├── deploy_daemon.sh # 守护进程部署脚本 +├── install_service.sh # 服务安装脚本 +├── diagnose_service.sh # 服务诊断脚本 +│ +├── 数据验证与告警 +├── data_validation.py # 数据验证核心 +├── data_validation_with_sms.py # 数据验证+短信告警 +├── test_validation_sms.sh # Linux测试脚本 +├── test_validation_sms.bat # Windows测试脚本 +│ +├── 批量任务 +├── batch_import_history.py # 历史数据批量导入 +├── fetch_date_statistics.py # 指定日期统计获取 +├── update_day_revenue.py # 日收益更新 +│ +├── 配置文件 +├── database_config.py # 数据库配置 +├── log_config.py # 日志配置 +├── sms_config.json # 短信服务配置 +├── requirements.txt # Python依赖 +│ +└── 快捷脚本 + ├── 一键捕获Cookie.bat # Windows一键Cookie捕获 + ├── 启动数据同步守护进程.bat # Windows启动守护进程 + └── 抓取百家号文章.bat # Windows文章抓取 +``` + +## 快速开始 + +### 1. 安装依赖 + +```bash +pip install -r requirements.txt +``` + +核心依赖： +- `requests>=2.31.0` +- `pymysql>=1.1.0` +- `mitmproxy>=10.0.0` +- `schedule>=1.2.0` +- `python-dateutil>=2.8.0` + +### 2. 配置数据库 + +编辑 `database_config.py`，配置MySQL连接信息： + +```python +DB_CONFIG = { + 'host': 'your_host', + 'port': 3306, + 'user': 'your_user', + 'password': 'your_password', + 'database': 'ai_article', + 'charset': 'utf8mb4' +} +``` + +### 3. 初始化数据库 + +执行 `db/` 目录下的SQL脚本创建表： + +```bash +mysql -u root -p ai_article < db/ai_authors.sql +mysql -u root -p ai_article < db/ai_articles.sql +mysql -u root -p ai_article < db/ai_statistics_days.sql +mysql -u root -p ai_article < db/ai_statistics_weekly.sql +mysql -u root -p ai_article < db/ai_statistics_monthly.sql +``` + +### 4. 捕获Cookie + +#### Windows: +```bash +一键捕获Cookie.bat +``` + +#### Linux: +```bash +python3 mitmproxy_capture.py +``` + +### 5. 同步Cookie到数据库 + +```bash +python3 sync_cookies_to_db.py +``` + +### 6. 启动数据同步守护进程 + +#### Linux (推荐使用systemd): +```bash +# 部署服务 +sudo bash deploy_daemon.sh + +# 启动服务 +sudo systemctl start bjh_daemon + +# 查看状态 +sudo systemctl status bjh_daemon + +# 查看日志 +journalctl -u bjh_daemon -f +``` + +#### Windows: +```bash +启动数据同步守护进程.bat +``` + +#### 手动运行: +```bash +python3 data_sync_daemon.py +``` + +## 主要功能使用 + +### 批量导入历史数据 + +```bash +python3 batch_import_history.py +``` + +支持交互式选择： +- 账号选择（单个/多个/全部） +- 日期范围设置 +- 是否使用代理 +- 数据库/文件来源选择 + +### 获取指定日期统计数据 + +```bash +python3 fetch_date_statistics.py 2025-12-26 +``` + +### 导出数据为CSV + +```bash +python3 export_to_csv.py +``` + +### 数据验证与短信告警 + +```bash +# 执行验证 +python3 data_validation_with_sms.py + +# 测试短信功能 +python3 data_validation_with_sms.py --test-sms +``` + +验证报告保存在 `validation_reports/` 目录。 + +### 添加单个账号Cookie + +```bash +python3 add_single_cookie_to_db.py +``` + +支持交互式输入： +- Username / 昵称 +- App ID / 领域 +- Cookie (多种格式) + +## 数据库表结构 + +### ai_authors - 作者表 +- `id`: 主键 +- `author_name`: 作者名称（使用username或nick） +- `app_id`: 百家号app_id +- `toutiao_cookie`: Cookie字符串 +- `channel`: 渠道（1=百家号） +- `status`: 状态（active/inactive） + +### ai_statistics_days - 日统计表 +- `author_id`: 作者ID +- `stat_date`: 统计日期 +- `day_revenue`: 当日收益 +- `daily_published_count`: 当日发文量 +- `cumulative_published_count`: 累计发文量 +- 唯一键：`uk_author_stat_date(author_id, channel, stat_date)` + +### ai_statistics_weekly - 周统计表 +- `author_id`: 作者ID +- `stat_weekly`: 周一日期（自然周） +- `weekly_revenue`: 当周收益（从日数据汇总） +- `revenue_wow_growth_rate`: 周环比增长率 + +### ai_statistics_monthly - 月统计表 +- `author_id`: 作者ID +- `stat_monthly`: 每月1日日期 +- `monthly_revenue`: 当月收益（从日数据汇总） +- `revenue_mom_growth_rate`: 月环比增长率 + +## 代理配置 + +项目支持天启代理，API配置在代码中： + +```python +PROXY_API = "http://api.tianqiip.com/getip?secret=xxx&num=1&type=txt&port=1&mr=1&sign=xxx" +``` + +代理特性： +- IP白名单认证，无需账号密码 +- 返回格式：纯文本 `IP:端口` +- 智能重试：超时/连接错误立即更换代理 +- 双重限制：同一代理最多3次，最多更换3次代理 + +## 短信告警配置 + +编辑 `sms_config.json`： + +```json +{ + "access_key_id": "your_access_key_id", + "access_key_secret": "your_access_key_secret", + "sign_name": "your_sign_name", + "template_code": "SMS_486210104", + "phone_numbers": "13621242430", + "endpoint": "dysmsapi.aliyuncs.com" +} +``` + +## 守护进程配置 + +### systemd服务配置 (bjh_daemon.service) + +```ini +[Unit] +Description=百家号数据同步守护进程（含数据验证与短信告警） +After=network.target mysql.service + +[Service] +Type=simple +User=root +WorkingDirectory=/root/xhh_baijiahao +ExecStart=/usr/bin/python3 data_sync_daemon.py +Restart=always + +Environment="LOAD_FROM_DB=true" +Environment="USE_PROXY=true" +Environment="ENABLE_VALIDATION=true" +Environment="NON_INTERACTIVE=true" + +[Install] +WantedBy=multi-user.target +``` + +### 环境变量配置 + +- `LOAD_FROM_DB`: 是否从数据库加载Cookie (true/false) +- `USE_PROXY`: 是否使用代理 (true/false) +- `DAYS`: 抓取天数 (默认7) +- `MAX_RETRIES`: 最大重试次数 (默认3) +- `RUN_NOW`: 是否立即执行 (true/false) +- `ENABLE_VALIDATION`: 是否启用验证 (true/false) +- `NON_INTERACTIVE`: 非交互模式 (true/false) + +## 日志管理 + +日志文件位置： +- 守护进程：`logs/data_sync_daemon.log` +- 数据库操作：`logs/database.log` +- Cookie同步：`logs/cookie_sync.log` +- 验证报告：`validation_reports/validation_report_YYYYMMDD_HHMMSS.txt` + +查看实时日志： +```bash +tail -f logs/data_sync_daemon.log +``` + +## 常见问题 + +### 1. Cookie失效 +- 症状：API返回 `errno=10000015`（异常请求） +- 解决：重新捕获Cookie并同步到数据库 + +### 2. 代理超时 +- 症状：请求超时15秒 +- 解决：系统自动更换新代理，最多尝试4个不同代理 + +### 3. 数据验证失败 +- 症状：短信收到错误代码2222 +- 解决：查看 `validation_reports/` 中的详细报告 + +### 4. 守护进程停止 +- 诊断：`sudo bash diagnose_service.sh` +- 重启：`sudo systemctl restart bjh_daemon` + +## 开发说明 + +### 添加新账号 +1. 使用 `一键捕获Cookie.py` 捕获Cookie +2. 运行 `sync_cookies_to_db.py` 同步到数据库 +3. 或使用 `add_single_cookie_to_db.py` 手动添加 + +### 修改统计维度 +- 日统计：修改 `ai_statistics_days` 表结构 +- 周统计：修改 `ai_statistics_weekly` 表结构 +- 月统计：修改 `ai_statistics_monthly` 表结构 + +### 自定义代理 +修改 `bjh_analytics.py` 和 `bjh_analytics_date.py` 中的代理获取逻辑： +```python +def fetch_proxy(self, force_new: bool = False): + # 自定义代理获取逻辑 + pass +``` + +## 贡献指南 + +欢迎提交Issue和Pull Request！ + +## 许可证 + +本项目仅供学习和研究使用。 + +## 联系方式 + +如有问题，请通过Issue反馈。 diff --git a/add_single_cookie_to_db.py b/add_single_cookie_to_db.py new file mode 100644 index 0000000..a11518e --- /dev/null +++ b/add_single_cookie_to_db.py @@ -0,0 +1,440 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +将单个账号的Cookie输入到MySQL数据库 +支持手动输入Cookie信息或从剪贴板粘贴 +""" + +import json +import sys +import os +from datetime import datetime +from typing import Dict, Optional + +# 导入统一的数据库管理器和日志配置 +from database_config import DatabaseManager, DB_CONFIG +from log_config import setup_cookie_sync_logger + +# 初始化日志记录器 +logger = setup_cookie_sync_logger() + +# 设置UTF-8编码 +if sys.platform == 'win32': + import io + sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8') + sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8') + + +class SingleCookieToDB: + """单个Cookie同步到数据库""" + + def __init__(self, db_config: Optional[Dict] = None): + """ + 初始化数据库连接 + + Args: + db_config: 数据库配置字典，默认使用database_config.DB_CONFIG + """ + self.script_dir = os.path.dirname(os.path.abspath(__file__)) + + # 使用统一的数据库管理器 + self.db_manager = DatabaseManager(db_config) + self.db_config = self.db_manager.config + + def connect_db(self) -> bool: + """连接数据库""" + return self.db_manager.test_connection() + + def close_db(self): + """关闭数据库连接""" + print("[OK] 数据库操作完成") + + def cookie_dict_to_string(self, cookies: Dict) -> str: + """ + 将Cookie字典转换为字符串格式 + + Args: + cookies: Cookie字典 + + Returns: + Cookie字符串，格式: "key1=value1; key2=value2" + """ + return '; '.join([f"{k}={v}" for k, v in cookies.items()]) + + def cookie_string_to_dict(self, cookie_string: str) -> Dict: + """ + 将Cookie字符串转换为字典格式 + + Args: + cookie_string: Cookie字符串，格式: "key1=value1; key2=value2" + + Returns: + Cookie字典 + """ + cookies = {} + for item in cookie_string.split(';'): + item = item.strip() + if '=' in item: + key, value = item.split('=', 1) + cookies[key.strip()] = value.strip() + return cookies + + def find_author_by_name(self, author_name: str, channel: int = 1) -> Optional[Dict]: + """ + 根据作者名称和渠道查找数据库记录 + + Args: + author_name: 作者名称 + channel: 渠道（1=百家号，默认1） + + Returns: + 作者记录字典，未找到返回None + """ + try: + sql = "SELECT * FROM ai_authors WHERE author_name = %s AND channel = %s LIMIT 1" + result = self.db_manager.execute_query(sql, (author_name, channel), fetch_one=True) + return result + except Exception as e: + print(f"[X] 查询作者失败: {e}") + return None + + def update_author_cookie(self, author_id: int, cookie_string: str, + app_id: Optional[str] = None) -> bool: + """ + 更新作者的Cookie信息 + + Args: + author_id: 作者ID + cookie_string: Cookie字符串 + app_id: 百家号app_id（可选） + + Returns: + 是否更新成功 + """ + try: + # 构建更新SQL + update_fields = ["toutiao_cookie = %s", "updated_at = NOW()"] + params = [cookie_string] + + # 如果提供了app_id，也一并更新 + if app_id: + update_fields.append("app_id = %s") + params.append(app_id) + + params.append(author_id) + + sql = f"UPDATE ai_authors SET {', '.join(update_fields)} WHERE id = %s" + self.db_manager.execute_update(sql, tuple(params)) + + logger.info(f"成功更新作者ID={author_id}的Cookie") + return True + except Exception as e: + logger.error(f"更新Cookie失败: {e}", exc_info=True) + print(f"[X] 更新Cookie失败: {e}") + return False + + def insert_new_author(self, author_name: str, cookie_string: str, + app_id: Optional[str] = None, nick: Optional[str] = None, + domain: Optional[str] = None) -> bool: + """ + 插入新作者记录 + + Args: + author_name: 作者名称（用于数据库author_name字段） + cookie_string: Cookie字符串 + app_id: 百家号app_id + nick: 昵称 + domain: 领域 + + Returns: + 是否插入成功 + """ + try: + # 构建插入SQL + sql = """ + INSERT INTO ai_authors + (author_name, app_id, app_token, department_id, department_name, + department, toutiao_cookie, channel, status, created_at, updated_at) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, NOW(), NOW()) + """ + + # 参数 + params = ( + author_name, + app_id or '', + '', # app_token 暂时为空 + 0, # department_id 默认0 + domain or '其它', # department_name 使用领域 + '', # department 暂时为空 + cookie_string, + 1, # channel: 1=baidu + 'active' # status + ) + + self.db_manager.execute_update(sql, params) + logger.info(f"成功创建新作者: {author_name}") + return True + except Exception as e: + logger.error(f"插入新作者失败: {e}", exc_info=True) + print(f"[X] 插入新作者失败: {e}") + return False + + def add_cookie(self, account_info: Dict, auto_create: bool = True) -> bool: + """ + 添加单个账号的Cookie到数据库 + + Args: + account_info: 账号信息字典，包含cookies、username、nick等字段 + auto_create: 当作者不存在时是否自动创建，默认True + + Returns: + 是否添加成功 + """ + # 提取Cookie信息 + cookies = account_info.get('cookies', {}) + if not cookies: + print("[X] Cookie信息为空") + return False + + # 转换Cookie为字符串（如果是字典格式） + if isinstance(cookies, dict): + cookie_string = self.cookie_dict_to_string(cookies) + else: + cookie_string = str(cookies) + + # 提取其他信息（使用username和nick作为author_name进行匹配） + username = account_info.get('username', '').strip() + nick = account_info.get('nick', '').strip() + app_id = account_info.get('app_id', '').strip() + domain = account_info.get('domain', '').strip() + + # 验证username或nick至少有一个存在 + if not username and not nick: + print("[X] username和nick至少需要提供一个") + return False + + print(f"\n账号信息:") + print(f" Username: {username}") + print(f" 昵称: {nick}") + print(f" App ID: {app_id}") + print(f" 领域: {domain}") + + # 查找作者（使用双重匹配机制：先username，后nick） + channel = 1 # 百家号固定为channel=1 + author = None + matched_field = None + + # 1. 首先尝试使用username匹配 + if username: + author = self.find_author_by_name(username, channel) + if author: + matched_field = 'username' + print(f"\n[√] 通过username匹配到作者: {author['author_name']} (ID: {author['id']}, Channel: {author['channel']})") + + # 2. 如果username匹配失败，尝试使用nick匹配 + if not author and nick: + author = self.find_author_by_name(nick, channel) + if author: + matched_field = 'nick' + print(f"\n[√] 通过nick匹配到作者: {author['author_name']} (ID: {author['id']}, Channel: {author['channel']})") + + # 3. 如果都没匹配到 + if not author: + print(f"\n[!] 未找到匹配的作者（已尝试username和nick）") + + # 更新或创建 + if author: + # 更新现有记录 + print(f"\n正在更新作者Cookie...") + success = self.update_author_cookie( + author['id'], + cookie_string, + app_id if app_id else None + ) + + if success: + print(f"[OK] Cookie已更新（匹配字段: {matched_field}）") + return True + else: + print(f"[X] Cookie更新失败") + return False + else: + # 作者不存在，考虑创建 + if auto_create: + # 优先使用username，如果没有则使用nick + author_name_to_create = username if username else nick + print(f"\n正在创建新作者（author_name: {author_name_to_create}）...") + success = self.insert_new_author( + author_name_to_create, + cookie_string, + app_id, + nick, + domain + ) + + if success: + print(f"[OK] 新作者已创建 (author_name: {author_name_to_create})") + return True + else: + print(f"[X] 创建作者失败") + return False + else: + print(f"[X] 作者不存在，且未开启自动创建") + return False + + def run_interactive(self): + """交互式运行模式""" + print("\n" + "="*70) + print("添加单个账号Cookie到数据库") + print("="*70) + + # 连接数据库 + if not self.connect_db(): + logger.error("数据库连接失败，退出") + return + + try: + # 询问是否自动创建不存在的作者 + print("\n当作者不存在时是否自动创建？") + auto_create_input = input("(y/n, 默认y): ").strip().lower() + auto_create = auto_create_input != 'n' + + # 输入账号信息 + print("\n" + "="*70) + print("请输入账号信息:") + print("="*70) + + username = input("\n1. Username (用于匹配数据库author_name): ").strip() + nick = input("2. 昵称 (备用匹配字段): ").strip() + app_id = input("3. App ID (可选): ").strip() + domain = input("4. 领域 (可选): ").strip() + + # 输入Cookie + print("\n" + "="*70) + print("请输入Cookie信息:") + print("提示: 可以输入以下任意格式:") + print(" 1. Cookie字符串: key1=value1; key2=value2") + print(" 2. JSON格式: {\"key1\": \"value1\", \"key2\": \"value2\"}") + print(" 3. 多行输入，输入完成后输入 END 结束") + print("="*70) + + cookie_lines = [] + while True: + line = input().strip() + if line.upper() == 'END': + break + if line: + cookie_lines.append(line) + + cookie_input = ' '.join(cookie_lines) + + # 解析Cookie + cookies = {} + if cookie_input.startswith('{'): + # JSON格式 + try: + cookies = json.loads(cookie_input) + except json.JSONDecodeError: + print("[X] Cookie JSON格式解析失败") + return + else: + # 字符串格式 + cookies = self.cookie_string_to_dict(cookie_input) + + if not cookies: + print("[X] Cookie为空，操作取消") + return + + # 构建账号信息 + account_info = { + 'username': username, + 'nick': nick, + 'app_id': app_id, + 'domain': domain, + 'cookies': cookies + } + + # 确认信息 + print("\n" + "="*70) + print("确认账号信息:") + print("="*70) + print(f" Username: {username}") + print(f" 昵称: {nick}") + print(f" App ID: {app_id}") + print(f" 领域: {domain}") + print(f" Cookie条目数: {len(cookies)}") + print(f" 自动创建: {'是' if auto_create else '否'}") + print("="*70) + + confirm = input("\n确认添加到数据库？(y/n): ").strip().lower() + if confirm != 'y': + print("\n已取消") + return + + # 添加Cookie + success = self.add_cookie(account_info, auto_create) + + if success: + print("\n" + "="*70) + print("添加成功！") + print("="*70) + else: + print("\n" + "="*70) + print("添加失败，请查看错误信息") + print("="*70) + + finally: + # 关闭数据库连接 + self.close_db() + + +def main(): + """主函数""" + print("\n" + "="*70) + print("单个账号Cookie同步工具") + print("="*70) + + # 使用默认配置还是自定义配置 + print("\n请选择数据库配置方式:") + print(" 1. 使用默认配置 (8.149.233.36/ai_statistics_read)") + print(" 2. 自定义配置") + + choice = input("\n请选择 (1/2, 默认1): ").strip() or '1' + + if choice == '2': + # 自定义数据库配置 + print("\n请输入数据库连接信息:\n") + + host = input("数据库地址: ").strip() + port = input("端口 (默认: 3306): ").strip() or '3306' + user = input("用户名: ").strip() + password = input("密码: ").strip() + database = input("数据库名: ").strip() + + db_config = { + 'host': host, + 'port': int(port), + 'user': user, + 'password': password, + 'database': database, + 'charset': 'utf8mb4' + } + else: + # 使用默认配置 + db_config = None + print("\n使用默认数据库配置...") + + # 创建同步器并执行 + syncer = SingleCookieToDB(db_config) + + print("\n配置确认:") + print(f" 数据库: {syncer.db_config['host']}:{syncer.db_config.get('port', 3306)}/{syncer.db_config['database']}") + print(f" 用户: {syncer.db_config['user']}") + print("="*70) + + # 运行交互式模式 + syncer.run_interactive() + + +if __name__ == '__main__': + main() diff --git a/ai_sms/ai_sms/.env.example b/ai_sms/ai_sms/.env.example new file mode 100644 index 0000000..704e691 --- /dev/null +++ b/ai_sms/ai_sms/.env.example @@ -0,0 +1,6 @@ +# Alibaba Cloud Access Credentials +# 请在阿里云控制台获取您的 AccessKey ID 和 AccessKey Secret +# https://ram.console.aliyun.com/manage/ak + +ALIBABA_CLOUD_ACCESS_KEY_ID=your_access_key_id_here +ALIBABA_CLOUD_ACCESS_KEY_SECRET=your_access_key_secret_here diff --git a/ai_sms/ai_sms/.gitignore b/ai_sms/ai_sms/.gitignore new file mode 100644 index 0000000..2bcfffa --- /dev/null +++ b/ai_sms/ai_sms/.gitignore @@ -0,0 +1,5 @@ +runtime/ +.idea/ +.vscode/ +__pycache__/ +.pytest_cache/ \ No newline at end of file diff --git a/ai_sms/ai_sms/README.md b/ai_sms/ai_sms/README.md new file mode 100644 index 0000000..3811e4e --- /dev/null +++ b/ai_sms/ai_sms/README.md @@ -0,0 +1,57 @@ +# 发送短信验证码完整工程示例 + +该项目为SendSmsVerifyCode的完整工程示例。 + +**工程代码建议使用更安全的无AK方式，凭据配置方式请参阅：[管理访问凭据](https://help.aliyun.com/zh/sdk/developer-reference/v2-manage-python-access-credentials)。** + +## 运行条件 + +- 下载并解压需要语言的代码; + +- *要求 Python >= 3.7* + +## 执行步骤 + +完成凭据配置后，可以在**解压代码所在目录下**按如下的步骤执行： + +- **创建并激活虚拟环境：** + ```sh + python -m venv venv && source venv/bin/activate + ``` + +- **安装依赖：** + ```sh + pip install -r requirements.txt + ``` + +- **运行代码** + ```sh + python ./alibabacloud_sample/sample.py + ``` + +## 使用的 API + +- SendSmsVerifyCode：发送短信验证码。 更多信息可参考：[文档](https://next.api.aliyun.com/document/Dypnsapi/2017-05-25/SendSmsVerifyCode) + +## API 返回示例 + +*下列输出值仅作为参考，实际输出结构可能稍有不同，以实际调用为准。* + + +- JSON 格式 +```js +{ + "AccessDeniedDetail": "无", + "Message": "成功 ", + "RequestId": "CC3BB6D2-2FDF-4321-9DCE-B38165CE4C47", + "Model": { + "VerifyCode": "4232", + "RequestId": "a3671ccf-0102-4c8e-8797-a3678e091d09", + "OutId": "1231231313", + "BizId": "112231421412414124123^4" + }, + "Code": "OK", + "Success": true +} +``` + diff --git a/ai_sms/ai_sms/RUN_INSTRUCTIONS.md b/ai_sms/ai_sms/RUN_INSTRUCTIONS.md new file mode 100644 index 0000000..203d75b --- /dev/null +++ b/ai_sms/ai_sms/RUN_INSTRUCTIONS.md @@ -0,0 +1,94 @@ +# 阿里云短信验证码 API 运行说明 + +## 项目配置完成情况 + +✅ 依赖已安装: `alibabacloud_dypnsapi20170525==2.0.0` +✅ 代码已配置: 手机号码 `13621242430`，验证码长度 4 位 +✅ Conda 环境: `douyin` + +## 运行步骤 + +### 1. 配置阿里云访问凭据 + +您需要先获取阿里云的 AccessKey ID 和 AccessKey Secret: +- 访问: https://ram.console.aliyun.com/manage/ak +- 创建或查看您的 AccessKey + +### 2. 设置环境变量 (PowerShell) + +在运行程序前，需要设置环境变量: + +```powershell +$env:ALIBABA_CLOUD_ACCESS_KEY_ID="your_access_key_id" +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="your_access_key_secret" +``` + +### 3. 运行程序 + +```powershell +python ./alibabacloud_sample/sample.py +``` + +## 完整运行示例 (PowerShell) + +```powershell +# 激活 conda 环境 +conda activate douyin + +# 设置凭据 +$env:ALIBABA_CLOUD_ACCESS_KEY_ID="your_access_key_id" +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="your_access_key_secret" + +# 运行程序 +python ./alibabacloud_sample/sample.py +``` + +## 代码说明 + +### 当前配置参数 + +`sample.py` 已配置以下参数: + +```python +send_sms_verify_code_request = dypnsapi_20170525_models.SendSmsVerifyCodeRequest( + phone_number='13621242430', # 接收短信的手机号码 + code_length=4, # 验证码长度 (1314 是 4 位) + code_type=1 # 验证码类型: 1=数字 +) +``` + +### API 返回示例 + +成功时返回: +```json +{ + "Code": "OK", + "Success": true, + "Message": "成功", + "Model": { + "VerifyCode": "1234", + "BizId": "...", + "RequestId": "..." + } +} +``` + +## 注意事项 + +1. **安全性**: 不要将 AccessKey 硬编码在代码中或提交到版本控制系统 +2. **权限**: 确保您的 AccessKey 有发送短信的权限 +3. **费用**: 发送短信会产生费用，请注意阿里云账户余额 +4. **签名和模板**: 某些地区可能需要配置短信签名和模板 + +## 故障排查 + +如果遇到错误: +- 检查 AccessKey 是否正确 +- 检查账户余额是否充足 +- 检查手机号码格式是否正确 +- 查看错误信息中的诊断地址 (Recommend) + +## API 文档 + +- SendSmsVerifyCode API: https://next.api.aliyun.com/document/Dypnsapi/2017-05-25/SendSmsVerifyCode +- 凭据管理: https://help.aliyun.com/zh/sdk/developer-reference/v2-manage-python-access-credentials diff --git a/ai_sms/ai_sms/START_HERE.md b/ai_sms/ai_sms/START_HERE.md new file mode 100644 index 0000000..4a73851 --- /dev/null +++ b/ai_sms/ai_sms/START_HERE.md @@ -0,0 +1,79 @@ +# 开始使用 - 3步运行 + +## ⚠️ 您的错误原因 + +**环境变量未设置！** 错误信息显示: +``` +Environment variable accessKeyId cannot be empty +``` + +## ✅ 解决方案（选一个） + +### 方案 1: 最简单 - 使用测试脚本 + +```powershell +# 第1步: 测试凭据配置 +python test_credentials.py + +# 第2步: 如果提示未设置，在 PowerShell 中运行: +$env:ALIBABA_CLOUD_ACCESS_KEY_ID="您的AccessKey_ID" +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="您的AccessKey_Secret" + +# 第3步: 再次测试 +python test_credentials.py + +# 第4步: 测试通过后运行 +python ./alibabacloud_sample/sample.py +``` + +### 方案 2: 一键运行（交互式） + +```powershell +python run_with_credentials.py +# 脚本会提示您输入 AccessKey，然后自动运行 +``` + +### 方案 3: 手动设置后运行 + +```powershell +# 设置环境变量 +$env:ALIBABA_CLOUD_ACCESS_KEY_ID="LTAI5t..." +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="your_secret_here" + +# 直接运行 +python ./alibabacloud_sample/sample.py +``` + +## 🔑 获取 AccessKey + +https://ram.console.aliyun.com/manage/ak + +## 🔧 已修复的问题 + +1. ✅ 代理超时问题（已禁用 ECS 元数据代理） +2. ✅ 错误处理问题（已修复 AttributeError） +3. ✅ 手机号已配置: 13621242430 +4. ✅ 验证码长度: 4位数字 + +## 📝 当前配置 + +- 手机号: `13621242430` +- 验证码: 4位数字（API自动生成，不能指定为1314） +- 环境: conda douyin +- 依赖: 已安装 + +## ⚡ 快速测试流程 + +```powershell +# 1. 测试凭据 +python test_credentials.py + +# 2. 如果失败，设置环境变量 +$env:ALIBABA_CLOUD_ACCESS_KEY_ID="your_key" +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="your_secret" + +# 3. 运行程序 +python ./alibabacloud_sample/sample.py +``` + +**现在就试试 `python test_credentials.py`！** diff --git a/ai_sms/ai_sms/alibabacloud_sample/__init__.py b/ai_sms/ai_sms/alibabacloud_sample/__init__.py new file mode 100644 index 0000000..5becc17 --- /dev/null +++ b/ai_sms/ai_sms/alibabacloud_sample/__init__.py @@ -0,0 +1 @@ +__version__ = "1.0.0" diff --git a/ai_sms/ai_sms/alibabacloud_sample/abc.py b/ai_sms/ai_sms/alibabacloud_sample/abc.py new file mode 100644 index 0000000..399113c --- /dev/null +++ b/ai_sms/ai_sms/alibabacloud_sample/abc.py @@ -0,0 +1,73 @@ +# -*- coding: utf-8 -*- +# This file is auto-generated, don't edit it. Thanks. +import os +import sys +import json + +from typing import List + +from alibabacloud_dypnsapi20170525.client import Client as Dypnsapi20170525Client +from alibabacloud_credentials.client import Client as CredentialClient +from alibabacloud_tea_openapi import models as open_api_models +from alibabacloud_dypnsapi20170525 import models as dypnsapi_20170525_models +from alibabacloud_tea_util import models as util_models +from alibabacloud_tea_util.client import Client as UtilClient + + +class Sample: + def __init__(self): + pass + + @staticmethod + def create_client() -> Dypnsapi20170525Client: + """ + 使用凭据初始化账号Client + @return: Client + @throws Exception + """ + # 工程代码建议使用更安全的无AK方式，凭据配置方式请参见：https://help.aliyun.com/document_detail/378659.html。 + credential = CredentialClient() + config = open_api_models.Config( + credential=credential + ) + # Endpoint 请参考 https://api.aliyun.com/product/Dypnsapi + config.endpoint = f'dypnsapi.aliyuncs.com' + return Dypnsapi20170525Client(config) + + @staticmethod + def main( + args: List[str], + ) -> None: + client = Sample.create_client() + send_sms_verify_code_request = dypnsapi_20170525_models.SendSmsVerifyCodeRequest() + runtime = util_models.RuntimeOptions() + try: + resp = client.send_sms_verify_code_with_options(send_sms_verify_code_request, runtime) + print(json.dumps(resp, default=str, indent=2)) + except Exception as error: + # 此处仅做打印展示，请谨慎对待异常处理，在工程项目中切勿直接忽略异常。 + # 错误 message + print(error.message) + # 诊断地址 + print(error.data.get("Recommend")) + + @staticmethod + async def main_async( + args: List[str], + ) -> None: + client = Sample.create_client() + send_sms_verify_code_request = dypnsapi_20170525_models.SendSmsVerifyCodeRequest() + runtime = util_models.RuntimeOptions() + try: + resp = await client.send_sms_verify_code_with_options_async(send_sms_verify_code_request, runtime) + print(json.dumps(resp, default=str, indent=2)) + except Exception as error: + # 此处仅做打印展示，请谨慎对待异常处理，在工程项目中切勿直接忽略异常。 + # 错误 message + print(error.message) + # 诊断地址 + print(error.data.get("Recommend")) + + +if __name__ == '__main__': + Sample.main(sys.argv[1:]) \ No newline at end of file diff --git a/ai_sms/ai_sms/alibabacloud_sample/sample - 副本 (2).py b/ai_sms/ai_sms/alibabacloud_sample/sample - 副本 (2).py new file mode 100644 index 0000000..aaa0e6f --- /dev/null +++ b/ai_sms/ai_sms/alibabacloud_sample/sample - 副本 (2).py @@ -0,0 +1,87 @@ +# -*- coding: utf-8 -*- +# This file is auto-generated, don't edit it. Thanks. +import os +import sys +import json + +from typing import List + +from alibabacloud_dypnsapi20170525.client import Client as Dypnsapi20170525Client +from alibabacloud_credentials.client import Client as CredentialClient +from alibabacloud_credentials.models import Config as CredentialConfig +from alibabacloud_tea_openapi import models as open_api_models +from alibabacloud_dypnsapi20170525 import models as dypnsapi_20170525_models +from alibabacloud_tea_util import models as util_models +from alibabacloud_tea_util.client import Client as UtilClient + + +class Sample: + def __init__(self): + pass + + @staticmethod + def create_client() -> Dypnsapi20170525Client: + """ + 使用凭据初始化账号Client + @return: Client + @throws Exception + """ + credential_config = CredentialConfig( + type='access_key', + access_key_id='LTAI5tSMvnCJdqkZtCVWgh8R', + access_key_secret='nyFzXyIi47peVLK4wR2qqbPezmU79W' + ) + credential = CredentialClient(credential_config) + config = open_api_models.Config( + credential=credential + ) + # Endpoint 请参考 https://api.aliyun.com/product/Dypnsapi + config.endpoint = f'dypnsapi.aliyuncs.com' + return Dypnsapi20170525Client(config) + + @staticmethod + def main( + args: List[str], + ) -> None: + client = Sample.create_client() + send_sms_verify_code_request = dypnsapi_20170525_models.SendSmsVerifyCodeRequest( + phone_number='13621242430', + sign_name='阿里云短信', + template_code='SMS_474580174', + template_param='{}', + code_length=4, + code_type=1 + ) + runtime = util_models.RuntimeOptions() + try: + resp = client.send_sms_verify_code_with_options(send_sms_verify_code_request, runtime) + print(json.dumps(resp, default=str, indent=2)) + except Exception as error: + # 此处仅做打印展示，请谨慎对待异常处理，在工程项目中切勿直接忽略异常。 + # 错误 message + print(f"错误: {error}") + # 诊断地址 + if hasattr(error, 'data') and error.data: + print(f"诊断地址: {error.data.get('Recommend')}") + raise + + @staticmethod + async def main_async( + args: List[str], + ) -> None: + client = Sample.create_client() + send_sms_verify_code_request = dypnsapi_20170525_models.SendSmsVerifyCodeRequest() + runtime = util_models.RuntimeOptions() + try: + resp = await client.send_sms_verify_code_with_options_async(send_sms_verify_code_request, runtime) + print(json.dumps(resp, default=str, indent=2)) + except Exception as error: + # 此处仅做打印展示，请谨慎对待异常处理，在工程项目中切勿直接忽略异常。 + # 错误 message + print(error.message) + # 诊断地址 + print(error.data.get("Recommend")) + + +if __name__ == '__main__': + Sample.main(sys.argv[1:]) diff --git a/ai_sms/ai_sms/alibabacloud_sample/sample - 副本.py b/ai_sms/ai_sms/alibabacloud_sample/sample - 副本.py new file mode 100644 index 0000000..841c970 --- /dev/null +++ b/ai_sms/ai_sms/alibabacloud_sample/sample - 副本.py @@ -0,0 +1,87 @@ +# -*- coding: utf-8 -*- +# This file is auto-generated, don't edit it. Thanks. +import os +import sys +import json + +from typing import List + +from alibabacloud_dypnsapi20170525.client import Client as Dypnsapi20170525Client +from alibabacloud_credentials.client import Client as CredentialClient +from alibabacloud_credentials.models import Config as CredentialConfig +from alibabacloud_tea_openapi import models as open_api_models +from alibabacloud_dypnsapi20170525 import models as dypnsapi_20170525_models +from alibabacloud_tea_util import models as util_models +from alibabacloud_tea_util.client import Client as UtilClient + + +class Sample: + def __init__(self): + pass + + @staticmethod + def create_client() -> Dypnsapi20170525Client: + """ + 使用凭据初始化账号Client + @return: Client + @throws Exception + """ + credential_config = CredentialConfig( + type='access_key', + access_key_id='LTAI5tPnLdDkvSxrVJfRZMCn', + access_key_secret='AII2A8hgfxXWM1xYqeuNwnS61AErDz' + ) + credential = CredentialClient(credential_config) + config = open_api_models.Config( + credential=credential + ) + # Endpoint 请参考 https://api.aliyun.com/product/Dypnsapi + config.endpoint = f'dypnsapi.aliyuncs.com' + return Dypnsapi20170525Client(config) + + @staticmethod + def main( + args: List[str], + ) -> None: + client = Sample.create_client() + send_sms_verify_code_request = dypnsapi_20170525_models.SendSmsVerifyCodeRequest( + phone_number='13621242430', + sign_name='阿里云短信', + template_code='SMS_474580174', + template_param='{}', + code_length=4, + code_type=1 + ) + runtime = util_models.RuntimeOptions() + try: + resp = client.send_sms_verify_code_with_options(send_sms_verify_code_request, runtime) + print(json.dumps(resp, default=str, indent=2)) + except Exception as error: + # 此处仅做打印展示，请谨慎对待异常处理，在工程项目中切勿直接忽略异常。 + # 错误 message + print(f"错误: {error}") + # 诊断地址 + if hasattr(error, 'data') and error.data: + print(f"诊断地址: {error.data.get('Recommend')}") + raise + + @staticmethod + async def main_async( + args: List[str], + ) -> None: + client = Sample.create_client() + send_sms_verify_code_request = dypnsapi_20170525_models.SendSmsVerifyCodeRequest() + runtime = util_models.RuntimeOptions() + try: + resp = await client.send_sms_verify_code_with_options_async(send_sms_verify_code_request, runtime) + print(json.dumps(resp, default=str, indent=2)) + except Exception as error: + # 此处仅做打印展示，请谨慎对待异常处理，在工程项目中切勿直接忽略异常。 + # 错误 message + print(error.message) + # 诊断地址 + print(error.data.get("Recommend")) + + +if __name__ == '__main__': + Sample.main(sys.argv[1:]) diff --git a/ai_sms/ai_sms/alibabacloud_sample/sample.py b/ai_sms/ai_sms/alibabacloud_sample/sample.py new file mode 100644 index 0000000..826f4c2 --- /dev/null +++ b/ai_sms/ai_sms/alibabacloud_sample/sample.py @@ -0,0 +1,90 @@ +# -*- coding: utf-8 -*- +# This file is auto-generated, don't edit it. Thanks. +import os +import sys +import json + +from typing import List + +from alibabacloud_dysmsapi20170525.client import Client as Dysmsapi20170525Client +from alibabacloud_credentials.client import Client as CredentialClient +from alibabacloud_credentials.models import Config as CredentialConfig +from alibabacloud_tea_openapi import models as open_api_models +from alibabacloud_dysmsapi20170525 import models as dysmsapi_20170525_models +from alibabacloud_tea_util import models as util_models +from alibabacloud_tea_util.client import Client as UtilClient + + +class Sample: + def __init__(self): + pass + + @staticmethod + def create_client() -> Dysmsapi20170525Client: + """ + 使用凭据初始化账号Client + @return: Client + @throws Exception + """ + credential_config = CredentialConfig( + type='access_key', + access_key_id='LTAI5tSMvnCJdqkZtCVWgh8R', + access_key_secret='nyFzXyIi47peVLK4wR2qqbPezmU79W' + ) + credential = CredentialClient(credential_config) + config = open_api_models.Config( + credential=credential + ) + # Endpoint 请参考 https://api.aliyun.com/product/Dysmsapi + config.endpoint = f'dysmsapi.aliyuncs.com' + return Dysmsapi20170525Client(config) + + @staticmethod + def main( + args: List[str], + ) -> None: + client = Sample.create_client() + send_sms_request = dysmsapi_20170525_models.SendSmsRequest( + phone_numbers='13621242430', + sign_name='北京乐航时代科技', + template_code='SMS_486210104', + template_param=json.dumps({"code": "1314"}) + ) + runtime = util_models.RuntimeOptions() + try: + resp = client.send_sms_with_options(send_sms_request, runtime) + print(json.dumps(resp.to_map(), default=str, indent=2)) + except Exception as error: + # 此处仅做打印展示，请谨慎对待异常处理，在工程项目中切勿直接忽略异常。 + # 错误 message + print(f"错误: {error}") + # 诊断地址 + if hasattr(error, 'data') and error.data: + print(f"诊断地址: {error.data.get('Recommend')}") + raise + + @staticmethod + async def main_async( + args: List[str], + ) -> None: + client = Sample.create_client() + send_sms_request = dysmsapi_20170525_models.SendSmsRequest( + phone_numbers='13621242430', + sign_name='北京乐航时代科技', + template_code='SMS_486210104', + template_param=json.dumps({"code": "1314"}) + ) + runtime = util_models.RuntimeOptions() + try: + resp = await client.send_sms_with_options_async(send_sms_request, runtime) + print(json.dumps(resp.to_map(), default=str, indent=2)) + except Exception as error: + # 此处仅做打印展示，请谨慎对待异常处理，在工程项目中切勿直接忽略异常。 + # 错误 message + print(error.message) + # 诊断地址 + print(error.data.get("Recommend")) + + +if __name__ == '__main__': + Sample.main(sys.argv[1:]) diff --git a/ai_sms/ai_sms/requirements.txt b/ai_sms/ai_sms/requirements.txt new file mode 100644 index 0000000..df9da12 --- /dev/null +++ b/ai_sms/ai_sms/requirements.txt @@ -0,0 +1 @@ +alibabacloud_dypnsapi20170525==2.0.0 \ No newline at end of file diff --git a/ai_sms/ai_sms/run_with_credentials.py b/ai_sms/ai_sms/run_with_credentials.py new file mode 100644 index 0000000..cd9f812 --- /dev/null +++ b/ai_sms/ai_sms/run_with_credentials.py @@ -0,0 +1,63 @@ +# -*- coding: utf-8 -*- +""" +快速运行脚本 - 设置凭据并运行 SMS 示例 +使用方法: python run_with_credentials.py +""" +import os +import sys +import subprocess + +def main(): + print("=" * 60) + print("阿里云短信验证码 API - 快速运行") + print("=" * 60) + print() + + # 检查环境变量 + access_key_id = os.environ.get('ALIBABA_CLOUD_ACCESS_KEY_ID') + access_key_secret = os.environ.get('ALIBABA_CLOUD_ACCESS_KEY_SECRET') + + if not access_key_id or not access_key_secret: + print("⚠️ 未检测到环境变量，请输入您的阿里云凭据:") + print(" (获取地址: https://ram.console.aliyun.com/manage/ak)") + print() + + access_key_id = input("AccessKey ID: ").strip() + access_key_secret = input("AccessKey Secret: ").strip() + + if not access_key_id or not access_key_secret: + print() + print("❌ 错误: AccessKey 不能为空!") + sys.exit(1) + + # 设置环境变量 + os.environ['ALIBABA_CLOUD_ACCESS_KEY_ID'] = access_key_id + os.environ['ALIBABA_CLOUD_ACCESS_KEY_SECRET'] = access_key_secret + print() + print("✅ 凭据已设置") + else: + print(f"✅ 检测到环境变量:") + print(f" ALIBABA_CLOUD_ACCESS_KEY_ID: {access_key_id[:8]}...") + print(f" ALIBABA_CLOUD_ACCESS_KEY_SECRET: {'*' * 20}") + + print() + print("=" * 60) + print("正在运行 SMS 示例...") + print("=" * 60) + print() + + # 运行示例 + try: + # 使用当前环境运行 + result = subprocess.run( + [sys.executable, './alibabacloud_sample/sample.py'], + env=os.environ.copy(), + capture_output=False + ) + sys.exit(result.returncode) + except Exception as e: + print(f"❌ 运行失败: {e}") + sys.exit(1) + +if __name__ == '__main__': + main() diff --git a/ai_sms/ai_sms/set_credentials.ps1 b/ai_sms/ai_sms/set_credentials.ps1 new file mode 100644 index 0000000..43236e9 --- /dev/null +++ b/ai_sms/ai_sms/set_credentials.ps1 @@ -0,0 +1,45 @@ +# PowerShell 脚本：设置阿里云凭据环境变量 +# 使用方法: .\set_credentials.ps1 + +Write-Host "=" -NoNewline -ForegroundColor Cyan +Write-Host ("=" * 59) -ForegroundColor Cyan +Write-Host "阿里云 SMS API 凭据配置" -ForegroundColor Yellow +Write-Host "=" -NoNewline -ForegroundColor Cyan +Write-Host ("=" * 59) -ForegroundColor Cyan +Write-Host "" + +# 提示用户输入凭据 +Write-Host "请输入您的阿里云访问凭据:" -ForegroundColor Green +Write-Host "(可以在 https://ram.console.aliyun.com/manage/ak 获取)" -ForegroundColor Gray +Write-Host "" + +$accessKeyId = Read-Host "AccessKey ID" +$accessKeySecret = Read-Host "AccessKey Secret" -AsSecureString +$accessKeySecretPlain = [Runtime.InteropServices.Marshal]::PtrToStringAuto( + [Runtime.InteropServices.Marshal]::SecureStringToBSTR($accessKeySecret) +) + +if ([string]::IsNullOrWhiteSpace($accessKeyId) -or [string]::IsNullOrWhiteSpace($accessKeySecretPlain)) { + Write-Host "" + Write-Host "错误: AccessKey ID 和 AccessKey Secret 不能为空!" -ForegroundColor Red + exit 1 +} + +# 设置环境变量 +$env:ALIBABA_CLOUD_ACCESS_KEY_ID = $accessKeyId +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET = $accessKeySecretPlain + +Write-Host "" +Write-Host "=" -NoNewline -ForegroundColor Cyan +Write-Host ("=" * 59) -ForegroundColor Cyan +Write-Host "凭据配置成功!" -ForegroundColor Green +Write-Host "=" -NoNewline -ForegroundColor Cyan +Write-Host ("=" * 59) -ForegroundColor Cyan +Write-Host "" +Write-Host "环境变量已设置 (当前 PowerShell 会话有效):" -ForegroundColor Yellow +Write-Host "ALIBABA_CLOUD_ACCESS_KEY_ID: $($accessKeyId.Substring(0, [Math]::Min(8, $accessKeyId.Length)))..." -ForegroundColor Gray +Write-Host "ALIBABA_CLOUD_ACCESS_KEY_SECRET: ********************" -ForegroundColor Gray +Write-Host "" +Write-Host "现在可以运行程序:" -ForegroundColor Green +Write-Host "python .\alibabacloud_sample\sample.py" -ForegroundColor Cyan +Write-Host "" diff --git a/ai_sms/ai_sms/setup.py b/ai_sms/ai_sms/setup.py new file mode 100644 index 0000000..93b39f4 --- /dev/null +++ b/ai_sms/ai_sms/setup.py @@ -0,0 +1,76 @@ +# -*- coding: utf-8 -*- +""" + Licensed to the Apache Software Foundation (ASF) under one + or more contributor license agreements. See the NOTICE file + distributed with this work for additional information + regarding copyright ownership. The ASF licenses this file + to you under the Apache License, Version 2.0 (the + "License"); you may not use this file except in compliance + with the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, + software distributed under the License is distributed on an + "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + KIND, either express or implied. See the License for the + specific language governing permissions and limitations + under the License. +""" + +import os +from setuptools import setup, find_packages + +""" +setup module for alibabacloud_sample. + +Created on 31/12/2025 + +@author: +""" + +PACKAGE = "alibabacloud_sample" +NAME = "alibabacloud_sample" or "alibabacloud-package" +DESCRIPTION = "Alibaba Cloud SDK Code Sample Library for Python" +AUTHOR = "" +AUTHOR_EMAIL = "" +URL = "https://github.com/aliyun/alibabacloud-sdk" +VERSION = __import__(PACKAGE).__version__ +REQUIRES = [ + "alibabacloud_dypnsapi20170525>=2.0.0, <3.0.0", +] + +LONG_DESCRIPTION = '' +if os.path.exists('./README.md'): + with open("README.md", encoding='utf-8') as fp: + LONG_DESCRIPTION = fp.read() + +setup( + name=NAME, + version=VERSION, + description=DESCRIPTION, + long_description=LONG_DESCRIPTION, + long_description_content_type='text/markdown', + author=AUTHOR, + author_email=AUTHOR_EMAIL, + license="Apache License 2.0", + url=URL, + keywords=["alibabacloud","sample"], + packages=find_packages(exclude=["tests*"]), + include_package_data=True, + platforms="any", + install_requires=REQUIRES, + python_requires=">=3.6", + classifiers=( + "Development Status :: 4 - Beta", + "Intended Audience :: Developers", + "License :: OSI Approved :: Apache Software License", + "Programming Language :: Python", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.6", + 'Programming Language :: Python :: 3.7', + 'Programming Language :: Python :: 3.8', + 'Programming Language :: Python :: 3.9', + "Topic :: Software Development" + ) +) diff --git a/ai_sms/ai_sms/setup_credentials.py b/ai_sms/ai_sms/setup_credentials.py new file mode 100644 index 0000000..e73c83a --- /dev/null +++ b/ai_sms/ai_sms/setup_credentials.py @@ -0,0 +1,41 @@ +# -*- coding: utf-8 -*- +import os +import sys + +def setup_credentials(): + """ + 设置阿里云访问凭据的环境变量 + """ + print("=" * 60) + print("阿里云 SMS API 凭据配置") + print("=" * 60) + print("\n请输入您的阿里云访问凭据:") + print("(可以在 https://ram.console.aliyun.com/manage/ak 获取)\n") + + access_key_id = input("AccessKey ID: ").strip() + access_key_secret = input("AccessKey Secret: ").strip() + + if not access_key_id or not access_key_secret: + print("\n错误: AccessKey ID 和 AccessKey Secret 不能为空!") + sys.exit(1) + + # 设置环境变量 + os.environ['ALIBABA_CLOUD_ACCESS_KEY_ID'] = access_key_id + os.environ['ALIBABA_CLOUD_ACCESS_KEY_SECRET'] = access_key_secret + + print("\n" + "=" * 60) + print("凭据配置成功!") + print("=" * 60) + print("\n环境变量已设置:") + print(f"ALIBABA_CLOUD_ACCESS_KEY_ID: {access_key_id[:8]}...") + print(f"ALIBABA_CLOUD_ACCESS_KEY_SECRET: {'*' * 20}") + + print("\n您可以使用以下命令设置环境变量 (PowerShell):") + print(f'$env:ALIBABA_CLOUD_ACCESS_KEY_ID="{access_key_id}"') + print(f'$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="{access_key_secret}"') + + print("\n或者在当前 Python 会话中运行:") + print("python ./alibabacloud_sample/sample.py") + +if __name__ == '__main__': + setup_credentials() diff --git a/ai_sms/ai_sms/test_credentials.py b/ai_sms/ai_sms/test_credentials.py new file mode 100644 index 0000000..02d5e3a --- /dev/null +++ b/ai_sms/ai_sms/test_credentials.py @@ -0,0 +1,83 @@ +# -*- coding: utf-8 -*- +""" +测试凭据是否正确配置 +使用方法: python test_credentials.py +""" +import os +import sys + +os.environ['NO_PROXY'] = '100.100.100.200' +os.environ['no_proxy'] = '100.100.100.200' + +from alibabacloud_credentials.client import Client as CredentialClient + +def test_credentials(): + print("=" * 60) + print("测试阿里云凭据配置") + print("=" * 60) + print() + + # 检查环境变量 + access_key_id = os.environ.get('ALIBABA_CLOUD_ACCESS_KEY_ID') + access_key_secret = os.environ.get('ALIBABA_CLOUD_ACCESS_KEY_SECRET') + + print("1. 检查环境变量:") + if access_key_id: + print(f" ✅ ALIBABA_CLOUD_ACCESS_KEY_ID: {access_key_id[:8]}...") + else: + print(f" ❌ ALIBABA_CLOUD_ACCESS_KEY_ID: 未设置") + + if access_key_secret: + print(f" ✅ ALIBABA_CLOUD_ACCESS_KEY_SECRET: {'*' * 20}") + else: + print(f" ❌ ALIBABA_CLOUD_ACCESS_KEY_SECRET: 未设置") + + print() + print("2. 测试凭据加载:") + + try: + credential_client = CredentialClient() + credential = credential_client.get_credential() + + loaded_ak_id = credential.get_access_key_id() + loaded_ak_secret = credential.get_access_key_secret() + + if loaded_ak_id and loaded_ak_secret: + print(f" ✅ 凭据加载成功!") + print(f" AccessKey ID: {loaded_ak_id[:8]}...") + print(f" AccessKey Secret: {'*' * 20}") + print() + print("=" * 60) + print("✅ 凭据配置正确，可以运行程序了!") + print("=" * 60) + print() + print("运行命令:") + print(" python ./alibabacloud_sample/sample.py") + print() + print("或使用快速运行脚本:") + print(" python run_with_credentials.py") + return True + else: + print(" ❌ 凭据加载失败: AccessKey 为空") + return False + + except Exception as e: + print(f" ❌ 凭据加载失败: {e}") + print() + print("=" * 60) + print("解决方案:") + print("=" * 60) + print() + print("请在 PowerShell 中设置环境变量:") + print() + print(' $env:ALIBABA_CLOUD_ACCESS_KEY_ID="您的AccessKey_ID"') + print(' $env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="您的AccessKey_Secret"') + print() + print("然后重新运行此测试脚本") + print() + print("获取 AccessKey: https://ram.console.aliyun.com/manage/ak") + return False + +if __name__ == '__main__': + success = test_credentials() + sys.exit(0 if success else 1) diff --git a/ai_sms/ai_sms/快速运行指南.md b/ai_sms/ai_sms/快速运行指南.md new file mode 100644 index 0000000..ee508b7 --- /dev/null +++ b/ai_sms/ai_sms/快速运行指南.md @@ -0,0 +1,100 @@ +# 快速运行指南 + +## 问题原因 + +您遇到的错误是因为程序无法加载阿里云访问凭据。默认凭据链尝试了以下方式但都失败了： +1. ❌ 环境变量 `ALIBABA_CLOUD_ACCESS_KEY_ID` 和 `ALIBABA_CLOUD_ACCESS_KEY_SECRET` +2. ❌ CLI 配置文件 `C:\Users\34362\.aliyun\config.json` +3. ❌ 凭据配置文件 `C:\Users\34362\.alibabacloud\credentials.ini` +4. ❌ ECS 实例 RAM 角色（尝试连接代理 127.0.0.1:10809 失败） + +## 解决方案 + +### 方案 1: 使用环境变量（推荐，最简单） + +在 PowerShell 中运行： + +```powershell +# 设置环境变量 +$env:ALIBABA_CLOUD_ACCESS_KEY_ID="您的AccessKey_ID" +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="您的AccessKey_Secret" + +# 运行程序 +python .\alibabacloud_sample\sample.py +``` + +### 方案 2: 使用 PowerShell 脚本（交互式） + +```powershell +# 运行凭据配置脚本 +.\set_credentials.ps1 + +# 脚本会提示输入凭据并自动设置环境变量 +# 然后直接运行程序 +python .\alibabacloud_sample\sample.py +``` + +### 方案 3: 创建凭据配置文件（永久配置） + +创建文件 `C:\Users\34362\.alibabacloud\credentials.ini`： + +```ini +[default] +type = access_key +access_key_id = 您的AccessKey_ID +access_key_secret = 您的AccessKey_Secret +``` + +然后直接运行： +```powershell +python .\alibabacloud_sample\sample.py +``` + +## 获取 AccessKey + +1. 访问阿里云 RAM 控制台: https://ram.console.aliyun.com/manage/ak +2. 创建或查看您的 AccessKey ID 和 AccessKey Secret +3. **重要**: 妥善保管 AccessKey Secret，不要泄露 + +## 当前配置 + +- ✅ 手机号码: `13621242430` +- ✅ 验证码长度: 4 位数字 +- ✅ 依赖已安装 +- ✅ 错误处理已修复 + +## 注意事项 + +1. **代理问题**: 如果您使用了代理（如 127.0.0.1:10809），可能需要临时关闭或配置 `NO_PROXY` 环境变量 +2. **验证码**: API 会自动生成验证码，无法指定为 "1314" +3. **费用**: 发送短信会产生费用 + +## 完整示例 + +```powershell +# 1. 激活 conda 环境（如果需要） +conda activate douyin + +# 2. 设置凭据 +$env:ALIBABA_CLOUD_ACCESS_KEY_ID="LTAI5t..." +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="your_secret" + +# 3. 运行程序 +python .\alibabacloud_sample\sample.py +``` + +## 预期输出 + +成功时会看到类似输出： +```json +{ + "Code": "OK", + "Success": true, + "Message": "成功", + "Model": { + "VerifyCode": "1234", + "BizId": "...", + "RequestId": "..." + } +} +``` diff --git a/ai_sms/ai_sms/成功运行说明.md b/ai_sms/ai_sms/成功运行说明.md new file mode 100644 index 0000000..79e268a --- /dev/null +++ b/ai_sms/ai_sms/成功运行说明.md @@ -0,0 +1,91 @@ +# ✅ API 已成功连接！ + +## 🎉 当前状态 + +1. **API 连接成功**: 已成功调用阿里云短信服务 API +2. **代码已切换**: 从 `dypnsapi` 切换到正确的 `dysmsapi` +3. **凭据正确**: AccessKey 配置正确 +4. **手机号已配置**: 13621242430 +5. **验证码已配置**: 1314 + +## ⚠️ 最后一步：配置正确的短信模板 + +当前错误: `isv.SMS_TEMPLATE_ILLEGAL` - 该账号下找不到对应模板 + +**原因**: 模板代码 `SMS_474580174` 不存在或未审核通过 + +### 解决方案 + +1. **登录阿里云短信控制台** + - 短信模板管理: https://dysms.console.aliyun.com/domestic/text/template + +2. **查看您的已审核通过的模板** + - 找到模板代码（格式: `SMS_xxxxxxxxx`） + - 确保模板状态为"审核通过" + +3. **更新代码中的模板代码** + + 编辑 `sample.py` 第 50 行和第 74 行: + ```python + template_code='SMS_您的实际模板代码', + ``` + +4. **确认模板参数** + + 如果您的模板内容是: `您的验证码是${code}，有效期5分钟` + + 那么当前的配置已经正确: + ```python + template_param=json.dumps({"code": "1314"}) + ``` + + 如果模板变量名不是 `code`，请相应修改。 + +## 📝 当前代码配置 + +```python +send_sms_request = dysmsapi_20170525_models.SendSmsRequest( + phone_numbers='13621242430', # ✅ 手机号 + sign_name='阿里云短信', # ✅ 签名（如果不对请修改） + template_code='SMS_474580174', # ⚠️ 需要替换为您的实际模板代码 + template_param=json.dumps({"code": "1314"}) # ✅ 验证码参数 +) +``` + +## 🚀 运行命令 + +配置完模板代码后: + +```powershell +python .\alibabacloud_sample\sample.py +``` + +## ✅ 成功的响应示例 + +配置正确后，您会看到: + +```json +{ + "statusCode": 200, + "body": { + "Code": "OK", + "Message": "OK", + "BizId": "...", + "RequestId": "..." + } +} +``` + +## 📖 参考链接 + +- **短信模板管理**: https://dysms.console.aliyun.com/domestic/text/template +- **短信签名管理**: https://dysms.console.aliyun.com/domestic/text/sign +- **API 文档**: https://help.aliyun.com/zh/sms/developer-reference/api-dysmsapi-2017-05-25-sendsms + +## 💡 提示 + +1. 如果签名名称也不对，请同时修改第 49 行和第 73 行的 `sign_name` +2. 模板必须是"审核通过"状态才能使用 +3. 签名和模板必须匹配您的账号 + +**只需要更新正确的模板代码，程序就能成功发送短信了！** diff --git a/ai_sms/ai_sms/配置说明.md b/ai_sms/ai_sms/配置说明.md new file mode 100644 index 0000000..822f491 --- /dev/null +++ b/ai_sms/ai_sms/配置说明.md @@ -0,0 +1,69 @@ +# ✅ 代码已跑通 - 还需配置短信签名和模板 + +## 🎉 成功进展 + +1. ✅ **凭据已硬编码**: AccessKey 已配置在代码中 +2. ✅ **API 连接成功**: 已成功调用阿里云 API +3. ✅ **手机号已配置**: 13621242430 +4. ✅ **验证码配置**: 4位数字 + +## ⚠️ 还需完成的配置 + +### 1. 短信签名 (SignName) + +当前代码使用: `'阿里云'` + +**您需要:** +- 在阿里云短信控制台创建并审核通过短信签名 +- 控制台地址: https://dysms.console.aliyun.com/domestic/text/sign +- 将 `@D:\ai_sms\alibabacloud_sample\sample.py:49` 中的 `'阿里云'` 替换为您的实际签名 + +### 2. 短信模板 (TemplateCode) + +当前代码使用: `'SMS_123456789'` (占位符) + +**您需要:** +- 在阿里云短信控制台创建并审核通过短信模板 +- 控制台地址: https://dysms.console.aliyun.com/domestic/text/template +- 模板类型: 验证码 +- 模板内容示例: `您的验证码是${code}，有效期5分钟` +- 将 `@D:\ai_sms\alibabacloud_sample\sample.py:50` 中的 `'SMS_123456789'` 替换为您的实际模板代码 + +## 📝 当前代码配置 + +```python +send_sms_verify_code_request = dypnsapi_20170525_models.SendSmsVerifyCodeRequest( + phone_number='13621242430', # ✅ 已配置 + sign_name='阿里云', # ⚠️ 需要替换为您的签名 + template_code='SMS_123456789', # ⚠️ 需要替换为您的模板代码 + code_length=4, # ✅ 已配置 + code_type=1 # ✅ 已配置 (数字验证码) +) +``` + +## 🚀 完成配置后运行 + +```powershell +python .\alibabacloud_sample\sample.py +``` + +## 📖 参考链接 + +- **短信签名管理**: https://dysms.console.aliyun.com/domestic/text/sign +- **短信模板管理**: https://dysms.console.aliyun.com/domestic/text/template +- **API 文档**: https://next.api.aliyun.com/document/Dypnsapi/2017-05-25/SendSmsVerifyCode + +## 💡 注意事项 + +1. 签名和模板需要审核，通常需要几分钟到几小时 +2. 签名和模板必须审核通过后才能使用 +3. 验证码由 API 自动生成，无法指定为 "1314" +4. 发送短信会产生费用，请确保账户有余额 + +## 🔍 当前错误信息 + +最后一次运行的错误: +- `MissingTemplateCode`: 需要配置模板代码 +- 诊断地址已在错误信息中提供 + +配置完签名和模板后，程序即可成功发送短信验证码！ diff --git a/ai_statistics_days.csv b/ai_statistics_days.csv index dd12e26..70cfa4e 100644 --- a/ai_statistics_days.csv +++ b/ai_statistics_days.csv @@ -1,85 +1,112 @@ 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-183,杜晋芳中医,1,2025-12-23,101,511,28.55,207.79,3.54,0.162787,0.366563 -185,郭俊恒中医,1,2025-12-23,48,324,5.44,73.16,0.79,-0.008403,0.898561 -186,董强中医,1,2025-12-23,1,24,0.00,3.02,0.00,2.355556,-0.454545 -187,李亚娟中医,1,2025-12-23,1,24,0.02,3.87,0.16,-0.692369,-0.685446 -188,苗辉医生,1,2025-12-23,0,0,20.53,1122.08,23.76,0.640372,0.020800 -189,耳鼻喉医生夏昆峰,1,2025-12-23,0,0,1.34,15.79,0.54,0.146696,0.225490 -190,中医苏晨,1,2025-12-23,1,103,15.92,47.70,9.08,0.269292,6.691176 -191,智璇医生,1,2025-12-23,1,72,10.18,111.51,2.48,0.684187,-0.321377 -246,石鹤医生,1,2025-12-23,1,114,2.03,228.80,0.33,4.412822,-0.854409 -247,梁丽君中医,1,2025-12-23,1,115,7.74,29.35,1.23,1.795238,1.088028 -248,崔丽荣中医,1,2025-12-23,1,177,1.44,17.44,0.76,0.006347,0.105991 -249,张承红中医,1,2025-12-23,45,232,0.51,12.96,0.26,1.234483,1.695312 -253,中医郑伟,1,2025-12-23,1,24,0.00,0.12,0.00,-0.294118,0.000000 -254,感染科郭金存医生,1,2025-12-23,0,0,4.39,100.37,2.82,-0.411940,0.325933 -255,贾素芬中医,1,2025-12-23,101,129,0.02,1.62,0.16,-0.369650,0.000000 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+384,阮志华讲健康,1,2025-12-30,1,16,0.00,14.14,0.54,14.140000,-0.953886 +385,沈理医生,1,2025-12-30,50,310,0.13,65.73,1.87,65.730000,-0.789651 +386,中医治肾病周厘,1,2025-12-30,1,18,0.00,1.50,0.06,1.500000,-0.923077 +387,中医妇产科安向荣,1,2025-12-30,15,142,0.06,25.08,3.39,25.080000,0.059375 +388,院博医生,1,2025-12-30,1,16,0.00,0.52,0.03,0.520000,-0.888889 +389,中医盛刚,1,2025-12-30,14,113,0.04,37.14,1.01,37.140000,-0.941585 +390,中医王雷,1,2025-12-30,1,10,0.00,1.70,0.11,1.700000,-0.877778 +391,泌尿科邱医生,1,2025-12-30,1,15,0.00,87.82,2.93,87.820000,-0.825906 diff --git a/batch_import_history.py b/batch_import_history.py new file mode 100644 index 0000000..80e7af2 --- /dev/null +++ b/batch_import_history.py @@ -0,0 +1,548 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +批量历史数据导入脚本 + +功能： +1. 按日期范围循环抓取百家号数据 +2. 每次抓取后自动导出CSV +3. 自动导入数据库 +4. 记录执行日志和错误信息 +5. 自动重试机制（针对网络、代理等临时性错误） + +使用方法： + # 基本用法 + python batch_import_history.py --start 2025-12-01 --end 2025-12-25 + + # 跳过失败的日期继续执行 + python batch_import_history.py --start 2025-12-01 --end 2025-12-25 --skip-failed + + # 自定义重试次数（默认3次） + python batch_import_history.py --start 2025-12-01 --end 2025-12-25 --max-retries 5 + + # 组合使用 + python batch_import_history.py --start 2025-12-01 --end 2025-12-25 --skip-failed --max-retries 5 +""" + +import sys +import os +import subprocess +import argparse +from datetime import datetime, timedelta +from typing import List, Tuple, Optional +import json +import time + +# 设置UTF-8编码 +if sys.platform == 'win32': + import io + if not isinstance(sys.stdout, io.TextIOWrapper) or sys.stdout.encoding != 'utf-8': + sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8') + if not isinstance(sys.stderr, io.TextIOWrapper) or sys.stderr.encoding != 'utf-8': + sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8') + + +class BatchImporter: + """批量历史数据导入器""" + + def __init__(self, start_date: str, end_date: str, skip_failed: bool = False, max_retries: int = 3): + """初始化 + + Args: + start_date: 开始日期 (YYYY-MM-DD) + end_date: 结束日期 (YYYY-MM-DD) + skip_failed: 是否跳过失败的日期继续执行 + max_retries: 每个步骤的最大重试次数（默认：3） + """ + self.script_dir = os.path.dirname(os.path.abspath(__file__)) + self.start_date = datetime.strptime(start_date, '%Y-%m-%d') + self.end_date = datetime.strptime(end_date, '%Y-%m-%d') + self.skip_failed = skip_failed + self.max_retries = max_retries + + # 脚本路径 + self.analytics_script = os.path.join(self.script_dir, 'bjh_analytics_date.py') + self.export_script = os.path.join(self.script_dir, 'export_to_csv.py') + self.import_script = os.path.join(self.script_dir, 'import_csv_to_database.py') + + # 日志文件 + self.log_dir = os.path.join(self.script_dir, 'logs') + if not os.path.exists(self.log_dir): + os.makedirs(self.log_dir) + + timestamp = datetime.now().strftime('%Y%m%d_%H%M%S') + self.log_file = os.path.join(self.log_dir, f'batch_import_{timestamp}.log') + + # 执行结果记录 + self.results = [] + + # 验证脚本文件存在 + self._validate_scripts() + + def _validate_scripts(self): + """验证所需脚本文件是否存在""" + scripts = { + 'bjh_analytics_date.py': self.analytics_script, + 'export_to_csv.py': self.export_script, + 'import_csv_to_database.py': self.import_script + } + + missing_scripts = [] + for name, path in scripts.items(): + if not os.path.exists(path): + missing_scripts.append(name) + + if missing_scripts: + print(f"[X] 缺少必要的脚本文件:") + for script in missing_scripts: + print(f" - {script}") + raise FileNotFoundError("脚本文件缺失") + + def log(self, message: str, level: str = 'INFO'): + """记录日志 + + Args: + message: 日志消息 + level: 日志级别 (INFO, WARNING, ERROR) + """ + timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S') + log_line = f"[{timestamp}] [{level}] {message}" + + # 输出到控制台 + print(log_line) + + # 写入日志文件 + try: + with open(self.log_file, 'a', encoding='utf-8') as f: + f.write(log_line + '\n') + except Exception as e: + print(f"[!] 写入日志文件失败: {e}") + + def get_date_list(self) -> List[str]: + """生成日期列表 + + Returns: + 日期字符串列表 (YYYY-MM-DD) + """ + dates = [] + current = self.start_date + + while current <= self.end_date: + dates.append(current.strftime('%Y-%m-%d')) + current += timedelta(days=1) + + return dates + + def run_command_with_retry(self, cmd: List[str], step_name: str, max_retries: Optional[int] = None) -> Tuple[bool, str]: + """执行命令（带重试机制） + + Args: + cmd: 命令列表 + step_name: 步骤名称 + max_retries: 最大重试次数，默认使用实例配置 + + Returns: + (是否成功, 错误信息) + """ + if max_retries is None: + max_retries = self.max_retries + + retry_count = 0 + last_error = "" + + while retry_count <= max_retries: + if retry_count > 0: + # 重试前等待，递增延迟：5秒、10秒、15秒 + wait_time = retry_count * 5 + self.log(f"{step_name} 第{retry_count}次重试，等待 {wait_time} 秒...", level='WARNING') + time.sleep(wait_time) + + # 执行命令 + success, error = self.run_command(cmd, step_name) + + if success: + if retry_count > 0: + self.log(f"{step_name} 重试成功！（第{retry_count}次重试）", level='INFO') + return True, "" + + # 失败，记录错误 + last_error = error + retry_count += 1 + + # 判断是否需要重试 + if retry_count <= max_retries: + # 可重试的错误类型 + retryable_errors = [ + '超时', + 'timeout', + '连接', + 'connection', + '代理', + 'proxy', + '网络', + 'network', + 'RemoteDisconnected', + 'ConnectionError', + 'ProxyError' + ] + + # 检查错误信息是否包含可重试的关键词 + is_retryable = any(keyword in str(error).lower() for keyword in retryable_errors) + + if is_retryable: + self.log(f"{step_name} 出现可重试错误: {error}", level='WARNING') + else: + # 不可重试的错误，直接失败 + self.log(f"{step_name} 出现不可重试错误，停止重试: {error}", level='ERROR') + return False, error + + # 所有重试失败 + self.log(f"{step_name} 失败，已达最大重试次数 ({max_retries})", level='ERROR') + return False, last_error + + def run_command(self, cmd: List[str], step_name: str) -> Tuple[bool, str]: + """执行命令 + + Args: + cmd: 命令列表 + step_name: 步骤名称 + + Returns: + (是否成功, 错误信息) + """ + process = None + try: + self.log(f"执行命令: {' '.join(cmd)}") + + # 使用subprocess运行命令，实时输出 + process = subprocess.Popen( + cmd, + cwd=self.script_dir, + stdout=subprocess.PIPE, + stderr=subprocess.STDOUT, # 合并stderr到stdout + text=True, + encoding='utf-8', + bufsize=1, # 行缓冲 + universal_newlines=True + ) + + # 实时读取输出 + output_lines = [] + if process.stdout: + try: + for line in process.stdout: + line = line.rstrip() + if line: # 只输出非空行 + print(f" {line}") # 实时输出到控制台 + output_lines.append(line) + # 每10行记录一次日志，减少日志文件大小 + if len(output_lines) % 10 == 0: + self.log(f"{step_name} 运行中... (已输出{len(output_lines)}行)") + except Exception as e: + self.log(f"读取输出异常: {e}", level='WARNING') + + # 等待进程结束 + return_code = process.wait(timeout=600) # 10分钟超时 + + # 记录完整输出 + full_output = '\n'.join(output_lines) + if full_output: + self.log(f"{step_name} 输出:\n{full_output}") + + # 检查返回码 + if return_code == 0: + self.log(f"[✓] {step_name} 执行成功", level='INFO') + return True, "" + else: + error_msg = f"返回码: {return_code}" + self.log(f"[X] {step_name} 执行失败: {error_msg}", level='ERROR') + return False, error_msg + + except subprocess.TimeoutExpired: + if process: + process.kill() + error_msg = "命令执行超时（>10分钟）" + self.log(f"[X] {step_name} 失败: {error_msg}", level='ERROR') + return False, error_msg + + except Exception as e: + error_msg = str(e) + self.log(f"[X] {step_name} 异常: {error_msg}", level='ERROR') + import traceback + self.log(f"异常堆栈:\n{traceback.format_exc()}", level='ERROR') + return False, error_msg + + def process_date(self, date_str: str) -> bool: + """处理单个日期的数据 + + Args: + date_str: 日期字符串 (YYYY-MM-DD) + + Returns: + 是否成功 + """ + self.log("="*70) + self.log(f"开始处理日期: {date_str}") + self.log("="*70) + + result = { + 'date': date_str, + 'start_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'), + 'steps': {}, + 'success': False, + 'error': None + } + + # 步骤1: 数据抓取（带重试） + self.log(f"\n[步骤 1/3] 抓取 {date_str} 的数据...") + cmd_analytics = [ + sys.executable, + self.analytics_script, + date_str, + '--proxy', + '--database', + '--no-confirm' # 跳过确认提示 + ] + + success, error = self.run_command_with_retry(cmd_analytics, f"数据抓取 ({date_str})") + result['steps']['analytics'] = {'success': success, 'error': error} + + if not success: + result['error'] = f"数据抓取失败: {error}" + result['end_time'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S') + self.results.append(result) + return False + + # 等待2秒，确保文件写入完成 + time.sleep(2) + + # 步骤2: 导出CSV（带重试） + self.log(f"\n[步骤 2/3] 导出CSV文件...") + cmd_export = [ + sys.executable, + self.export_script, + '--mode', 'csv', + '--no-confirm' # 跳过确认提示 + ] + + success, error = self.run_command_with_retry(cmd_export, f"CSV导出 ({date_str})") + + result['steps']['export'] = {'success': success, 'error': error} + + if not success: + result['error'] = f"CSV导出失败: {error}" + result['end_time'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S') + self.results.append(result) + return False + + # 等待2秒 + time.sleep(2) + + # 步骤3: 导入数据库（带重试） + self.log(f"\n[步骤 3/3] 导入数据库...") + cmd_import = [ + sys.executable, + self.import_script + ] + + success, error = self.run_command_with_retry(cmd_import, f"数据库导入 ({date_str})") + result['steps']['import'] = {'success': success, 'error': error} + + if not success: + result['error'] = f"数据库导入失败: {error}" + result['end_time'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S') + self.results.append(result) + return False + + # 全部成功 + result['success'] = True + result['end_time'] = datetime.now().strftime('%Y-%m-%d %H:%M:%S') + self.results.append(result) + + self.log(f"\n[✓] {date_str} 处理完成!") + self.log("="*70 + "\n") + + return True + + def run(self): + """执行批量导入""" + dates = self.get_date_list() + + print("\n" + "="*70) + print("批量历史数据导入") + print("="*70) + print(f"开始日期: {self.start_date.strftime('%Y-%m-%d')}") + print(f"结束日期: {self.end_date.strftime('%Y-%m-%d')}") + print(f"总天数: {len(dates)} 天") + print(f"跳过失败: {'是' if self.skip_failed else '否'}") + print(f"最大重试次数: {self.max_retries}") + print(f"日志文件: {self.log_file}") + print("="*70) + + # 确认执行 + confirm = input("\n是否开始执行? (y/n): ").strip().lower() + if confirm != 'y': + print("已取消") + return + + self.log(f"开始批量导入: {len(dates)} 个日期") + start_time = datetime.now() + + success_count = 0 + failed_count = 0 + + for idx, date_str in enumerate(dates, 1): + print(f"\n{'='*70}") + print(f"进度: [{idx}/{len(dates)}] {date_str}") + print(f"{'='*70}") + + success = self.process_date(date_str) + + if success: + success_count += 1 + else: + failed_count += 1 + + # 如果不跳过失败，则停止执行 + if not self.skip_failed: + self.log(f"[X] 日期 {date_str} 处理失败，停止执行", level='ERROR') + break + else: + self.log(f"[!] 日期 {date_str} 处理失败，跳过继续", level='WARNING') + + # 日期间延迟（避免请求过快） + if idx < len(dates): + delay = 5 + self.log(f"等待 {delay} 秒后处理下一个日期...") + time.sleep(delay) + + # 执行完成 + end_time = datetime.now() + duration = end_time - start_time + + print("\n" + "="*70) + print("批量导入完成") + print("="*70) + print(f"总耗时: {duration}") + print(f"成功: {success_count} 天") + print(f"失败: {failed_count} 天") + print(f"日志文件: {self.log_file}") + print("="*70) + + self.log("="*70) + self.log(f"批量导入完成: 成功 {success_count} 天, 失败 {failed_count} 天") + self.log(f"总耗时: {duration}") + self.log("="*70) + + # 保存执行结果 + self._save_results() + + # 显示失败的日期 + if failed_count > 0: + print("\n失败的日期:") + for r in self.results: + if not r['success']: + print(f" - {r['date']}: {r.get('error', '未知错误')}") + + def _save_results(self): + """保存执行结果到JSON文件""" + try: + timestamp = datetime.now().strftime('%Y%m%d_%H%M%S') + result_file = os.path.join(self.log_dir, f'batch_result_{timestamp}.json') + + summary = { + 'start_date': self.start_date.strftime('%Y-%m-%d'), + 'end_date': self.end_date.strftime('%Y-%m-%d'), + 'total_dates': len(self.results), + 'success_count': sum(1 for r in self.results if r['success']), + 'failed_count': sum(1 for r in self.results if not r['success']), + 'results': self.results + } + + with open(result_file, 'w', encoding='utf-8') as f: + json.dump(summary, f, ensure_ascii=False, indent=2) + + self.log(f"执行结果已保存: {result_file}") + + except Exception as e: + self.log(f"保存执行结果失败: {e}", level='ERROR') + + +def main(): + """主函数""" + parser = argparse.ArgumentParser( + description='批量历史数据导入脚本', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +示例用法: + python batch_import_history.py --start 2025-12-01 --end 2025-12-25 + python batch_import_history.py --start 2025-12-01 --end 2025-12-25 --skip-failed + """ + ) + + parser.add_argument( + '--start', + type=str, + required=True, + help='开始日期 (格式: YYYY-MM-DD)' + ) + + parser.add_argument( + '--end', + type=str, + required=True, + help='结束日期 (格式: YYYY-MM-DD)' + ) + + parser.add_argument( + '--skip-failed', + action='store_true', + help='跳过失败的日期继续执行（默认：遇到失败停止）' + ) + + parser.add_argument( + '--max-retries', + type=int, + default=3, + help='每个步骤的最大重试次数（默认：3）' + ) + + args = parser.parse_args() + + # 验证日期格式 + try: + start = datetime.strptime(args.start, '%Y-%m-%d') + end = datetime.strptime(args.end, '%Y-%m-%d') + + if start > end: + print("[X] 开始日期不能晚于结束日期") + return 1 + + except ValueError as e: + print(f"[X] 日期格式错误: {e}") + print(" 正确格式: YYYY-MM-DD (例如: 2025-12-01)") + return 1 + + try: + # 创建导入器 + importer = BatchImporter( + start_date=args.start, + end_date=args.end, + skip_failed=args.skip_failed, + max_retries=args.max_retries + ) + + # 执行批量导入 + importer.run() + + return 0 + + except Exception as e: + print(f"\n[X] 程序执行出错: {e}") + import traceback + traceback.print_exc() + return 1 + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/bjh_analytics.py b/bjh_analytics.py index e372f5d..b6008e3 100644 --- a/bjh_analytics.py +++ b/bjh_analytics.py @@ -29,12 +29,12 @@ from database_config import DatabaseManager, DB_CONFIG # 代理配置 - 大麦代理IP PROXY_API_URL = ( - 'https://api2.damaiip.com/index.php?s=/front/user/getIPlist&xsn=e054861d08471263d970bde4f4905181&osn=TC_NO176655872088456223&tiqu=1' + 'https://api2.damaiip.com/index.php?s=/front/user/getIPlist&xsn=2912cb2b22d3b7ae724f045012790479&osn=TC_NO176707424165606223&tiqu=1' ) # 大麦代理账号密码认证 -PROXY_USERNAME = '694b8c3172af7' -PROXY_PASSWORD = 'q8yA8x1dwCpdyIK' +PROXY_USERNAME = '69538fdef04e1' +PROXY_PASSWORD = '63v0kQBr2yJXnjf' # 备用固定代理IP池（格式：'IP:端口', '用户名', '密码'） BACKUP_PROXY_POOL = [ @@ -62,7 +62,8 @@ class BaijiahaoAnalytics: # 代理配置 self.use_proxy = use_proxy - self.current_proxy = None + self.current_proxy = None # 当前IP，使用完后/失败后才重新获取 + self.proxy_fail_count = 0 # 当前代理失败次数 # 数据库配置 self.load_from_db = load_from_db @@ -76,6 +77,8 @@ class BaijiahaoAnalytics: if self.use_proxy: self.logger.info("已启用代理模式") print("[配置] 已启用代理模式") + # 初始化时获取第一个代理 + self.fetch_proxy(force_new=True) if self.load_from_db: self.logger.info("已启用数据库加载模式") @@ -99,6 +102,12 @@ class BaijiahaoAnalytics: self.analytics_output = os.path.join(self.script_dir, "bjh_analytics_data.json") self.income_output = os.path.join(self.script_dir, "bjh_income_data_v2.json") + # 创建备份文件夹 + self.backup_dir = os.path.join(self.script_dir, "backup") + if not os.path.exists(self.backup_dir): + os.makedirs(self.backup_dir) + print(f"[OK] 创建备份文件夹: {self.backup_dir}") + def cookie_string_to_dict(self, cookie_string: str) -> Dict: """将Cookie字符串转换为字典格式 @@ -230,15 +239,23 @@ class BaijiahaoAnalytics: print(f"[OK] 已设置账号 {account_id} 的Cookie ({len(cookies)} 个字段)") return True - def fetch_proxy(self) -> Optional[Dict]: + def fetch_proxy(self, force_new: bool = False) -> Optional[Dict]: """从代理服务获取一个可用代理，失败时使用备用固定代理 + Args: + force_new: 是否强制获取新代理，默认False（优先使用当前IP） + Returns: 代理配置字典，格式: {'http': 'http://...', 'https': 'http://...'} """ if not self.use_proxy: return None + # 如果已有可用代理且不强制获取新代理，直接返回 + if self.current_proxy and not force_new: + return self.current_proxy + + # 获取新代理 try: # 使用大麦代理API获取IP resp = requests.get(PROXY_API_URL, timeout=10) @@ -247,21 +264,30 @@ class BaijiahaoAnalytics: # 首先尝试解析为纯文本格式（最常见） text = resp.text.strip() + # 检测是否返回错误信息 + if text.upper().startswith('ERROR'): + raise Exception(f"代理API返回错误: {text}") + # 尝试直接解析为IP:PORT格式 lines = text.split('\n') for line in lines: line = line.strip() if ':' in line and not line.startswith('{') and not line.startswith('['): # 找到第一个IP:PORT格式 - ip_port = line.split()[0] if ' ' in line else line # 处理可能带有其他信息的情况 + ip_port = line.split()[0] if ' ' in line else line if ip_port.count(':') == 1: # 确保是IP:PORT格式 nowtime = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()) self.logger.info(f'提取大麦代理IP(文本): {ip_port} at {nowtime}') print(f'[代理] 提取大麦IP: {ip_port}') + # 大麦代理使用账号密码认证 host, port = ip_port.split(':', 1) - proxy_url = f'http://{PROXY_USERNAME}:{PROXY_PASSWORD}@{host}:{port}' + if PROXY_USERNAME and PROXY_PASSWORD: + proxy_url = f'http://{PROXY_USERNAME}:{PROXY_PASSWORD}@{host}:{port}' + else: + proxy_url = f'http://{host}:{port}' + self.current_proxy = { 'http': proxy_url, 'https': proxy_url, @@ -282,8 +308,12 @@ class BaijiahaoAnalytics: self.logger.info(f'提取大麦代理IP(JSON): {ip_port} at {nowtime}') print(f'[代理] 提取大麦IP: {ip_port}') - # 构建带账密的代理URL: http://username:password@host:port - proxy_url = f'http://{PROXY_USERNAME}:{PROXY_PASSWORD}@{ip_info["ip"]}:{ip_info["port"]}' + # 大麦代理使用账号密码认证 + if PROXY_USERNAME and PROXY_PASSWORD: + proxy_url = f'http://{PROXY_USERNAME}:{PROXY_PASSWORD}@{ip_info["ip"]}:{ip_info["port"]}' + else: + proxy_url = f'http://{ip_info["ip"]}:{ip_info["port"]}' + self.current_proxy = { 'http': proxy_url, 'https': proxy_url, @@ -316,6 +346,34 @@ class BaijiahaoAnalytics: } return self.current_proxy + def mark_proxy_failed(self): + """标记当前代理失败，失败超过3次后重新获取代理 + + Returns: + bool: 是否需要重新获取代理 + """ + if not self.use_proxy or not self.current_proxy: + return False + + self.proxy_fail_count += 1 + self.logger.warning(f"当前代理失败次数: {self.proxy_fail_count}") + + # 失败超过3次，重新获取代理 + if self.proxy_fail_count >= 3: + self.logger.info("当前代理失败次数过多，重新获取新代理") + print(f"[代理] 失败{self.proxy_fail_count}次，重新获取新代理") + self.current_proxy = None + self.proxy_fail_count = 0 + # 强制获取新代理 + self.fetch_proxy(force_new=True) + return True + + return False + + def reset_proxy_fail_count(self): + """重置代理失败计数（请求成功后调用）""" + self.proxy_fail_count = 0 + def get_common_headers(self) -> Dict: """获取通用请求头""" return { @@ -425,6 +483,8 @@ class BaijiahaoAnalytics: successful_data = [] retry_count = 0 + proxy_change_count = 0 # 代理更换次数计数器 + max_proxy_changes = 3 # 最多更换3次代理（即最多使用4个不同代理） while retry_count <= max_retries: try: @@ -438,6 +498,21 @@ class BaijiahaoAnalytics: # 获取代理（如果启用） proxies = self.fetch_proxy() if self.use_proxy else None + # 调试信息：显示代理使用情况 + if self.use_proxy: + if proxies: + proxy_url = proxies.get('http', '') + if '@' in proxy_url: + # 提取IP部分（隐藏账号密码） + proxy_ip = proxy_url.split('@')[1] + else: + proxy_ip = proxy_url.replace('http://', '').replace('https://', '') + self.logger.info(f"发文统计API 使用代理: {proxy_ip}") + print(f" [代理] 使用IP: {proxy_ip}") + else: + self.logger.warning(f"发文统计API 代理未生效！use_proxy={self.use_proxy}") + print(f" [!] 警告：代理未生效！use_proxy={self.use_proxy}") + response = self.session.get( api_url, headers=headers, @@ -462,6 +537,9 @@ class BaijiahaoAnalytics: self.logger.info("发文统计API调用成功") print(f" [✓] API调用成功") + # 请求成功，重置代理失败计数 + self.reset_proxy_fail_count() + # 提取发文统计数据 total_info = data.get('data', {}).get('total_info', {}) @@ -490,6 +568,34 @@ class BaijiahaoAnalytics: else: self.logger.error(f"API返回错误: errno={errno}, errmsg={errmsg}") print(f" [X] API返回错误: errno={errno}, errmsg={errmsg}") + + # 特别处理 errno=10000015 （异常请求），这通常是代理未生效 + if errno == 10000015 and self.use_proxy: + self.logger.warning("检测到 errno=10000015（异常请求），代理未生效，立即强制更换新代理") + print(f" [!] 检测到代理未生效，立即更换新代理") + + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + break + + # 立即强制获取新代理（不等待3次） + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + + if new_proxy: + # 如果还没达到重试上限，尝试重试 + if retry_count < max_retries: + proxy_change_count += 1 + self.logger.info(f"已更换新代理({proxy_change_count}/{max_proxy_changes})，将重试，当前第{retry_count+1}次") + print(f" [!] 已更换新代理({proxy_change_count}/{max_proxy_changes})，将重试...") + retry_count += 1 + continue + else: + self.logger.error("无法获取新代理，放弃重试") + print(f" [X] 无法获取新代理") + break # API错误，不重试 except json.JSONDecodeError as e: @@ -521,6 +627,58 @@ class BaijiahaoAnalytics: if retry_count < max_retries: self.logger.warning(f"发文统计API代理连接错误: {error_type}，将重试") print(f" [!] 代理连接错误: {error_type}") + + # 标记代理失败 + self.mark_proxy_failed() + + # 超时或连接错误立即更换代理（不等待3次失败） + if self.use_proxy and ('Timeout' in error_type or 'Connection' in error_type or 'ProxyError' in error_type): + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + self.logger.error(f"已达代理更换上限({max_proxy_changes}次)，放弃重试") + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + break + + self.logger.warning(f"检测到{error_type}错误，立即更换新代理") + print(f" [!] 检测到{error_type}，立即更换新代理") + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + + if new_proxy: + proxy_change_count += 1 + self.logger.info(f"已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + print(f" [✓] 已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + # 更换代理后，不增加retry_count，直接continue重试 + continue + else: + self.logger.error("无法获取新代理，放弃重试") + print(f" [X] 无法获取新代理") + break + # 其他代理错误，等待3次失败后更换 + elif self.proxy_fail_count >= 3 and self.use_proxy: + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + self.logger.error(f"已达代理更换上限({max_proxy_changes}次)，放弃重试") + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + break + + print(f" [!] 代理已失败{self.proxy_fail_count}次，强制更换新代理") + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + if new_proxy: + proxy_change_count += 1 + self.logger.info(f"已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + print(f" [✓] 已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + # 更换代理后，不增加retry_count，直接continue重试 + continue + else: + self.logger.error("无法获取新代理") + print(f" [X] 无法获取新代理") + break + + # 其他情况才增加retry_count retry_count += 1 continue else: @@ -701,6 +859,8 @@ class BaijiahaoAnalytics: print(f" API: {api_url}") retry_count = 0 + proxy_change_count = 0 # 代理更换次数计数器 + max_proxy_changes = 3 # 最多更换3次代理（即最多使用4个不同代理） while retry_count <= max_retries: try: @@ -714,6 +874,21 @@ class BaijiahaoAnalytics: # 获取代理（如果启用） proxies = self.fetch_proxy() if self.use_proxy else None + # 调试信息：显示代理使用情况 + if self.use_proxy: + if proxies: + proxy_url = proxies.get('http', '') + if '@' in proxy_url: + # 提取IP部分（隐藏账号密码） + proxy_ip = proxy_url.split('@')[1] + else: + proxy_ip = proxy_url.replace('http://', '').replace('https://', '') + self.logger.info(f"收入API 使用代理: {proxy_ip}") + print(f" [代理] 使用IP: {proxy_ip}") + else: + self.logger.warning(f"收入API 代理未生效！use_proxy={self.use_proxy}") + print(f" [!] 警告：代理未生效！use_proxy={self.use_proxy}") + response = self.session.get( api_url, headers=headers, @@ -735,6 +910,9 @@ class BaijiahaoAnalytics: self.logger.info("收入数据API调用成功") print(f" [✓] API调用成功") + # 请求成功，重置代理失败计数 + self.reset_proxy_fail_count() + # 显示收入数据摘要 income_data = data.get('data', {}).get('income', {}) if 'recent7Days' in income_data: @@ -752,6 +930,34 @@ class BaijiahaoAnalytics: else: self.logger.error(f"收入API返回错误: errno={errno}, errmsg={errmsg}") print(f" [X] API返回错误: errno={errno}, errmsg={errmsg}") + + # 特别处理 errno=10000015 （异常请求），这通常是代理未生效 + if errno == 10000015 and self.use_proxy: + self.logger.warning("检测到收入API errno=10000015（异常请求），代理未生效，立即强制更换新代理") + print(f" [!] 检测到代理未生效，立即更换新代理") + + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + return None + + # 立即强制获取新代理（不等待3次） + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + + if new_proxy: + # 如果还没达到重试上限，尝试重试 + if retry_count < max_retries: + proxy_change_count += 1 + self.logger.info(f"已更换新代理({proxy_change_count}/{max_proxy_changes})，将重试收入API，当前第{retry_count+1}次") + print(f" [!] 已更换新代理({proxy_change_count}/{max_proxy_changes})，将重试...") + retry_count += 1 + continue + else: + self.logger.error("无法获取新代理，放弃重试") + print(f" [X] 无法获取新代理") + return None except json.JSONDecodeError as e: self.logger.error(f"收入数据JSON解析失败: {e}") @@ -781,6 +987,58 @@ class BaijiahaoAnalytics: if retry_count < max_retries: self.logger.warning(f"收入数据API代理连接错误: {error_type}，将重试") print(f" [!] 代理连接错误: {error_type}") + + # 标记代理失败 + self.mark_proxy_failed() + + # 超时或连接错误立即更换代理（不等待3次失败） + if self.use_proxy and ('Timeout' in error_type or 'Connection' in error_type or 'ProxyError' in error_type): + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + self.logger.error(f"已达代理更换上限({max_proxy_changes}次)，放弃重试") + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + return None + + self.logger.warning(f"检测到{error_type}错误，立即更换新代理") + print(f" [!] 检测到{error_type}，立即更换新代理") + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + + if new_proxy: + proxy_change_count += 1 + self.logger.info(f"已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + print(f" [✓] 已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + # 更换代理后，不增加retry_count，直接continue重试 + continue + else: + self.logger.error("无法获取新代理，放弃重试") + print(f" [X] 无法获取新代理") + return None + # 其他代理错误，等待3次失败后更换 + elif self.proxy_fail_count >= 3 and self.use_proxy: + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + self.logger.error(f"已达代理更换上限({max_proxy_changes}次)，放弃重试") + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + return None + + print(f" [!] 代理已失败{self.proxy_fail_count}次，强制更换新代理") + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + if new_proxy: + proxy_change_count += 1 + self.logger.info(f"已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + print(f" [✓] 已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + # 更换代理后，不增加retry_count，直接continue重试 + continue + else: + self.logger.error("无法获取新代理") + print(f" [X] 无法获取新代理") + return None + + # 其他情况才增加retry_count retry_count += 1 continue else: @@ -866,6 +1124,8 @@ class BaijiahaoAnalytics: errno = data.get('errno', -1) if errno == 0: + # 请求成功，重置代理失败计数 + self.reset_proxy_fail_count() return data else: self.logger.error(f"单日收入API返回错误: errno={errno}") @@ -895,6 +1155,10 @@ class BaijiahaoAnalytics: if is_proxy_error: if retry_count < max_retries: self.logger.warning(f"单日收入代理连接错误 ({target_date.strftime('%Y-%m-%d')}): {error_type}，将重试") + + # 标记代理失败 + self.mark_proxy_failed() + retry_count += 1 continue else: @@ -1068,17 +1332,29 @@ class BaijiahaoAnalytics: return results def save_results(self, results: List[Dict]): - """保存结果到文件 + """保存结果到文件（同时备份带日期的副本） Args: results: 数据分析结果列表 """ + import shutil + try: + # 1. 保存到主文件（不带时间戳） with open(self.output_file, 'w', encoding='utf-8') as f: json.dump(results, f, ensure_ascii=False, indent=2) print(f"\n{'='*70}") print(f"[OK] 数据已保存到: {self.output_file}") + + # 2. 创建带日期的备份文件（只保留日期） + timestamp = datetime.now().strftime('%Y%m%d') + backup_filename = f"bjh_integrated_data_{timestamp}.json" + backup_file = os.path.join(self.backup_dir, backup_filename) + + # 复制文件到备份目录 + shutil.copy2(self.output_file, backup_file) + print(f"[OK] 备份已保存到: {backup_file}") print(f"{'='*70}") # 显示统计 diff --git a/bjh_analytics_date.py b/bjh_analytics_date.py new file mode 100644 index 0000000..f464905 --- /dev/null +++ b/bjh_analytics_date.py @@ -0,0 +1,809 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +百家号指定日期数据抓取工具 +根据指定日期范围抓取发文统计和收入数据 +""" + +import json +import sys +import os +import argparse +from datetime import datetime, timedelta +from typing import Dict, List, Optional + +# 导入基础分析器 +from bjh_analytics import BaijiahaoAnalytics + +# 设置标准输出编码为UTF-8 +if sys.platform == 'win32': + import io + sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8') + sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8') + + +class BaijiahaoDateAnalytics(BaijiahaoAnalytics): + """百家号指定日期数据抓取器""" + + def __init__(self, target_date: str, use_proxy: bool = False, load_from_db: bool = False, db_config: Optional[Dict] = None): + """初始化 + + Args: + target_date: 目标日期 (YYYY-MM-DD) + use_proxy: 是否使用代理 + load_from_db: 是否从数据库加载Cookie + db_config: 数据库配置 + """ + super().__init__(use_proxy=use_proxy, load_from_db=load_from_db, db_config=db_config) + + # 解析目标日期 + try: + self.target_date = datetime.strptime(target_date, '%Y-%m-%d') + self.target_date_str = target_date + except ValueError: + raise ValueError(f"日期格式错误: {target_date}，正确格式: YYYY-MM-DD") + + # 修改输出文件名（不带日期，使用固定文件名） + self.output_file = os.path.join( + self.script_dir, + "bjh_integrated_data.json" + ) + + # 创建备份文件夹 + self.backup_dir = os.path.join(self.script_dir, "backup") + if not os.path.exists(self.backup_dir): + os.makedirs(self.backup_dir) + + print(f"[配置] 目标日期: {target_date}") + print(f"[配置] 输出文件: {self.output_file}") + print(f"[配置] 备份目录: {self.backup_dir}") + + def fetch_analytics_api_for_date(self, days: int = 7, max_retries: int = 3) -> Optional[Dict]: + """获取指定日期范围的发文统计数据 + + Args: + days: 查询天数（从target_date往前推） + max_retries: 最大重试次数 + + Returns: + 发文统计数据 + """ + import time + + # 计算日期范围（从target_date往前推days天） + end_date = self.target_date + start_date = end_date - timedelta(days=days-1) + + start_day = start_date.strftime('%Y%m%d') + end_day = end_date.strftime('%Y%m%d') + + # API端点 + api_url = f"{self.base_url}/author/eco/statistics/appStatisticV3" + + # 请求参数（不使用special_filter_days，直接指定日期范围） + params = { + 'type': 'event', + 'start_day': start_day, + 'end_day': end_day, + 'stat': '0' + } + + # 从Cookie中提取token + token_cookie = self.session.cookies.get('bjhStoken') or self.session.cookies.get('devStoken') + + # 请求头 + headers = { + 'Accept': 'application/json, text/plain, */*', + 'Accept-Language': 'zh-CN,zh;q=0.9', + 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', + 'Referer': f'{self.base_url}/builder/rc/analysiscontent', + 'Sec-Fetch-Dest': 'empty', + 'Sec-Fetch-Mode': 'cors', + 'Sec-Fetch-Site': 'same-origin', + } + + if token_cookie: + headers['token'] = token_cookie + + self.logger.info(f"获取发文统计: {start_date.strftime('%Y-%m-%d')} 至 {end_date.strftime('%Y-%m-%d')}") + print(f"\n[请求] 获取发文统计数据") + print(f" 日期范围: {start_date.strftime('%Y-%m-%d')} 至 {end_date.strftime('%Y-%m-%d')}") + + successful_data = [] + retry_count = 0 + proxy_change_count = 0 # 代理更换次数计数器 + max_proxy_changes = 3 # 最多更换3次代理（即最多使用4个不同代理） + + while retry_count <= max_retries: + try: + if retry_count > 0: + wait_time = retry_count * 2 + print(f" [重试 {retry_count}/{max_retries}] 等待 {wait_time} 秒...") + time.sleep(wait_time) + + proxies = self.fetch_proxy() if self.use_proxy else None + + # 调试信息：显示代理使用情况 + if self.use_proxy: + if proxies: + proxy_url = proxies.get('http', '') + if '@' in proxy_url: + proxy_ip = proxy_url.split('@')[1] + else: + proxy_ip = proxy_url.replace('http://', '').replace('https://', '') + print(f" [代理] 使用IP: {proxy_ip}") + else: + print(f" [!] 警告：代理未生效！use_proxy={self.use_proxy}") + + response = self.session.get( + api_url, + headers=headers, + params=params, + proxies=proxies, + timeout=15, + verify=False + ) + + print(f" 状态码: {response.status_code}") + + if response.status_code == 200: + data = response.json() + errno = data.get('errno', -1) + + if errno == 0: + print(f" [✓] API调用成功") + + # 请求成功，重置代理失败计数 + self.reset_proxy_fail_count() + + # 检查data字段类型 + data_field = data.get('data', {}) + if isinstance(data_field, list): + print(f" [X] API返回数据格式异常: data字段为列表而非字典") + print(f" 原始响应前500字符: {str(data)[:500]}") + break + + if not isinstance(data_field, dict): + print(f" [X] API返回数据格式异常: data字段类型为 {type(data_field).__name__}") + break + + total_info = data_field.get('total_info', {}) + print(f"\n 发文统计数据:") + print(f" 发文量: {total_info.get('publish_count', '0')}") + print(f" 曝光量: {total_info.get('disp_pv', '0')}") + print(f" 阅读量: {total_info.get('view_count', '0')}") + + api_result = { + 'endpoint': '/author/eco/statistics/appStatisticV3', + 'name': '发文统计', + 'date_range': f"{start_day} - {end_day}", + 'data': data, + 'fetch_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S') + } + successful_data.append(api_result) + break + else: + errmsg = data.get('errmsg', '') + print(f" [X] API返回错误: errno={errno}, errmsg={errmsg}") + + # 特别处理 errno=10000015（异常请求），这通常是代理未生效 + if errno == 10000015 and self.use_proxy: + print(f" [!] 检测到代理未生效，立即更换新代理") + + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + break + + # 立即强制获取新代理 + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + + if new_proxy and retry_count < max_retries: + proxy_change_count += 1 + print(f" [!] 已更换新代理({proxy_change_count}/{max_proxy_changes})，将重试...") + retry_count += 1 + continue + else: + print(f" [X] 无法获取新代理或已达重试上限") + break + else: + # 其他API错误，不重试 + break + else: + print(f" [X] HTTP错误: {response.status_code}") + break + + except Exception as e: + error_type = type(e).__name__ + is_retry_error = any([ + 'Connection' in error_type, + 'Timeout' in error_type, + 'ProxyError' in error_type, + ]) + + if is_retry_error and retry_count < max_retries: + print(f" [!] 连接错误: {error_type}") + + # 标记代理失败 + self.mark_proxy_failed() + + # 如果代理失败次数达到3次，强制更换新代理（第4次重试用新代理） + if self.proxy_fail_count >= 3 and self.use_proxy: + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + break + + print(f" [!] 代理已失败{self.proxy_fail_count}次，强制更换新代理") + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + if new_proxy: + proxy_change_count += 1 + print(f" [✓] 已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + else: + print(f" [X] 无法获取新代理") + break + + retry_count += 1 + continue + else: + print(f" [X] 请求异常: {e}") + break + + if successful_data: + return { + 'apis': successful_data, + 'count': len(successful_data) + } + + return None + + def fetch_income_for_date(self, max_retries: int = 3) -> Optional[Dict]: + """获取指定日期的收入数据 + + 使用overviewhomelist API获取按天的详细收入数据 + + Returns: + 收入数据 + """ + import time + from datetime import timedelta + + # 计算Unix时间戳（从目标日期往前30天，以便获取更多数据） + end_date = self.target_date + start_date = end_date - timedelta(days=29) # 30天范围 + + # 转换为Unix时间戳（秒） + start_timestamp = int(start_date.timestamp()) + end_timestamp = int(end_date.timestamp()) + + # 使用overviewhomelist API获取每日收入明细 + api_url = f"{self.base_url}/author/eco/income4/overviewhomelist" + + token_cookie = self.session.cookies.get('bjhStoken') or self.session.cookies.get('devStoken') + + headers = { + 'Accept': 'application/json, text/plain, */*', + 'Accept-Language': 'zh-CN,zh;q=0.9', + 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', + 'Referer': f'{self.base_url}/builder/rc/incomecenter', + 'Sec-Fetch-Dest': 'empty', + 'Sec-Fetch-Mode': 'cors', + 'Sec-Fetch-Site': 'same-origin', + } + + if token_cookie: + headers['token'] = token_cookie + + # 请求参数 + params = { + 'start_date': start_timestamp, + 'end_date': end_timestamp + } + + print(f"\n[请求] 获取收入数据") + print(f" 日期范围: {start_date.strftime('%Y-%m-%d')} 至 {end_date.strftime('%Y-%m-%d')}") + + retry_count = 0 + proxy_change_count = 0 # 代理更换次数计数器 + max_proxy_changes = 3 # 最多更换3次代理（即最多使用4个不同代理） + + while retry_count <= max_retries: + try: + if retry_count > 0: + wait_time = retry_count * 2 + print(f" [重试 {retry_count}/{max_retries}] 等待 {wait_time} 秒...") + time.sleep(wait_time) + + proxies = self.fetch_proxy() if self.use_proxy else None + + # 调试信息：显示代理使用情况 + if self.use_proxy: + if proxies: + proxy_url = proxies.get('http', '') + if '@' in proxy_url: + proxy_ip = proxy_url.split('@')[1] + else: + proxy_ip = proxy_url.replace('http://', '').replace('https://', '') + print(f" [代理] 使用IP: {proxy_ip}") + else: + print(f" [!] 警告：代理未生效！use_proxy={self.use_proxy}") + + response = self.session.get( + api_url, + headers=headers, + params=params, + proxies=proxies, + timeout=15, + verify=False + ) + + print(f" 状态码: {response.status_code}") + + if response.status_code == 200: + data = response.json() + errno = data.get('errno', -1) + + if errno == 0: + print(f" [✓] API调用成功") + + # 请求成功，重置代理失败计数 + self.reset_proxy_fail_count() + + # 提取收入列表 + income_list = data.get('data', {}).get('list', []) + + if income_list: + # 找到目标日期的数据 + target_timestamp = int(self.target_date.timestamp()) + target_income_data = None + + for item in income_list: + if item.get('day_time') == target_timestamp: + target_income_data = item + break + + if target_income_data: + day_revenue = target_income_data.get('total_income', 0) + print(f"\n 收入数据详情:") + print(f" {self.target_date_str} 当日收入: ¥{day_revenue:.2f}") + + # 计算近7天收入 + recent7_revenue = 0.0 + recent7_start = self.target_date - timedelta(days=6) + recent7_start_ts = int(recent7_start.timestamp()) + for item in income_list: + if recent7_start_ts <= item.get('day_time', 0) <= target_timestamp: + recent7_revenue += item.get('total_income', 0) + print(f" 近7天: ¥{recent7_revenue:.2f}") + + # 计算近30天收入 + recent30_revenue = sum(item.get('total_income', 0) for item in income_list) + print(f" 近30天: ¥{recent30_revenue:.2f}") + + # 计算当月收入（从月初到目标日期） + month_start = self.target_date.replace(day=1) + month_start_ts = int(month_start.timestamp()) + current_month_revenue = 0.0 + for item in income_list: + if month_start_ts <= item.get('day_time', 0) <= target_timestamp: + current_month_revenue += item.get('total_income', 0) + print(f" 当月收入: ¥{current_month_revenue:.2f}") + + # 构造返回数据（与原有格式保持一致） + return { + 'errno': 0, + 'errmsg': 'success', + 'data': { + 'income': { + 'yesterday': { + 'income': day_revenue, + 'value': day_revenue + }, + 'recent7Days': { + 'income': recent7_revenue, + 'value': recent7_revenue + }, + 'recent30Days': { + 'income': recent30_revenue, + 'value': recent30_revenue + }, + 'currentMonth': { + 'income': current_month_revenue, + 'value': current_month_revenue + } + } + }, + 'raw_list': income_list # 保留原始数据 + } + else: + print(f" [警告] 未找到 {self.target_date_str} 的收入数据") + return None + else: + print(f" [警告] 收入数据列表为空") + return None + else: + errmsg = data.get('errmsg', '') + print(f" [X] API返回错误: errno={errno}, errmsg={errmsg}") + + # 特别处理 errno=10000015（异常请求），这通常是代理未生效 + if errno == 10000015 and self.use_proxy: + print(f" [!] 检测到代理未生效，立即更换新代理") + + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + return None + + # 立即强制获取新代理 + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + + if new_proxy and retry_count < max_retries: + proxy_change_count += 1 + print(f" [!] 已更换新代理({proxy_change_count}/{max_proxy_changes})，将重试...") + retry_count += 1 + continue + else: + print(f" [X] 无法获取新代理或已达重试上限") + return None + else: + # 其他API错误，不重试 + return None + else: + print(f" [X] HTTP错误: {response.status_code}") + return None + + except Exception as e: + error_type = type(e).__name__ + is_retry_error = any([ + 'Connection' in error_type, + 'Timeout' in error_type, + 'ProxyError' in error_type, + ]) + + if is_retry_error and retry_count < max_retries: + print(f" [!] 连接错误: {error_type}") + + # 标记代理失败 + self.mark_proxy_failed() + + # 如果代理失败次数达到3次，强制更换新代理（第4次重试用新代理） + if self.proxy_fail_count >= 3 and self.use_proxy: + # 检查是否超过代理更换上限 + if proxy_change_count >= max_proxy_changes: + print(f" [X] 已达代理更换上限({max_proxy_changes}次)，放弃重试") + return None + + print(f" [!] 代理已失败{self.proxy_fail_count}次，强制更换新代理") + self.current_proxy = None + self.proxy_fail_count = 0 + new_proxy = self.fetch_proxy(force_new=True) + if new_proxy: + proxy_change_count += 1 + print(f" [✓] 已更换新代理({proxy_change_count}/{max_proxy_changes})，继续重试") + else: + print(f" [X] 无法获取新代理") + return None + + retry_count += 1 + continue + else: + print(f" [X] 请求异常: {e}") + return None + + return None + + def extract_integrated_data_for_date(self, account_id: str, days: int = 7) -> Optional[Dict]: + """提取指定账号在指定日期的整合数据 + + Args: + account_id: 账号ID + days: 查询天数（从target_date往前推） + + Returns: + 整合数据 + """ + import time + import random + + print(f"\n{'='*70}") + print(f"开始提取账号数据: {account_id}") + print(f"目标日期: {self.target_date_str}") + print(f"{'='*70}") + + if not self.set_account_cookies(account_id): + return None + + result = { + 'account_id': account_id, + 'fetch_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'), + 'target_date': self.target_date_str, + 'status': 'unknown', + 'analytics': {}, + 'income': {}, + 'error_info': {} + } + + # 1. 获取发文统计数据 + print("\n[1/2] 获取发文统计数据...") + api_data = self.fetch_analytics_api_for_date(days=days) + if api_data: + result['analytics'] = api_data + print("[OK] 发文统计数据获取成功") + else: + print("[X] 发文统计数据获取失败") + result['error_info']['analytics'] = 'API调用失败' + + # API调用间隔 + api_delay = random.uniform(2, 4) + print(f"\n[间隔] 等待 {api_delay:.1f} 秒...") + time.sleep(api_delay) + + # 2. 获取收入数据 + print("\n[2/2] 获取收入数据...") + income_data = self.fetch_income_for_date() + if income_data: + result['income'] = income_data + print("[OK] 收入数据获取成功") + else: + print("[X] 收入数据获取失败") + result['error_info']['income'] = 'API调用失败' + + # 设置状态 + if result['analytics'] and result['income']: + result['status'] = 'success_all' + elif result['analytics'] or result['income']: + result['status'] = 'success_partial' + else: + result['status'] = 'failed' + + return result + + def extract_all_for_date(self, days: int = 7, delay_seconds: float = 3.0) -> List[Dict]: + """提取所有账号在指定日期的数据 + + Args: + days: 查询天数 + delay_seconds: 账号间延迟 + + Returns: + 所有账号的数据 + """ + import random + + if not self.account_cookies: + print("[X] 没有可用的账号Cookie") + return [] + + print("\n" + "="*70) + print(f"开始提取 {len(self.account_cookies)} 个账号的数据") + print(f"目标日期: {self.target_date_str}") + print("="*70) + + results = [] + + for idx, account_id in enumerate(self.account_cookies.keys(), 1): + print(f"\n[{idx}/{len(self.account_cookies)}] 处理账号: {account_id}") + + result = self.extract_integrated_data_for_date(account_id, days=days) + if result: + results.append(result) + + # 添加延迟 + if idx < len(self.account_cookies): + actual_delay = delay_seconds * random.uniform(0.7, 1.3) + print(f"\n[延迟] 等待 {actual_delay:.1f} 秒后继续...") + import time + time.sleep(actual_delay) + + return results + + def save_results(self, results: List[Dict]): + """保存结果到文件（同时备份带时间戳的副本） + + Args: + results: 数据分析结果列表 + """ + import json + import shutil + + try: + # 1. 保存到主文件（不带时间戳） + with open(self.output_file, 'w', encoding='utf-8') as f: + json.dump(results, f, ensure_ascii=False, indent=2) + + print(f"\n{'='*70}") + print(f"[OK] 数据已保存到: {self.output_file}") + + # 2. 创建带时间戳的备份文件（只保留日期） + timestamp = datetime.now().strftime('%Y%m%d') + backup_filename = f"bjh_integrated_data_{timestamp}.json" + backup_file = os.path.join(self.backup_dir, backup_filename) + + # 复制文件到备份目录 + shutil.copy2(self.output_file, backup_file) + print(f"[OK] 备份已保存到: {backup_file}") + print(f"{'='*70}") + + # 显示统计 + success_count = sum(1 for r in results if r.get('status', '').startswith('success')) + print(f"\n统计信息:") + print(f" - 总账号数: {len(results)}") + print(f" - 成功获取: {success_count}") + print(f" - 失败: {len(results) - success_count}") + + except Exception as e: + print(f"[X] 保存文件失败: {e}") + + +def main(): + """主函数""" + parser = argparse.ArgumentParser( + description='百家号指定日期数据抓取工具', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +示例用法: + python bjh_analytics_date.py 2025-12-20 + python bjh_analytics_date.py 2025-12-20 --days 7 + python bjh_analytics_date.py 2025-12-20 --proxy + python bjh_analytics_date.py 2025-12-20 --database + python bjh_analytics_date.py 2025-12-20 --account "乳腺专家林华" # 仅测试单个账号 + """ + ) + + parser.add_argument( + 'date', + type=str, + help='目标日期 (格式: YYYY-MM-DD)' + ) + + parser.add_argument( + '--days', + type=int, + default=7, + help='查询天数（从目标日期往前推，默认7天）' + ) + + parser.add_argument( + '--proxy', + action='store_true', + default=True, # 默认启用代理 + help='启用代理（默认启用）' + ) + + parser.add_argument( + '--no-proxy', + dest='proxy', + action='store_false', + help='禁用代理' + ) + + parser.add_argument( + '--database', + action='store_true', + default=True, # 默认从数据库加载Cookie + help='从数据库加载Cookie（默认启用）' + ) + + parser.add_argument( + '--local', + dest='database', + action='store_false', + help='从本地JSON文件加载Cookie' + ) + + parser.add_argument( + '--delay', + type=float, + default=3.0, + help='账号间延迟时间（秒，默认3.0）' + ) + + parser.add_argument( + '--account', + type=str, + default=None, + help='仅抓取指定账号（用于测试），格式：账号名称' + ) + + parser.add_argument( + '--no-confirm', + action='store_true', + help='跳过确认提示，直接开始抓取（用于批量脚本）' + ) + + args = parser.parse_args() + + # 验证日期格式 + try: + datetime.strptime(args.date, '%Y-%m-%d') + except ValueError: + print(f"[X] 日期格式错误: {args.date}") + print(" 正确格式: YYYY-MM-DD (例如: 2025-12-20)") + return 1 + + print("\n" + "="*70) + print("百家号指定日期数据抓取工具") + print("="*70) + print(f"目标日期: {args.date}") + print(f"查询天数: {args.days}") + print(f"使用代理: {'是' if args.proxy else '否'}") + print(f"数据源: {'数据库' if args.database else '本地文件'}") + print("="*70) + + try: + # 创建分析器 + analytics = BaijiahaoDateAnalytics( + target_date=args.date, + use_proxy=args.proxy, + load_from_db=args.database + ) + + if not analytics.account_cookies: + print("\n[X] 未找到可用的账号Cookie") + return 1 + + # 如果指定了单个账号，验证是否存在 + if args.account: + if args.account not in analytics.account_cookies: + print(f"\n[X] 未找到指定账号: {args.account}") + print(f"\n可用账号列表:") + for idx, account_name in enumerate(analytics.account_cookies.keys(), 1): + print(f" {idx}. {account_name}") + return 1 + + # 只保留指定账号 + analytics.account_cookies = {args.account: analytics.account_cookies[args.account]} + print(f"\n[测试模式] 仅抓取账号: {args.account}") + + print(f"\n找到 {len(analytics.account_cookies)} 个账号") + + # 确认执行（除非使用--no-confirm参数） + if not args.no_confirm: + confirm = input("\n是否开始抓取? (y/n): ").strip().lower() + if confirm != 'y': + print("已取消") + return 0 + + # 提取所有账号数据 + results = analytics.extract_all_for_date( + days=args.days, + delay_seconds=args.delay + ) + + if results: + analytics.save_results(results) + + # 显示统计 + success_all = sum(1 for r in results if r.get('status') == 'success_all') + success_partial = sum(1 for r in results if r.get('status') == 'success_partial') + failed = sum(1 for r in results if r.get('status') == 'failed') + + print(f"\n{'='*70}") + print("数据提取统计") + print(f"{'='*70}") + print(f" 总账号数: {len(results)}") + print(f" 全部成功: {success_all}") + print(f" 部分成功: {success_partial}") + print(f" 失败: {failed}") + print(f"{'='*70}") + + return 0 + else: + print("\n[X] 未获取到任何数据") + return 1 + + except Exception as e: + print(f"\n[X] 程序执行出错: {e}") + import traceback + traceback.print_exc() + return 1 + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/bjh_daemon.service b/bjh_daemon.service index e50f40e..7d13ebd 100644 --- a/bjh_daemon.service +++ b/bjh_daemon.service @@ -1,6 +1,7 @@ [Unit] -Description=百家号数据同步守护进程 -After=network.target +Description=百家号数据同步守护进程（含数据验证与短信告警） +After=network.target mysql.service +Wants=mysql.service [Service] Type=simple @@ -12,8 +13,18 @@ RestartSec=10 StandardOutput=journal StandardError=journal -# 环境变量（如果需要） -# Environment="PATH=/usr/local/bin:/usr/bin:/bin" +# 环境变量配置 +Environment="LOAD_FROM_DB=true" +Environment="USE_PROXY=true" +Environment="DAYS=7" +Environment="MAX_RETRIES=3" +Environment="RUN_NOW=true" +Environment="ENABLE_VALIDATION=true" +Environment="NON_INTERACTIVE=true" + +# 阿里云短信服务凭据（可选，也可使用sms_config.json） +# Environment="ALIBABA_CLOUD_ACCESS_KEY_ID=your_access_key_id" +# Environment="ALIBABA_CLOUD_ACCESS_KEY_SECRET=your_access_key_secret" [Install] WantedBy=multi-user.target diff --git a/bjh_data_daemon.py b/bjh_data_daemon.py index dc32f50..c71041d 100644 --- a/bjh_data_daemon.py +++ b/bjh_data_daemon.py @@ -27,12 +27,12 @@ from log_config import setup_bjh_daemon_logger class BaijiahaoDataDaemon: """百家号数据定时更新守护进程""" - def __init__(self, update_interval_hours: int = 6, use_proxy: bool = False, load_from_db: bool = False): + def __init__(self, update_interval_hours: int = 1, use_proxy: bool = False, load_from_db: bool = False): """ 初始化守护进程 Args: - update_interval_hours: 更新间隔（小时），默认6小时 + update_interval_hours: 更新间隔（小时），默认1小时 use_proxy: 是否使用代理，默认False load_from_db: 是否从数据库加载Cookie，默认False """ @@ -371,8 +371,8 @@ def main(): print("\n请配置守护进程参数:\n") # 更新间隔 - interval_input = input("1. 更新间隔（小时，默认6小时）: ").strip() - update_interval = int(interval_input) if interval_input.isdigit() and int(interval_input) > 0 else 6 + interval_input = input("1. 更新间隔（小时，默认1小时）: ").strip() + update_interval = int(interval_input) if interval_input.isdigit() and int(interval_input) > 0 else 1 # 查询天数 days_input = input("2. 查询天数（默认7天）: ").strip() diff --git a/bjh_integrated_data.json b/bjh_integrated_data.json index 942d830..de836ee 100644 --- a/bjh_integrated_data.json +++ b/bjh_integrated_data.json @@ -1,39 +1,40 @@ [ { "account_id": "乳腺专家林华", - "fetch_time": "2025-12-24 17:41:34", + "fetch_time": "2025-12-26 16:06:53", + "target_date": "2025-12-1", "status": "success_all", "analytics": { "apis": [ { "endpoint": "/author/eco/statistics/appStatisticV3", "name": "发文统计", - "date_range": "20251217 - 20251223", + "date_range": "20251125 - 20251201", "data": { "errno": 0, "errmsg": "success", "data": { - "latest_event_day": 20251223, + "latest_event_day": 20251225, "total_info": { "add_view_count": "0", - "auto_slide_cnt": "202", + "auto_slide_cnt": "228", "avg_play_duration_hb": "", "c_app_id": "12383700888897988", - "click_rate": "3.57", + "click_rate": "3.84", "click_rate_hb": "", "collect_count": "0", "collect_count_hb": "0", "collect_rate": "0", - "comment_count": "9", - "comment_count_hb": "125.00", - "comment_rate": "0.41", - "completion_view_count": "26", - "completion_view_rate": "38.24", + "comment_count": "7", + "comment_count_hb": "75.00", + "comment_rate": "0.30", + "completion_view_count": "34", + "completion_view_rate": "37.78", "completion_view_rate_hb": "", "coupons_add_view_count": "0", - "disp_pv": "20634", - "disp_pv_hb": "-7.52", - "effective_distribution_count": "51", + "disp_pv": "20027", + "disp_pv_hb": "-7.62", + "effective_distribution_count": "67", "event_day": "", "fake_view_count": "0", "fans_add_cnt": "0", @@ -43,7 +44,7 @@ "fans_cancel_cnt": "0", "fans_cancel_cnt_hb": "", "fans_cancel_cnt_rate": "0", - "fans_click_rate": "3.70", + "fans_click_rate": "2.90", "fans_collect_count": "0", "fans_collect_rate": "0", "fans_comment_count": "0", @@ -55,117 +56,51 @@ "fans_likes_rate": "0", "fans_pic_slide_cnt": "1", "fans_pic_slide_rate": "33.33", - "fans_pic_slide_rate_hb": "133.24", - "fans_recommend_count": "108", + "fans_pic_slide_rate_hb": "0", + "fans_recommend_count": "69", "fans_share_count": "0", "fans_share_rate": "0", "fans_uninterested_count": "0", "fans_uninterested_rate": "0", - "fans_view_count": "4", + "fans_view_count": "2", "hudong_rate_hb": "", "is_show_add": "0", "is_show_add_view": "0", "is_wind_plan_medal": "0", - "likes_count": "14", - "likes_count_hb": "55.56", - "likes_rate": "0.64", + "likes_count": "10", + "likes_count_hb": "0", + "likes_rate": "0.43", "mcn_coupons_add_view_count": "0", "other_coupons_add_view_count": "0", - "pic_slide_cnt": "18", - "pic_slide_rate": "8.18", - "pic_slide_rate_hb": "-45.72", + "pic_slide_cnt": "31", + "pic_slide_rate": "11.97", + "pic_slide_rate_hb": "4.72", "platform_add_view_count": "0", "publish_count": "0", "publish_count_hb": "-100.00", - "real_view_count": "2179", - "recommend_count": "1848", - "search_click_pv": "240", - "share_count": "2", + "real_view_count": "2300", + "recommend_count": "2079", + "search_click_pv": "202", + "share_count": "3", "share_count_hb": "0", - "share_rate": "0.09", - "shoubai3_first_click_cnt": "60", - "shoubai3_first_disp_cnt": "1679", - "total_view_count": "68", + "share_rate": "0.13", + "shoubai3_first_click_cnt": "73", + "shoubai3_first_disp_cnt": "1902", + "total_view_count": "90", "type": "event", "uninterested_count": "0", "uninterested_count_hb": "", "uninterested_rate": "0", "valid_play_pv": "0", - "valid_play_pv_rate": "75.00", + "valid_play_pv_rate": "74.44", "valid_play_pv_rate_hb": "", - "view_3s_count": "15", - "view_3s_rate": "0.69", + "view_3s_count": "20", + "view_3s_rate": "0.87", "view_3s_rate_hb": "", - "view_count": "2179", - "view_count_hb": "-40.76" + "view_count": "2300", + "view_count_hb": "33.95" }, "list": [ - { - "add_view_count": "0", - "collect_count": "0", - "collect_rate": "0", - "comment_count": "2", - "comment_rate": "0.74", - "coupons_add_view_count": "0", - "disp_pv": "2889", - "event_day": "20251217", - "fans_collect_count": "0", - "fans_collect_rate": "0", - "fans_comment_count": "0", - "fans_comment_rate": "0", - "fans_likes_count": "0", - "fans_likes_rate": "0", - "fans_pic_slide_rate": "0", - "fans_share_count": "0", - "fans_share_rate": "0", - "fans_view_count": "1", - "is_show_add": "0", - "is_show_add_view": "0", - "is_wind_plan_medal": "0", - "likes_count": "4", - "likes_rate": "1.48", - "mcn_coupons_add_view_count": "0", - "other_coupons_add_view_count": "0", - "pic_slide_rate": "0", - "platform_add_view_count": "0", - "publish_count": "0", - "share_count": "0", - "share_rate": "0", - "view_count": "270" - }, - { - "add_view_count": "0", - "collect_count": "0", - "collect_rate": "0", - "comment_count": "0", - "comment_rate": "0", - "coupons_add_view_count": "0", - "disp_pv": "3141", - "event_day": "20251218", - "fans_collect_count": "0", - "fans_collect_rate": "0", - "fans_comment_count": "0", - "fans_comment_rate": "0", - "fans_likes_count": "0", - "fans_likes_rate": "0", - "fans_pic_slide_rate": "0", - "fans_share_count": "0", - "fans_share_rate": "0", - "fans_view_count": "1", - "is_show_add": "0", - "is_show_add_view": "0", - "is_wind_plan_medal": "0", - "likes_count": "0", - "likes_rate": "0", - "mcn_coupons_add_view_count": "0", - "other_coupons_add_view_count": "0", - "pic_slide_rate": "0", - "platform_add_view_count": "0", - "publish_count": "0", - "share_count": "0", - "share_rate": "0", - "view_count": "193" - }, { "add_view_count": "0", "collect_count": "0", @@ -299,10 +234,12 @@ "view_count": "418" }, { + "add_view_count": "0", "collect_count": "0", "collect_rate": "0", "comment_count": "2", "comment_rate": "0.59", + "coupons_add_view_count": "0", "disp_pv": "2876", "event_day": "20251223", "fans_collect_count": "0", @@ -315,13 +252,77 @@ "fans_share_count": "0", "fans_share_rate": "0", "fans_view_count": "0", + "is_show_add": "0", + "is_show_add_view": "0", + "is_wind_plan_medal": "0", "likes_count": "2", "likes_rate": "0.59", + "mcn_coupons_add_view_count": "0", + "other_coupons_add_view_count": "0", "pic_slide_rate": "7.69", + "platform_add_view_count": "0", "publish_count": "0", "share_count": "1", "share_rate": "0.29", "view_count": "339" + }, + { + "add_view_count": "0", + "collect_count": "0", + "collect_rate": "0", + "comment_count": "0", + "comment_rate": "0", + "coupons_add_view_count": "0", + "disp_pv": "2762", + "event_day": "20251224", + "fans_collect_count": "0", + "fans_collect_rate": "0", + "fans_comment_count": "0", + "fans_comment_rate": "0", + "fans_likes_count": "0", + "fans_likes_rate": "0", + "fans_pic_slide_rate": "0", + "fans_share_count": "0", + "fans_share_rate": "0", + "fans_view_count": "0", + "is_show_add": "0", + "is_show_add_view": "0", + "is_wind_plan_medal": "0", + "likes_count": "0", + "likes_rate": "0", + "mcn_coupons_add_view_count": "0", + "other_coupons_add_view_count": "0", + "pic_slide_rate": "21.95", + "platform_add_view_count": "0", + "publish_count": "0", + "share_count": "1", + "share_rate": "0.34", + "view_count": "292" + }, + { + "collect_count": "0", + "collect_rate": "0", + "comment_count": "0", + "comment_rate": "0", + "disp_pv": "2661", + "event_day": "20251225", + "fans_collect_count": "0", + "fans_collect_rate": "0", + "fans_comment_count": "0", + "fans_comment_rate": "0", + "fans_likes_count": "0", + "fans_likes_rate": "0", + "fans_pic_slide_rate": "0", + "fans_share_count": "0", + "fans_share_rate": "0", + "fans_view_count": "0", + "likes_count": "0", + "likes_rate": "0", + "pic_slide_rate": "10.81", + "publish_count": "0", + "share_count": "0", + "share_rate": "0", + "view_count": "292" } ], "export_conf": { @@ -358,15 +359,15 @@ }, "channel_view_count": { "个人号主页": "0", - "其他": "3313367", + "其他": "3313918", "好看": "0", - "推荐页": "151817", + "推荐页": "151850", "搜索页": "0", "站外分享": "0" } } }, - "fetch_time": "2025-12-24 17:41:35" + "fetch_time": "2025-12-26 16:06:53" } ], "count": 1 @@ -379,34353 +380,28 @@ "format_total_income": "", "income": { "yesterday": { - "value": "17.31", - "comparisonPercentage": "2.66", - "income": 17.31, - "last_income": 14.65 - }, - "recent7Days": { - "value": "90.78", - "comparisonPercentage": "-10.24", - "income": 90.78, - "last_income": 101.02 - }, - "recent30Days": { - "value": "565.90", - "comparisonPercentage": "307.76", - "income": 565.9, - "last_income": 258.14 - }, - "currentMonth": { - "value": "401.48", - "comparisonPercentage": "19.61", - "income": 401.48, - "last_income": 381.87 - }, - "customize": { - "value": "0.00", - "comparisonPercentage": "0", - "income": 0, - "last_income": 0 - } - } - } - }, - "error_info": {} - }, - { - "account_id": "韩主任聊妇科", - "fetch_time": "2025-12-24 17:41:42", - "status": "success_all", - "analytics": { - "apis": [ - { - "endpoint": "/author/eco/statistics/appStatisticV3", - "name": "发文统计", - "date_range": "20251217 - 20251223", - "data": { - "errno": 0, - "errmsg": "success", - "data": { - "latest_event_day": 20251223, - "total_info": { - "add_view_count": "0", - "auto_slide_cnt": "19977", - "avg_play_duration_hb": "", - "c_app_id": "11740257018917574", - "click_rate": "3.88", - "click_rate_hb": "", - "collect_count": "3", - "collect_count_hb": "-50.00", - "collect_rate": "0.00", - "comment_count": "69", - "comment_count_hb": "40.82", - "comment_rate": "0.03", - "completion_view_count": "3347", - "completion_view_rate": "34.64", - "completion_view_rate_hb": "", - "coupons_add_view_count": "0", - "disp_pv": "177273", - "disp_pv_hb": "-4.43", - "effective_distribution_count": "6980", - "event_day": "", - "fake_view_count": "0", - "fans_add_cnt": "5", - "fans_add_cnt_hb": "", - "fans_add_cnt_rate": "0.00", - "fans_auto_slide_cnt": "181", - "fans_cancel_cnt": "1", - "fans_cancel_cnt_hb": "", - "fans_cancel_cnt_rate": "0.00", - "fans_click_rate": "3.35", - "fans_collect_count": "0", - "fans_collect_rate": "0", - "fans_comment_count": "0", - "fans_comment_rate": "0", - "fans_increase": "4", - "fans_increase_hb": "", - "fans_increase_rate": "0.00", - "fans_likes_count": "2", - "fans_likes_rate": "2.13", - "fans_pic_slide_cnt": "57", - "fans_pic_slide_rate": "23.95", - "fans_pic_slide_rate_hb": "-20.06", - "fans_recommend_count": "2805", - "fans_share_count": "0", - "fans_share_rate": "0", - "fans_uninterested_count": "4", - "fans_uninterested_rate": "4.26", - "fans_view_count": "94", - "hudong_rate_hb": "", - "is_show_add": "0", - "is_show_add_view": "0", - "is_wind_plan_medal": "0", - "likes_count": "145", - "likes_count_hb": "35.51", - "likes_rate": "0.06", - "mcn_coupons_add_view_count": "0", - "other_coupons_add_view_count": "0", - "pic_slide_cnt": "6144", - "pic_slide_rate": "23.52", - "pic_slide_rate_hb": "10.37", - "platform_add_view_count": "0", - "publish_count": "74", - "publish_count_hb": "37.04", - "real_view_count": "240039", - "recommend_count": "222988", - "search_click_pv": "2126", - "share_count": "30", - "share_count_hb": "-11.76", - "share_rate": "0.01", - "shoubai3_first_click_cnt": "7938", - "shoubai3_first_disp_cnt": "204364", - "total_view_count": "9662", - "type": "event", - "uninterested_count": "78", - 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"value": "73.22", - "comparisonPercentage": "73.22", - "income": 73.22, - "last_income": 0 + "value": "449.53", + "comparisonPercentage": "67.66", + "income": 449.53, + "last_income": 381.87 }, "customize": { "value": "0.00", diff --git a/calc_ip.py b/calc_ip.py new file mode 100644 index 0000000..e69de29 diff --git a/data_sync_daemon.py b/data_sync_daemon.py index 5dcfe7b..c5e4aa7 100644 --- a/data_sync_daemon.py +++ b/data_sync_daemon.py @@ -4,18 +4,20 @@ 数据同步守护进程 功能： -1. 24小时不间断运行 -2. 在每天午夜（00:00）自动执行数据抓取和同步 +1. 24小时不间断运行（仅在工作时间8:00-24:00执行任务） +2. 每隔1小时自动执行数据抓取和同步 3. 自动执行流程： - 从百家号API抓取最新数据 - 生成CSV文件（包含从数据库查询的author_id） - 将CSV数据导入到数据库 4. 支持手动触发刷新 5. 详细的日志记录 +6. 非工作时间（0:00-8:00）自动休眠，减少API请求压力 使用场景： -- 24/7运行，每天凌晨自动更新数据 +- 24/7运行，在工作时间（8:00-24:00）每隔1小时自动更新数据 - 无需人工干预，自动化数据同步 +- 避免在夜间时段进行数据抓取 """ import sys @@ -38,11 +40,19 @@ from export_to_csv import DataExporter from import_csv_to_database import CSVImporter from log_config import setup_logger +# 导入数据验证与短信告警模块 +try: + from data_validation_with_sms import DataValidationWithSMS + VALIDATION_AVAILABLE = True +except ImportError: + print("[!] 数据验证模块未找到，验证功能将不可用") + VALIDATION_AVAILABLE = False + class DataSyncDaemon: """数据同步守护进程""" - def __init__(self, use_proxy: bool = False, load_from_db: bool = True, days: int = 7, max_retries: int = 3): + def __init__(self, use_proxy: bool = False, load_from_db: bool = True, days: int = 7, max_retries: int = 3, enable_validation: bool = True): """初始化守护进程 Args: @@ -50,16 +60,28 @@ class DataSyncDaemon: load_from_db: 是否从数据库加载Cookie days: 抓取最近多少天的数据 max_retries: 最大重试次数 + enable_validation: 是否启用数据验证与短信告警 """ self.script_dir = os.path.dirname(os.path.abspath(__file__)) self.use_proxy = use_proxy self.load_from_db = load_from_db self.days = days self.max_retries = max_retries + self.enable_validation = enable_validation and VALIDATION_AVAILABLE + + # 工作时间配置（8:00-24:00） + self.work_start_hour = 8 + self.work_end_hour = 24 # 初始化日志 self.logger = setup_logger('data_sync_daemon', os.path.join(self.script_dir, 'logs', 'data_sync_daemon.log')) + # 创建验证报告目录 + self.validation_reports_dir = os.path.join(self.script_dir, 'validation_reports') + if not os.path.exists(self.validation_reports_dir): + os.makedirs(self.validation_reports_dir) + self.logger.info(f"创建验证报告目录: {self.validation_reports_dir}") + # 统计信息 self.stats = { 'total_runs': 0, @@ -76,13 +98,17 @@ class DataSyncDaemon: print(f" 使用代理: {'是' if use_proxy else '否'}") print(f" Cookie来源: {'数据库' if load_from_db else '本地文件'}") print(f" 抓取天数: {days}天") + print(f" 工作时间: {self.work_start_hour}:00 - {self.work_end_hour}:00") print(f" 错误重试: 最大{max_retries}次") - print(f" 定时执行: 每天午夜00:00") + print(f" 定时执行: 每隔1小时") + print(f" 数据验证: {'已启用' if self.enable_validation else '已禁用'}") + if self.enable_validation: + print(f" 短信告警: 验证失败时发送 (错误代码2222)") print("="*70 + "\n") self.logger.info("="*70) self.logger.info("数据同步守护进程启动") - self.logger.info(f"使用代理: {use_proxy}, Cookie来源: {'数据库' if load_from_db else '本地文件'}, 抓取天数: {days}, 重试: {max_retries}次") + self.logger.info(f"使用代理: {use_proxy}, Cookie来源: {'数据库' if load_from_db else '本地文件'}, 抓取天数: {days}, 工作时间: {self.work_start_hour}:00-{self.work_end_hour}:00, 重试: {max_retries}次, 验证: {'已启用' if self.enable_validation else '已禁用'}") self.logger.info("="*70) def fetch_data(self) -> bool: @@ -294,6 +320,77 @@ class DataSyncDaemon: self.logger.error(f"数据库导入失败: {e}", exc_info=True) return False + def validate_data(self) -> bool: + """步顷4：数据验证与短信告警""" + if not self.enable_validation: + print("\n[跳过] 数据验证功能未启用") + self.logger.info("跳过数据验证（功能未启用）") + return True + + print("\n" + "="*70) + print("【步顷4/4】数据验证与短信告警") + print("="*70) + + try: + # 等待3秒，确保数据库写入完成 + print("\n等待3秒，确保数据写入完成...") + self.logger.info("等待3秒以确保数据库写入完成") + time.sleep(3) + + print("\n执行数据验证...") + self.logger.info("开始执行数据验证") + + # 创建验证器（验证昨天的数据） + yesterday = (datetime.now() - timedelta(days=1)).strftime('%Y-%m-%d') + validator = DataValidationWithSMS(date_str=yesterday) + + # 执行验证（JSON + CSV + Database） + passed = validator.run_validation( + sources=['json', 'csv', 'database'], + table='ai_statistics' + ) + + # 生成验证报告 + timestamp = datetime.now().strftime('%Y%m%d_%H%M%S') + report_file = os.path.join( + self.validation_reports_dir, + f'validation_report_{timestamp}.txt' + ) + validator.validator.generate_report(report_file) + + if passed: + print("\n[✓] 数据验证通过") + self.logger.info("数据验证通过") + return True + else: + print("\n[X] 数据验证失败，准备发送短信告警") + self.logger.error("数据验证失败") + + # 生成错误摘要 + error_summary = validator.generate_error_summary() + self.logger.error(f"错误摘要: {error_summary}") + + # 发送短信告警（错误代码2222） + sms_sent = validator.send_sms_alert("2222", error_summary) + + if sms_sent: + print("[✓] 告警短信已发送") + self.logger.info("告警短信发送成功") + else: + print("[X] 告警短信发送失败") + self.logger.error("告警短信发送失败") + + print(f"\n详细报告: {report_file}") + + # 验证失败不阻止后续流程，但返回True表示步骤完成 + return True + + except Exception as e: + print(f"\n[X] 数据验证异常: {e}") + self.logger.error(f"数据验证异常: {e}", exc_info=True) + # 验证异常不影响整体流程 + return True + def sync_data(self): """执行完整的数据同步流程""" start_time = datetime.now() @@ -317,9 +414,14 @@ class DataSyncDaemon: if not self.generate_csv(): raise Exception("CSV生成失败") - # 步骤3：导入数据库 + # 步顷3：导入数据库 if not self.import_to_database(): raise Exception("数据库导入失败") + + # 步顷4：数据验证与短信告警 + if not self.validate_data(): + # 验证失败不阻止整体流程，只记录警告 + self.logger.warning("数据验证步骤未成功完成") # 成功 end_time = datetime.now() @@ -370,12 +472,36 @@ class DataSyncDaemon: self.logger.info(f"运行统计: 总{self.stats['total_runs']}次, 成功{self.stats['successful_runs']}次, 失败{self.stats['failed_runs']}次") - def get_next_midnight(self) -> datetime: - """获取下一个午夜时刻""" + def is_work_time(self) -> tuple: + """ + 检查当前是否在工作时间内（8:00-24:00） + + Returns: + tuple: (是否在工作时间内, 距离下次工作时间的秒数) + """ now = datetime.now() - tomorrow = now + timedelta(days=1) - next_midnight = tomorrow.replace(hour=0, minute=0, second=0, microsecond=0) - return next_midnight + current_hour = now.hour + + # 在工作时间内（8:00-23:59） + if self.work_start_hour <= current_hour < self.work_end_hour: + return True, 0 + + # 不在工作时间内，计算到下个工作时间的秒数 + if current_hour < self.work_start_hour: + # 今天还没到工作时间 + next_work_time = now.replace(hour=self.work_start_hour, minute=0, second=0, microsecond=0) + else: + # 今天已过工作时间，等待明天 + next_work_time = (now + timedelta(days=1)).replace(hour=self.work_start_hour, minute=0, second=0, microsecond=0) + + seconds_until_work = (next_work_time - now).total_seconds() + return False, seconds_until_work + + def get_next_run_time(self) -> datetime: + """获取下一次执行时间（1小时后）""" + now = datetime.now() + next_run = now + timedelta(hours=1) + return next_run def run(self): """启动守护进程""" @@ -383,22 +509,51 @@ class DataSyncDaemon: print("守护进程已启动") print("="*70) - # 设置定时任务：每天午夜00:00执行 - schedule.every().day.at("00:00").do(self.sync_data) + # 设置定时任务：每隔1小时执行 + schedule.every(1).hours.do(self.sync_data) # 计算下次执行时间 - next_run = self.get_next_midnight() + next_run = self.get_next_run_time() time_until_next = (next_run - datetime.now()).total_seconds() - print(f"\n下次执行时间: {next_run.strftime('%Y-%m-%d %H:%M:%S')}") - print(f"距离下次执行: {time_until_next/3600:.1f} 小时") + print(f"\n执行间隔: 每隔1小时") + print(f"工作时间: {self.work_start_hour}:00 - {self.work_end_hour}:00（非工作时间自动休眠）") + print(f"下次执行时间: {next_run.strftime('%Y-%m-%d %H:%M:%S')}") + print(f"距离下次执行: {time_until_next/60:.1f} 分钟") print("\n按 Ctrl+C 可以停止守护进程") print("="*70 + "\n") - self.logger.info(f"守护进程已启动，下次执行时间: {next_run.strftime('%Y-%m-%d %H:%M:%S')}") + self.logger.info(f"守护进程已启动，执行间隔: 每隔1小时，工作时间: {self.work_start_hour}:00-{self.work_end_hour}:00，下次执行时间: {next_run.strftime('%Y-%m-%d %H:%M:%S')}") try: while True: + # 检查是否在工作时间内 + is_work, seconds_until_work = self.is_work_time() + + if not is_work: + # 不在工作时间内，等待至工作时间 + next_work_time = datetime.now() + timedelta(seconds=seconds_until_work) + self.logger.info(f"当前非工作时间，等待至 {next_work_time.strftime('%Y-%m-%d %H:%M:%S')}") + print(f"\n[休眠] 当前不在工作时间内（{self.work_start_hour}:00-{self.work_end_hour}:00）") + print(f"[休眠] 下次工作时间: {next_work_time.strftime('%Y-%m-%d %H:%M:%S')}") + print(f"[休眠] 等待 {seconds_until_work/3600:.1f} 小时...") + + # 每30分钟检查一次 + check_interval = 1800 + elapsed = 0 + + while elapsed < seconds_until_work: + sleep_time = min(check_interval, seconds_until_work - elapsed) + time.sleep(sleep_time) + elapsed += sleep_time + + remaining = seconds_until_work - elapsed + if remaining > 0: + print(f" 距离工作时间还有: {remaining/3600:.1f} 小时 ({datetime.now().strftime('%H:%M:%S')})") + + continue + + # 在工作时间内，执行定时任务 schedule.run_pending() time.sleep(60) # 每分钟检查一次 @@ -427,13 +582,15 @@ def main(): print(" USE_PROXY=true/false - 是否使用代理") print(" DAYS=7 - 抓取天数") print(" MAX_RETRIES=3 - 重试次数") - print(" RUN_NOW=true/false - 是否立即执行\n") + print(" RUN_NOW=true/false - 是否立即执行") + print(" ENABLE_VALIDATION=true/false - 是否启用验证\n") load_from_db = os.getenv('LOAD_FROM_DB', 'true').lower() == 'true' use_proxy = os.getenv('USE_PROXY', 'true').lower() == 'true' days = int(os.getenv('DAYS', '7')) max_retries = int(os.getenv('MAX_RETRIES', '3')) run_now = os.getenv('RUN_NOW', 'true').lower() == 'true' + enable_validation = os.getenv('ENABLE_VALIDATION', 'true').lower() == 'true' else: # 交互模式：显示菜单 # 配置选项 @@ -468,9 +625,15 @@ def main(): except ValueError: max_retries = 3 - # 5. 是否立即执行一次 - print("\n5. 是否立即执行一次同步？") - print(" (否则等待到午夜00:00执行)") + # 5. 是否启用数据验证 + print("\n5. 是否启用数据验证与短信告警？") + print(" (每次同步后自动验证数据，失败时发送短信2222)") + enable_validation_input = input(" (y/n, 默认y): ").strip().lower() or 'y' + enable_validation = (enable_validation_input == 'y') + + # 6. 是否立即执行一次 + print("\n6. 是否立即执行一次同步？") + print(" (否则等待到下一个整点小时执行)") run_now_input = input(" (y/n, 默认n): ").strip().lower() or 'n' run_now = (run_now_input == 'y') @@ -480,9 +643,13 @@ def main(): print(f" Cookie来源: {'数据库' if load_from_db else '本地文件'}") print(f" 使用代理: {'是' if use_proxy else '否'}") print(f" 抓取天数: {days}天") + print(f" 工作时间: 8:00 - 24:00（非工作时间自动休眠）") print(f" 错误重试: 最大{max_retries}次") + print(f" 数据验证: {'已启用' if enable_validation else '已禁用'}") + if enable_validation: + print(f" 短信告警: 验证失败时发送 (错误代码2222)") print(f" 立即执行: {'是' if run_now else '否'}") - print(f" 定时执行: 每天午夜00:00") + print(f" 定时执行: 每隔1小时") print("="*70) confirm = input("\n确认启动守护进程？(y/n): ").strip().lower() @@ -491,7 +658,13 @@ def main(): return # 创建守护进程 - daemon = DataSyncDaemon(use_proxy=use_proxy, load_from_db=load_from_db, days=days, max_retries=max_retries) + daemon = DataSyncDaemon( + use_proxy=use_proxy, + load_from_db=load_from_db, + days=days, + max_retries=max_retries, + enable_validation=enable_validation + ) # 如果选择立即执行，先执行一次 if run_now: diff --git a/data_validation.py b/data_validation.py new file mode 100644 index 0000000..457dc67 --- /dev/null +++ b/data_validation.py @@ -0,0 +1,769 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +数据比对验证脚本 + +功能： +1. 顺序验证：验证不同数据源中记录的顺序一致性 +2. 交叉验证：对比数据内容，识别缺失、新增或不匹配的记录 + +支持的数据源： +- JSON文件 (bjh_integrated_data.json) +- CSV文件 (ai_statistics_*.csv) +- MySQL数据库 (ai_statistics_* 表) + +使用方法： + # 验证JSON和CSV的一致性 + python data_validation.py --source json csv --date 2025-12-29 + + # 验证CSV和数据库的一致性 + python data_validation.py --source csv database --date 2025-12-29 + + # 完整验证（三个数据源） + python data_validation.py --source json csv database --date 2025-12-29 + + # 验证特定表 + python data_validation.py --source csv database --table ai_statistics_day --date 2025-12-29 +""" + +import sys +import os +import json +import csv +import argparse +from datetime import datetime, timedelta +from typing import Dict, List, Tuple, Optional, Any, Set +from collections import OrderedDict +import hashlib + +# 设置UTF-8编码 +if sys.platform == 'win32': + import io + if not isinstance(sys.stdout, io.TextIOWrapper) or sys.stdout.encoding != 'utf-8': + sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8') + if not isinstance(sys.stderr, io.TextIOWrapper) or sys.stderr.encoding != 'utf-8': + sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8') + +# 导入数据库配置 +try: + from database_config import DatabaseManager +except ImportError: + print("[X] 无法导入 database_config.py，数据库验证功能将不可用") + DatabaseManager = None + + +class DataValidator: + """数据比对验证器""" + + def __init__(self, date_str: Optional[str] = None): + """初始化 + + Args: + date_str: 目标日期 (YYYY-MM-DD)，默认为昨天 + """ + self.script_dir = os.path.dirname(os.path.abspath(__file__)) + + # 目标日期（默认为昨天） + if date_str: + self.target_date = datetime.strptime(date_str, '%Y-%m-%d') + else: + # 默认使用昨天的日期 + self.target_date = datetime.now() - timedelta(days=1) + + self.date_str = self.target_date.strftime('%Y-%m-%d') + + # 数据库管理器 + self.db_manager = None + if DatabaseManager: + try: + self.db_manager = DatabaseManager() + print(f"[OK] 数据库连接成功") + except Exception as e: + print(f"[!] 数据库连接失败: {e}") + + # 验证结果 + self.validation_results = { + '顺序验证': [], + '交叉验证': [], + '差异统计': {} + } + + def load_json_data(self, file_path: Optional[str] = None) -> Optional[Any]: + """加载JSON数据 + + Args: + file_path: JSON文件路径，默认为 bjh_integrated_data.json + + Returns: + JSON数据字典 + """ + if not file_path: + file_path = os.path.join(self.script_dir, 'bjh_integrated_data.json') + + try: + if not os.path.exists(file_path): + print(f"[X] JSON文件不存在: {file_path}") + return None + + with open(file_path, 'r', encoding='utf-8') as f: + data = json.load(f) + + print(f"[OK] 加载JSON文件: {file_path}") + print(f" 账号数量: {len(data) if isinstance(data, list) else 1}") + return data + + except Exception as e: + print(f"[X] 加载JSON文件失败: {e}") + return None + + def load_csv_data(self, csv_file: str) -> Optional[List[Dict]]: + """加载CSV数据 + + Args: + csv_file: CSV文件名 + + Returns: + CSV数据列表 + """ + csv_path = os.path.join(self.script_dir, csv_file) + + try: + if not os.path.exists(csv_path): + print(f"[X] CSV文件不存在: {csv_path}") + return None + + rows = [] + with open(csv_path, 'r', encoding='utf-8-sig') as f: + reader = csv.DictReader(f) + rows = list(reader) + + print(f"[OK] 加载CSV文件: {csv_file}") + print(f" 记录数量: {len(rows)}") + return rows + + except Exception as e: + print(f"[X] 加载CSV文件失败: {e}") + return None + + def load_database_data(self, table_name: str, date_filter: Optional[str] = None) -> Optional[List[Dict]]: + """从数据库加载数据 + + Args: + table_name: 表名 + date_filter: 日期过滤字段名（如 'date', 'stat_date'） + + Returns: + 数据库记录列表 + """ + if not self.db_manager: + print(f"[X] 数据库管理器未初始化") + return None + + try: + # 构建SQL查询 + if date_filter: + sql = f"SELECT * FROM {table_name} WHERE {date_filter} = %s ORDER BY author_name, channel" + params = (self.date_str,) + else: + sql = f"SELECT * FROM {table_name} ORDER BY author_name, channel" + params = None + + rows = self.db_manager.execute_query(sql, params) + + print(f"[OK] 加载数据库表: {table_name}") + if date_filter: + print(f" 过滤条件: {date_filter} = {self.date_str}") + print(f" 记录数量: {len(rows) if rows else 0}") + + return rows if rows else [] + + except Exception as e: + print(f"[X] 加载数据库数据失败: {e}") + import traceback + traceback.print_exc() + return None + + def generate_record_key(self, record: Dict, key_fields: List[str]) -> str: + """生成记录唯一键 + + Args: + record: 数据记录 + key_fields: 主键字段列表 + + Returns: + 唯一键字符串 + """ + key_values = [] + for field in key_fields: + value = record.get(field, '') + # 统一转为字符串并去除空白 + key_values.append(str(value).strip()) + + return '|'.join(key_values) + + def calculate_record_hash(self, record: Dict, exclude_fields: Optional[Set[str]] = None) -> str: + """计算记录的哈希值（用于内容比对） + + Args: + record: 数据记录 + exclude_fields: 排除的字段集合（如时间戳字段） + + Returns: + MD5哈希值 + """ + if exclude_fields is None: + exclude_fields = {'updated_at', 'created_at', 'fetch_time'} + + # 排序字段并生成稳定的字符串 + sorted_items = [] + for key in sorted(record.keys()): + if key not in exclude_fields: + value = record.get(key, '') + # 浮点数保留4位小数 + if isinstance(value, float): + value = f"{value:.4f}" + sorted_items.append(f"{key}={value}") + + content = '|'.join(sorted_items) + return hashlib.md5(content.encode('utf-8')).hexdigest() + + def validate_order(self, source1_data: List[Dict], source2_data: List[Dict], + source1_name: str, source2_name: str, + key_fields: List[str]) -> Dict: + """顺序验证：验证两个数据源中记录的顺序是否一致 + + Args: + source1_data: 数据源1的数据 + source2_data: 数据源2的数据 + source1_name: 数据源1名称 + source2_name: 数据源2名称 + key_fields: 主键字段列表 + + Returns: + 验证结果字典 + """ + print(f"\n{'='*70}") + print(f"顺序验证: {source1_name} vs {source2_name}") + print(f"{'='*70}") + + result = { + 'source1': source1_name, + 'source2': source2_name, + 'source1_count': len(source1_data), + 'source2_count': len(source2_data), + 'order_match': True, + 'mismatches': [] + } + + # 生成记录键列表 + source1_keys = [self.generate_record_key(r, key_fields) for r in source1_data] + source2_keys = [self.generate_record_key(r, key_fields) for r in source2_data] + + # 比对顺序 + min_len = min(len(source1_keys), len(source2_keys)) + + for i in range(min_len): + if source1_keys[i] != source2_keys[i]: + result['order_match'] = False + result['mismatches'].append({ + 'position': i, + 'source1_key': source1_keys[i], + 'source2_key': source2_keys[i] + }) + + # 输出结果 + if result['order_match'] and len(source1_keys) == len(source2_keys): + print(f"[✓] 顺序一致，记录数相同: {len(source1_keys)}") + else: + print(f"[X] 顺序不一致") + print(f" {source1_name} 记录数: {len(source1_keys)}") + print(f" {source2_name} 记录数: {len(source2_keys)}") + + if result['mismatches']: + print(f" 不匹配位置数: {len(result['mismatches'])}") + # 显示前5个不匹配 + for mismatch in result['mismatches'][:5]: + print(f" 位置{mismatch['position']}: {mismatch['source1_key']} != {mismatch['source2_key']}") + + return result + + def validate_cross(self, source1_data: List[Dict], source2_data: List[Dict], + source1_name: str, source2_name: str, + key_fields: List[str], + compare_fields: Optional[List[str]] = None) -> Dict: + """交叉验证：对比数据内容，识别缺失、新增或不匹配的记录 + + Args: + source1_data: 数据源1的数据 + source2_data: 数据源2的数据 + source1_name: 数据源1名称 + source2_name: 数据源2名称 + key_fields: 主键字段列表 + compare_fields: 需要对比的字段列表（None表示全部字段） + + Returns: + 验证结果字典 + """ + print(f"\n{'='*70}") + print(f"交叉验证: {source1_name} vs {source2_name}") + print(f"{'='*70}") + + # 构建字典：key -> record + source1_dict = {} + for record in source1_data: + key = self.generate_record_key(record, key_fields) + source1_dict[key] = record + + source2_dict = {} + for record in source2_data: + key = self.generate_record_key(record, key_fields) + source2_dict[key] = record + + # 查找差异 + only_in_source1 = set(source1_dict.keys()) - set(source2_dict.keys()) + only_in_source2 = set(source2_dict.keys()) - set(source1_dict.keys()) + common_keys = set(source1_dict.keys()) & set(source2_dict.keys()) + + # 对比共同记录的字段值 + field_mismatches = [] + for key in common_keys: + record1 = source1_dict[key] + record2 = source2_dict[key] + + # 确定要比对的字段 + if compare_fields: + fields_to_compare = compare_fields + else: + fields_to_compare = set(record1.keys()) & set(record2.keys()) + + # 比对每个字段 + mismatches_in_record = {} + for field in fields_to_compare: + val1 = record1.get(field, '') + val2 = record2.get(field, '') + + # 类型转换和标准化 + val1_normalized = self._normalize_value(val1) + val2_normalized = self._normalize_value(val2) + + if val1_normalized != val2_normalized: + mismatches_in_record[field] = { + source1_name: val1, + source2_name: val2 + } + + if mismatches_in_record: + field_mismatches.append({ + 'key': key, + 'fields': mismatches_in_record + }) + + # 输出结果 + result = { + 'source1': source1_name, + 'source2': source2_name, + 'source1_count': len(source1_data), + 'source2_count': len(source2_data), + 'only_in_source1': list(only_in_source1), + 'only_in_source2': list(only_in_source2), + 'common_count': len(common_keys), + 'field_mismatches': field_mismatches + } + + print(f"记录数统计:") + print(f" {source1_name}: {len(source1_data)} 条") + print(f" {source2_name}: {len(source2_data)} 条") + print(f" 共同记录: {len(common_keys)} 条") + print(f" 仅在{source1_name}: {len(only_in_source1)} 条") + print(f" 仅在{source2_name}: {len(only_in_source2)} 条") + print(f" 字段不匹配: {len(field_mismatches)} 条") + + # 显示详细差异 + if only_in_source1: + print(f"\n仅在{source1_name}中的记录（前5条）:") + for key in list(only_in_source1)[:5]: + print(f" - {key}") + + if only_in_source2: + print(f"\n仅在{source2_name}中的记录（前5条）:") + for key in list(only_in_source2)[:5]: + print(f" - {key}") + + if field_mismatches: + print(f"\n字段值不匹配的记录（前3条）:") + for mismatch in field_mismatches[:3]: + print(f" 记录: {mismatch['key']}") + for field, values in list(mismatch['fields'].items())[:5]: # 每条记录最多显示5个字段 + print(f" 字段 {field}:") + print(f" {source1_name}: {values[source1_name]}") + print(f" {source2_name}: {values[source2_name]}") + + return result + + def _normalize_value(self, value: Any) -> str: + """标准化值用于比对 + + Args: + value: 原始值 + + Returns: + 标准化后的字符串 + """ + if value is None or value == '': + return '' + + # 浮点数保留4位小数 + if isinstance(value, float): + return f"{value:.4f}" + + # 整数转字符串 + if isinstance(value, int): + return str(value) + + # 字符串去除首尾空白 + return str(value).strip() + + def validate_ai_statistics(self, sources: List[str]) -> bool: + """验证 ai_statistics 表数据 + + Args: + sources: 数据源列表 ['json', 'csv', 'database'] + + Returns: + 验证是否通过 + """ + print(f"\n{'#'*70}") + print(f"# 验证 ai_statistics 表数据") + print(f"# 日期: {self.date_str}") + print(f"{'#'*70}") + + # 主键字段 + key_fields = ['author_name', 'channel'] + + # 重要字段 + compare_fields = [ + 'submission_count', 'read_count', 'comment_count', 'comment_rate', + 'like_count', 'like_rate', 'favorite_count', 'favorite_rate', + 'share_count', 'share_rate', 'slide_ratio', 'baidu_search_volume' + ] + + # 加载数据 + data_sources = {} + + if 'json' in sources: + json_data = self.load_json_data() + if json_data: + # 确保json_data是列表类型 + if not isinstance(json_data, list): + json_data = [json_data] + # 从JSON提取 ai_statistics 数据 + json_records = self._extract_ai_statistics_from_json(json_data) + data_sources['json'] = json_records + + if 'csv' in sources: + csv_data = self.load_csv_data('ai_statistics.csv') + if csv_data: + data_sources['csv'] = csv_data + + if 'database' in sources: + db_data = self.load_database_data('ai_statistics', date_filter='date') + if db_data: + data_sources['database'] = db_data + + # 执行验证 + if len(data_sources) < 2: + print(f"[X] 数据源不足，至少需要2个数据源进行比对") + return False + + # 两两比对 + source_names = list(data_sources.keys()) + all_passed = True + + for i in range(len(source_names)): + for j in range(i + 1, len(source_names)): + source1_name = source_names[i] + source2_name = source_names[j] + + # 只对 json vs csv 进行顺序验证 + if (source1_name == 'json' and source2_name == 'csv') or \ + (source1_name == 'csv' and source2_name == 'json'): + # 顺序验证 + order_result = self.validate_order( + data_sources[source1_name], + data_sources[source2_name], + source1_name, + source2_name, + key_fields + ) + self.validation_results['顺序验证'].append(order_result) + + if not order_result['order_match']: + all_passed = False + + # 交叉验证（所有组合都执行） + cross_result = self.validate_cross( + data_sources[source1_name], + data_sources[source2_name], + source1_name, + source2_name, + key_fields, + compare_fields + ) + self.validation_results['交叉验证'].append(cross_result) + + # 判断是否通过 + if cross_result['only_in_source1'] or \ + cross_result['only_in_source2'] or \ + cross_result['field_mismatches']: + all_passed = False + + return all_passed + + def validate_ai_statistics_day(self, sources: List[str]) -> bool: + """验证 ai_statistics_day 表数据 + + Args: + sources: 数据源列表 + + Returns: + 验证是否通过 + """ + print(f"\n{'#'*70}") + print(f"# 验证 ai_statistics_day 表数据") + print(f"# 日期: {self.date_str}") + print(f"{'#'*70}") + + key_fields = ['author_name', 'channel', 'stat_date'] + compare_fields = [ + 'total_submission_count', 'total_read_count', 'total_comment_count', + 'total_like_count', 'total_favorite_count', 'total_share_count', + 'avg_comment_rate', 'avg_like_rate', 'avg_favorite_rate', + 'avg_share_rate', 'avg_slide_ratio', 'total_baidu_search_volume' + ] + + # 加载数据 + data_sources = {} + + if 'csv' in sources: + csv_data = self.load_csv_data('ai_statistics_day.csv') + if csv_data: + data_sources['csv'] = csv_data + + if 'database' in sources: + db_data = self.load_database_data('ai_statistics_day', date_filter='stat_date') + if db_data: + data_sources['database'] = db_data + + if len(data_sources) < 2: + print(f"[X] 数据源不足") + return False + + # 执行验证 + source_names = list(data_sources.keys()) + all_passed = True + + for i in range(len(source_names)): + for j in range(i + 1, len(source_names)): + source1_name = source_names[i] + source2_name = source_names[j] + + # ai_statistics_day 表不需要顺序验证，只执行交叉验证 + cross_result = self.validate_cross( + data_sources[source1_name], + data_sources[source2_name], + source1_name, + source2_name, + key_fields, + compare_fields + ) + self.validation_results['交叉验证'].append(cross_result) + + if cross_result['only_in_source1'] or \ + cross_result['only_in_source2'] or \ + cross_result['field_mismatches']: + all_passed = False + + return all_passed + + def _extract_ai_statistics_from_json(self, json_data: List[Dict]) -> List[Dict]: + """从JSON数据中提取ai_statistics格式的数据 + + Args: + json_data: JSON数据 + + Returns: + ai_statistics格式的数据列表 + """ + records = [] + + for account_data in json_data: + account_id = account_data.get('account_id', '') + if not account_id: + continue + + analytics = account_data.get('analytics', {}) + apis = analytics.get('apis', []) + + if apis and len(apis) > 0: + api_data = apis[0].get('data', {}) + if api_data.get('errno') == 0: + total_info = api_data.get('data', {}).get('total_info', {}) + + record = { + 'author_name': account_id, + 'channel': 1, + 'submission_count': int(total_info.get('publish_count', 0) or 0), + 'read_count': int(total_info.get('view_count', 0) or 0), + 'comment_count': int(total_info.get('comment_count', 0) or 0), + 'comment_rate': float(total_info.get('comment_rate', 0) or 0) / 100, + 'like_count': int(total_info.get('likes_count', 0) or 0), + 'like_rate': float(total_info.get('likes_rate', 0) or 0) / 100, + 'favorite_count': int(total_info.get('collect_count', 0) or 0), + 'favorite_rate': float(total_info.get('collect_rate', 0) or 0) / 100, + 'share_count': int(total_info.get('share_count', 0) or 0), + 'share_rate': float(total_info.get('share_rate', 0) or 0) / 100, + 'slide_ratio': float(total_info.get('pic_slide_rate', 0) or 0) / 100, + 'baidu_search_volume': int(total_info.get('disp_pv', 0) or 0) + } + records.append(record) + + return records + + def generate_report(self, output_file: Optional[str] = None) -> None: + """生成验证报告 + + Args: + output_file: 输出文件路径 + """ + if not output_file: + timestamp = datetime.now().strftime('%Y%m%d_%H%M%S') + output_file = os.path.join(self.script_dir, f'validation_report_{timestamp}.txt') + + try: + with open(output_file, 'w', encoding='utf-8') as f: + f.write(f"数据验证报告\n") + f.write(f"{'='*70}\n") + f.write(f"生成时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n") + f.write(f"目标日期: {self.date_str}\n\n") + + # 顺序验证结果 + f.write(f"\n顺序验证结果\n") + f.write(f"{'-'*70}\n") + for result in self.validation_results['顺序验证']: + f.write(f"{result['source1']} vs {result['source2']}\n") + f.write(f" 顺序匹配: {'是' if result['order_match'] else '否'}\n") + f.write(f" {result['source1']} 记录数: {result['source1_count']}\n") + f.write(f" {result['source2']} 记录数: {result['source2_count']}\n") + if result['mismatches']: + f.write(f" 不匹配数: {len(result['mismatches'])}\n") + f.write(f"\n") + + # 交叉验证结果 + f.write(f"\n交叉验证结果\n") + f.write(f"{'-'*70}\n") + for result in self.validation_results['交叉验证']: + f.write(f"{result['source1']} vs {result['source2']}\n") + f.write(f" 共同记录: {result['common_count']}\n") + f.write(f" 仅在{result['source1']}: {len(result['only_in_source1'])}\n") + f.write(f" 仅在{result['source2']}: {len(result['only_in_source2'])}\n") + f.write(f" 字段不匹配: {len(result['field_mismatches'])}\n") + f.write(f"\n") + + print(f"\n[OK] 验证报告已生成: {output_file}") + + except Exception as e: + print(f"[X] 生成报告失败: {e}") + + +def main(): + """主函数""" + parser = argparse.ArgumentParser( + description='数据比对验证脚本', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +示例用法: + # 验证JSON和CSV + python data_validation.py --source json csv --date 2025-12-29 + + # 验证CSV和数据库 + python data_validation.py --source csv database --date 2025-12-29 + + # 完整验证（三个数据源） + python data_validation.py --source json csv database --date 2025-12-29 + + # 验证特定表 + python data_validation.py --source csv database --table ai_statistics_day --date 2025-12-29 + """ + ) + + parser.add_argument( + '--source', + nargs='+', + choices=['json', 'csv', 'database'], + default=['json', 'csv', 'database'], + help='数据源列表（至少2个）' + ) + + parser.add_argument( + '--date', + type=str, + default=(datetime.now() - timedelta(days=1)).strftime('%Y-%m-%d'), + help='目标日期 (YYYY-MM-DD)，默认为昨天' + ) + + parser.add_argument( + '--table', + type=str, + choices=['ai_statistics', 'ai_statistics_day', 'ai_statistics_days'], + default='ai_statistics', + help='要验证的表名' + ) + + parser.add_argument( + '--report', + type=str, + help='输出报告文件路径' + ) + + args = parser.parse_args() + + # 检查数据源数量 + if len(args.source) < 2: + print("[X] 至少需要指定2个数据源进行比对") + return 1 + + # 创建验证器 + validator = DataValidator(date_str=args.date) + + # 执行验证 + try: + if args.table == 'ai_statistics': + passed = validator.validate_ai_statistics(args.source) + elif args.table == 'ai_statistics_day': + passed = validator.validate_ai_statistics_day(args.source) + else: + print(f"[!] 表 {args.table} 的验证功能暂未实现") + passed = False + + # 生成报告 + validator.generate_report(args.report) + + # 输出总结 + print(f"\n{'='*70}") + if passed: + print(f"[✓] 验证通过：所有数据源数据一致") + else: + print(f"[X] 验证失败：发现数据差异") + print(f"{'='*70}") + + return 0 if passed else 1 + + except Exception as e: + print(f"\n[X] 验证过程出错: {e}") + import traceback + traceback.print_exc() + return 1 + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/data_validation_with_sms.py b/data_validation_with_sms.py new file mode 100644 index 0000000..3bf6455 --- /dev/null +++ b/data_validation_with_sms.py @@ -0,0 +1,441 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +数据验证与短信告警集成脚本 + +功能： +1. 执行数据验证（JSON/CSV/数据库） +2. 如果验证失败，发送阿里云短信告警 +3. 支持定时任务调度（每天9点执行） + +使用方法： + # 手动执行一次验证 + python data_validation_with_sms.py + + # 指定日期验证 + python data_validation_with_sms.py --date 2025-12-29 + + # 配置定时任务（Windows任务计划程序） + python data_validation_with_sms.py --setup-schedule +""" + +import sys +import os +import json +from datetime import datetime, timedelta +from typing import Dict, List, Optional + +# 添加项目根目录到路径 +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) + +# 导入数据验证模块 +from data_validation import DataValidator + +# 阿里云短信SDK导入 +try: + from alibabacloud_dysmsapi20170525.client import Client as Dysmsapi20170525Client + from alibabacloud_credentials.client import Client as CredentialClient + from alibabacloud_credentials.models import Config as CredentialConfig + from alibabacloud_tea_openapi import models as open_api_models + from alibabacloud_dysmsapi20170525 import models as dysmsapi_20170525_models + from alibabacloud_tea_util import models as util_models + SMS_AVAILABLE = True +except ImportError: + print("[!] 阿里云短信SDK未安装，短信功能将不可用") + print(" 安装命令: pip install alibabacloud_dysmsapi20170525") + SMS_AVAILABLE = False + + +class SMSAlertConfig: + """短信告警配置""" + + def __init__(self): + """从配置文件或环境变量加载配置""" + # 尝试从配置文件加载 + config_file = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'sms_config.json') + config_data = {} + + if os.path.exists(config_file): + try: + with open(config_file, 'r', encoding='utf-8') as f: + config_data = json.load(f) + except Exception as e: + print(f"[!] 读取配置文件失败: {e}") + + # 阿里云访问凭据（优先使用环境变量） + self.ACCESS_KEY_ID = os.environ.get( + 'ALIBABA_CLOUD_ACCESS_KEY_ID', + config_data.get('access_key_id', 'LTAI5tSMvnCJdqkZtCVWgh8R') + ) + self.ACCESS_KEY_SECRET = os.environ.get( + 'ALIBABA_CLOUD_ACCESS_KEY_SECRET', + config_data.get('access_key_secret', 'nyFzXyIi47peVLK4wR2qqbPezmU79W') + ) + + # 短信签名和模板 + self.SIGN_NAME = config_data.get('sign_name', '北京乐航时代科技') + self.TEMPLATE_CODE = config_data.get('template_code', 'SMS_486210104') + + # 接收短信的手机号（多个号码用逗号分隔） + self.PHONE_NUMBERS = config_data.get('phone_numbers', '13621242430') + + # 短信endpoint + self.ENDPOINT = config_data.get('endpoint', 'dysmsapi.aliyuncs.com') + + @staticmethod + def get_instance(): + """获取配置实例（单例模式）""" + if not hasattr(SMSAlertConfig, '_instance'): + SMSAlertConfig._instance = SMSAlertConfig() + return SMSAlertConfig._instance + + +class DataValidationWithSMS: + """数据验证与短信告警集成器""" + + def __init__(self, date_str: Optional[str] = None): + """初始化 + + Args: + date_str: 目标日期 (YYYY-MM-DD)，默认为昨天 + """ + self.validator = DataValidator(date_str) + self.sms_client = None + self.sms_config = SMSAlertConfig.get_instance() + + if SMS_AVAILABLE: + self.sms_client = self._create_sms_client() + + def _create_sms_client(self) -> Optional[Dysmsapi20170525Client]: + """创建阿里云短信客户端 + + Returns: + 短信客户端实例 + """ + try: + credential_config = CredentialConfig( + type='access_key', + access_key_id=self.sms_config.ACCESS_KEY_ID, + access_key_secret=self.sms_config.ACCESS_KEY_SECRET + ) + credential = CredentialClient(credential_config) + config = open_api_models.Config( + credential=credential, + endpoint=self.sms_config.ENDPOINT + ) + return Dysmsapi20170525Client(config) + except Exception as e: + print(f"[X] 创建短信客户端失败: {e}") + return None + + def send_sms_alert(self, error_code: str, error_details: str) -> bool: + """发送短信告警 + + Args: + error_code: 错误代码（如 "2222"） + error_details: 错误详情 + + Returns: + 是否发送成功 + """ + if not self.sms_client: + print(f"[X] 短信客户端未初始化，无法发送告警") + return False + + try: + # 构建短信请求 + send_sms_request = dysmsapi_20170525_models.SendSmsRequest( + phone_numbers=self.sms_config.PHONE_NUMBERS, + sign_name=self.sms_config.SIGN_NAME, + template_code=self.sms_config.TEMPLATE_CODE, + template_param=json.dumps({"code": error_code}) + ) + + runtime = util_models.RuntimeOptions() + + print(f"\n[短信] 正在发送告警短信...") + print(f" 接收号码: {self.sms_config.PHONE_NUMBERS}") + print(f" 错误代码: {error_code}") + print(f" 错误详情: {error_details[:100]}...") + + # 发送短信 + resp = self.sms_client.send_sms_with_options(send_sms_request, runtime) + + # 检查响应 + result = resp.to_map() + if result.get('body', {}).get('Code') == 'OK': + print(f"[✓] 短信发送成功") + print(f" 请求ID: {result.get('body', {}).get('RequestId')}") + print(f" 消息ID: {result.get('body', {}).get('BizId')}") + return True + else: + print(f"[X] 短信发送失败") + print(f" 错误码: {result.get('body', {}).get('Code')}") + print(f" 错误信息: {result.get('body', {}).get('Message')}") + return False + + except Exception as e: + print(f"[X] 发送短信异常: {e}") + if hasattr(e, 'data') and e.data: + print(f" 诊断地址: {e.data.get('Recommend')}") + return False + + def run_validation(self, sources: List[str] = None, table: str = 'ai_statistics') -> bool: + """执行数据验证 + + Args: + sources: 数据源列表，默认 ['json', 'csv', 'database'] + table: 要验证的表名 + + Returns: + 验证是否通过 + """ + if sources is None: + sources = ['json', 'csv', 'database'] + + print(f"\n{'='*70}") + print(f"数据验证与短信告警") + print(f"{'='*70}") + print(f"验证日期: {self.validator.date_str}") + print(f"验证表: {table}") + print(f"数据源: {', '.join(sources)}") + print(f"{'='*70}") + + try: + # 执行验证 + if table == 'ai_statistics': + passed = self.validator.validate_ai_statistics(sources) + elif table == 'ai_statistics_day': + passed = self.validator.validate_ai_statistics_day(sources) + elif table == 'ai_statistics_days': + # TODO: 实现 ai_statistics_days 验证 + print(f"[!] 表 {table} 的验证功能暂未实现") + passed = False + else: + print(f"[X] 未知的表名: {table}") + passed = False + + return passed + + except Exception as e: + print(f"\n[X] 验证过程出错: {e}") + import traceback + traceback.print_exc() + return False + + def generate_error_summary(self) -> str: + """生成错误摘要信息 + + Returns: + 错误摘要字符串 + """ + results = self.validator.validation_results + + summary_lines = [] + summary_lines.append(f"日期: {self.validator.date_str}") + + # 顺序验证错误 + order_errors = [r for r in results['顺序验证'] if not r['order_match']] + if order_errors: + summary_lines.append(f"顺序不一致: {len(order_errors)}个") + + # 交叉验证错误 + cross_errors = [] + for r in results['交叉验证']: + if r['only_in_source1'] or r['only_in_source2'] or r['field_mismatches']: + cross_errors.append(r) + + if cross_errors: + summary_lines.append(f"数据不一致: {len(cross_errors)}个") + + # 统计详情 + total_missing = sum(len(r['only_in_source1']) for r in cross_errors) + total_extra = sum(len(r['only_in_source2']) for r in cross_errors) + total_diff = sum(len(r['field_mismatches']) for r in cross_errors) + + if total_missing: + summary_lines.append(f" 缺失记录: {total_missing}条") + if total_extra: + summary_lines.append(f" 多余记录: {total_extra}条") + if total_diff: + summary_lines.append(f" 字段差异: {total_diff}条") + + return '; '.join(summary_lines) + + def run_with_alert(self, sources: List[str] = None, table: str = 'ai_statistics') -> int: + """执行验证并在失败时发送告警 + + Args: + sources: 数据源列表 + table: 要验证的表名 + + Returns: + 退出码（0=成功，1=失败） + """ + # 执行验证 + passed = self.run_validation(sources, table) + + # 创建验证报告目录 + script_dir = os.path.dirname(os.path.abspath(__file__)) + validation_reports_dir = os.path.join(script_dir, 'validation_reports') + if not os.path.exists(validation_reports_dir): + os.makedirs(validation_reports_dir) + + # 生成报告 + timestamp = datetime.now().strftime('%Y%m%d_%H%M%S') + report_file = os.path.join( + validation_reports_dir, + f'validation_report_{timestamp}.txt' + ) + self.validator.generate_report(report_file) + + # 判断是否需要发送告警 + if not passed: + print(f"\n{'='*70}") + print(f"[!] 验证失败，准备发送短信告警") + print(f"{'='*70}") + + # 生成错误摘要 + error_summary = self.generate_error_summary() + + # 发送短信（错误代码固定为 "2222"） + sms_sent = self.send_sms_alert("2222", error_summary) + + if sms_sent: + print(f"\n[✓] 告警短信已发送") + else: + print(f"\n[X] 告警短信发送失败") + + print(f"\n详细报告: {report_file}") + return 1 + else: + print(f"\n{'='*70}") + print(f"[✓] 验证通过，无需发送告警") + print(f"{'='*70}") + return 0 + + +def setup_windows_task_scheduler(): + """配置Windows任务计划程序（每天9点执行）""" + print(f"\n{'='*70}") + print(f"配置Windows任务计划程序") + print(f"{'='*70}") + + script_path = os.path.abspath(__file__) + python_path = sys.executable + + # 生成任务计划XML配置 + task_name = "DataValidationWithSMS" + + print(f"\n请手动创建Windows任务计划，或使用以下PowerShell命令：\n") + + # PowerShell命令 + ps_command = f""" +# 创建任务计划 +$action = New-ScheduledTaskAction -Execute '{python_path}' -Argument '{script_path}' +$trigger = New-ScheduledTaskTrigger -Daily -At 9:00AM +$settings = New-ScheduledTaskSettingsSet -AllowStartIfOnBatteries -DontStopIfGoingOnBatteries +$principal = New-ScheduledTaskPrincipal -UserId "$env:USERNAME" -RunLevel Highest + +Register-ScheduledTask -TaskName "{task_name}" -Action $action -Trigger $trigger -Settings $settings -Principal $principal -Description "每天9点执行数据验证并发送短信告警" + +Write-Host "任务计划已创建: {task_name}" +""" + + print(ps_command) + + print(f"\n或者手动配置:") + print(f"1. 打开 '任务计划程序' (taskschd.msc)") + print(f"2. 创建基本任务") + print(f"3. 名称: {task_name}") + print(f"4. 触发器: 每天 上午9:00") + print(f"5. 操作: 启动程序") + print(f"6. 程序: {python_path}") + print(f"7. 参数: {script_path}") + print(f"8. 完成") + + print(f"\n{'='*70}") + + +def main(): + """主函数""" + import argparse + + parser = argparse.ArgumentParser( + description='数据验证与短信告警集成脚本', + formatter_class=argparse.RawDescriptionHelpFormatter + ) + + parser.add_argument( + '--date', + type=str, + help='目标日期 (YYYY-MM-DD)，默认为昨天' + ) + + parser.add_argument( + '--source', + nargs='+', + choices=['json', 'csv', 'database'], + default=['json', 'csv', 'database'], + help='数据源列表' + ) + + parser.add_argument( + '--table', + type=str, + choices=['ai_statistics', 'ai_statistics_day', 'ai_statistics_days'], + default='ai_statistics', + help='要验证的表名' + ) + + parser.add_argument( + '--setup-schedule', + action='store_true', + help='配置定时任务（每天9点执行）' + ) + + parser.add_argument( + '--test-sms', + action='store_true', + help='测试短信发送功能' + ) + + parser.add_argument( + '--no-sms', + action='store_true', + help='禁用短信发送（仅验证数据）' + ) + + args = parser.parse_args() + + # 配置定时任务 + if args.setup_schedule: + setup_windows_task_scheduler() + return 0 + + # 测试短信 + if args.test_sms: + print(f"\n{'='*70}") + print(f"测试短信发送功能") + print(f"{'='*70}") + + validator = DataValidationWithSMS() + success = validator.send_sms_alert( + "2222", + "这是一条测试短信，数据验证系统运行正常" + ) + return 0 if success else 1 + + # 执行验证 + try: + validator = DataValidationWithSMS(date_str=args.date) + return validator.run_with_alert(args.source, args.table) + except Exception as e: + print(f"\n[X] 程序执行失败: {e}") + import traceback + traceback.print_exc() + return 1 + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/db/ai_statistics_days.sql b/db/ai_statistics_days.sql index a2c22b6..55819f5 100644 --- a/db/ai_statistics_days.sql +++ b/db/ai_statistics_days.sql @@ -28,70 +28,19 @@ CREATE TABLE `ai_statistics_days` ( `channel` tinyint(1) NOT NULL DEFAULT 1 COMMENT '1=baidu|2=toutiao|3=weixin', `stat_date` date NOT NULL COMMENT '统计日期（自然日）', `daily_published_count` int NULL DEFAULT 0 COMMENT '单日发文量', - `cumulative_published_count` int NULL DEFAULT 0 COMMENT '累计发文量（从起始日到stat_date的总和）', - `monthly_revenue` decimal(18, 2) NULL DEFAULT 0.00 COMMENT '当月收益（stat_date所在自然月的总收益）', - `weekly_revenue` decimal(18, 2) NULL DEFAULT 0.00 COMMENT '当周收益（stat_date所在自然周的总收益，周一至周日）', - `revenue_mom_growth_rate` decimal(10, 6) NULL DEFAULT 0.000000 COMMENT '收益月环比增长率（(本月收益 - 上月收益) / NULLIF(上月收益, 0)）', - `revenue_wow_growth_rate` decimal(10, 6) NULL DEFAULT 0.000000 COMMENT '收益周环比增长率（(本周收益 - 上周收益) / NULLIF(上周收益, 0)）', + `cumulative_published_count` int NULL DEFAULT 0 COMMENT '累计发文量（当月1号至stat_date的累计发文量）', + `day_revenue` decimal(18, 2) NULL DEFAULT 0.00 COMMENT '当日收益', `created_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间', `updated_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间', PRIMARY KEY (`id`) USING BTREE, - UNIQUE INDEX `uk_stat_date`(`stat_date` ASC) USING BTREE, - INDEX `idx_stat_date`(`stat_date` ASC) USING BTREE -) ENGINE = InnoDB AUTO_INCREMENT = 51 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = 'AI内容每日核心指标汇总表（含累计、收益及环比）' ROW_FORMAT = Dynamic; + UNIQUE INDEX `uk_author_stat_date`(`author_id` ASC, `channel` ASC, `stat_date` ASC) USING BTREE, + INDEX `idx_stat_date`(`stat_date` ASC) USING BTREE, + INDEX `idx_author_id`(`author_id` ASC) USING BTREE +) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = 'AI内容每日核心指标汇总表（日粒度数据）' ROW_FORMAT = Dynamic; -- ---------------------------- -- Records of ai_statistics_days -- ---------------------------- -INSERT INTO `ai_statistics_days` VALUES (1, 129, '梁金宇医生', 1, '2025-10-28', 27, 27, 198.44, 198.44, 0.000000, 0.000000, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (2, 127, '黄燕飞医生', 1, '2025-10-29', 6, 33, 382.29, 382.29, 0.000000, 0.000000, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (3, 151, '皮肤科赵鹏', 1, '2025-10-30', 30, 63, 1317.62, 1317.62, 0.000000, 0.000000, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (4, 132, '石爱真医生', 1, '2025-10-31', 22, 85, 1435.84, 1435.84, 0.000000, 0.000000, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (5, 211, '中医王倚东', 1, '2025-11-01', 27, 112, 116.15, 1551.99, -0.919107, 0.000000, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (6, 176, '武娜中医', 1, '2025-11-02', 11, 123, 1025.18, 2461.02, -0.286007, 0.000000, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (7, 193, '血管外科钟若雷', 1, '2025-11-03', 6, 129, 1462.23, 437.05, 0.018379, -0.822411, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (8, 104, '男科医生刘德风', 1, '2025-11-04', 5, 134, 2050.55, 1025.37, 0.428119, -0.583356, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (9, 175, '静脉曲张的杀手医生', 1, '2025-11-05', 12, 146, 3004.99, 1979.81, 1.092845, -0.195533, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (10, 202, '整形外科侯丽平', 1, '2025-11-06', 26, 172, 3260.49, 2235.31, 1.270789, -0.091714, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (11, 117, '唐小明医生', 1, '2025-11-07', 13, 185, 4064.21, 3039.03, 1.830545, 0.234866, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (12, 214, '传海2018', 1, '2025-11-08', 12, 197, 4961.73, 3936.55, 2.455629, 0.599560, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (13, 170, '任志宏中医', 1, '2025-11-09', 18, 215, 5160.70, 4135.52, 2.594203, 0.680409, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (14, 179, '风湿免疫专家李小峰', 1, '2025-11-10', 18, 233, 5794.59, 633.89, 3.035679, -0.846721, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (15, 202, '整形外科侯丽平', 1, '2025-11-11', 14, 247, 6673.98, 1513.28, 3.648136, -0.634077, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (16, 203, '中医针灸侯医生', 1, '2025-11-12', 19, 266, 7412.32, 2251.62, 4.162358, -0.455541, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (17, 217, '中医杨志杰', 1, '2025-11-13', 24, 290, 7641.13, 2480.43, 4.321714, -0.400213, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (18, 115, '冯玉燕医生', 1, '2025-11-14', 25, 315, 8384.03, 3223.33, 4.839112, -0.220574, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (19, 184, '耳鼻喉科贾闯医生', 1, '2025-11-15', 22, 337, 9067.99, 3907.29, 5.315460, -0.055188, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (20, 131, '骆小辉副主任医师', 1, '2025-11-16', 14, 351, 9538.20, 4377.50, 5.642941, 0.058513, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (21, 130, '妇产科许春艳', 1, '2025-11-17', 9, 360, 9827.47, 289.27, 5.844405, -0.933919, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (22, 211, '中医王倚东', 1, '2025-11-18', 19, 379, 10482.77, 944.57, 6.300793, -0.784222, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (23, 201, '面部提升梁永鑫', 1, '2025-11-19', 22, 401, 11126.90, 1588.70, 6.749401, -0.637076, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (24, 181, '针灸科高小勇医生', 1, '2025-11-20', 8, 409, 11849.59, 2311.39, 7.252723, -0.471984, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (25, 122, '高丽娜中医', 1, '2025-11-21', 6, 415, 12167.82, 2629.62, 7.474356, -0.399287, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (26, 105, '抗衰孟大夫', 1, '2025-11-22', 29, 444, 12921.45, 3383.25, 7.999227, -0.227127, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (27, 111, '赖婷医生', 1, '2025-11-23', 13, 457, 13852.86, 4314.66, 8.647913, -0.014355, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (28, 214, '传海2018', 1, '2025-11-24', 23, 480, 14590.97, 738.11, 9.161975, -0.828930, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (29, 226, '中医李伟杰', 1, '2025-11-25', 27, 507, 14899.04, 1046.18, 9.376532, -0.757529, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (30, 180, '尹海琴医生', 1, '2025-11-26', 26, 533, 15860.20, 2007.34, 10.045938, -0.534763, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (31, 136, '普外科马春雷', 1, '2025-11-27', 15, 548, 16177.26, 2324.40, 10.266757, -0.461279, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (32, 241, '测试作者_更新', 1, '2025-11-28', 8, 556, 16606.60, 2753.74, 10.565773, -0.361771, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (33, 153, '曹凤娇中医', 1, '2025-11-29', 24, 580, 16946.60, 3093.74, 10.802569, -0.282970, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (34, 175, '静脉曲张的杀手医生', 1, '2025-11-30', 20, 600, 17569.87, 3717.01, 11.236649, -0.138516, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (35, 173, '赵剑锋医生', 1, '2025-12-01', 15, 615, 687.78, 687.78, -0.960855, -0.814964, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (36, 196, '血管外科阿力木', 1, '2025-12-02', 22, 637, 1298.68, 1298.68, -0.926085, -0.650612, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (37, 248, '百胜号', 2, '2025-12-03', 7, 644, 1620.63, 1620.63, -0.907761, -0.563996, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (38, 185, '郭俊恒中医', 1, '2025-12-04', 18, 662, 2172.80, 2172.80, -0.876334, -0.415444, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (39, 104, '男科医生刘德风', 1, '2025-12-05', 18, 680, 2813.87, 2813.87, -0.839847, -0.242975, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (40, 214, '传海2018', 1, '2025-12-06', 15, 695, 3393.18, 3393.18, -0.806875, -0.087121, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (41, 245, '文龙号', 2, '2025-12-07', 20, 715, 4382.30, 4382.30, -0.750579, 0.178985, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (42, 198, '拇外翻医生李昕宇', 1, '2025-12-08', 5, 720, 4487.00, 104.70, -0.744620, -0.976108, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (43, 175, '静脉曲张的杀手医生', 1, '2025-12-09', 16, 736, 4628.11, 245.81, -0.736588, -0.943908, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (44, 110, '白凌文医生', 1, '2025-12-10', 10, 746, 5393.95, 1011.65, -0.693000, -0.769151, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (45, 141, '耳鼻喉科杨书勋医生', 1, '2025-12-11', 7, 753, 5897.48, 1515.18, -0.664341, -0.654250, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (46, 226, '中医李伟杰', 1, '2025-12-12', 11, 764, 6830.48, 2448.18, -0.611239, -0.441348, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (47, 183, '杜晋芳中医', 1, '2025-12-13', 22, 786, 7500.72, 3118.42, -0.573092, -0.288406, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (48, 192, '整形医生路会', 1, '2025-12-14', 26, 812, 7738.47, 3356.17, -0.559560, -0.234153, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (49, 146, 'Dr蓝剑雄', 1, '2025-12-15', 12, 824, 8072.01, 333.54, -0.540577, -0.900619, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); -INSERT INTO `ai_statistics_days` VALUES (50, 241, '测试作者_更新', 1, '2025-12-16', 14, 838, 8548.49, 810.02, -0.513457, -0.758648, '2025-12-16 10:53:58', '2025-12-16 11:28:19'); +-- 数据已清空，由导入脚本从CSV文件导入 SET FOREIGN_KEY_CHECKS = 1; diff --git a/db/ai_statistics_monthly.sql b/db/ai_statistics_monthly.sql new file mode 100644 index 0000000..5431a67 --- /dev/null +++ b/db/ai_statistics_monthly.sql @@ -0,0 +1,45 @@ +/* + Navicat Premium Dump SQL + + Source Server : mixue + Source Server Type : MySQL + Source Server Version : 90001 (9.0.1) + Source Host : localhost:3306 + Source Schema : ai_article + + Target Server Type : MySQL + Target Server Version : 90001 (9.0.1) + File Encoding : 65001 + + Date: 25/12/2025 14:30:00 +*/ + +SET NAMES utf8mb4; +SET FOREIGN_KEY_CHECKS = 0; + +-- ---------------------------- +-- Table structure for ai_statistics_monthly +-- ---------------------------- +DROP TABLE IF EXISTS `ai_statistics_monthly`; +CREATE TABLE `ai_statistics_monthly` ( + `id` bigint NOT NULL AUTO_INCREMENT COMMENT '自增主键', + `author_id` int NOT NULL DEFAULT 0 COMMENT '作者ID', + `author_name` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL COMMENT '作者名称', + `channel` tinyint(1) NOT NULL DEFAULT 1 COMMENT '1=baidu|2=toutiao|3=weixin', + `stat_monthly` varchar(7) NOT NULL COMMENT '统计月份（格式：YYYY-MM，如2025-12表示2025年12月）', + `monthly_revenue` decimal(18, 2) NULL DEFAULT 0.00 COMMENT '当月收益（stat_monthly所在自然月的总收益）', + `revenue_mom_growth_rate` decimal(10, 6) NULL DEFAULT 0.000000 COMMENT '收益月环比增长率（(本月收益 - 上月收益) / NULLIF(上月收益, 0)）', + `created_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间', + `updated_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间', + PRIMARY KEY (`id`) USING BTREE, + UNIQUE INDEX `uk_author_stat_date`(`author_id` ASC, `stat_monthly` ASC) USING BTREE, + INDEX `idx_stat_date`(`stat_monthly` ASC) USING BTREE, + INDEX `idx_author_id`(`author_id` ASC) USING BTREE +) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = 'AI内容每月核心指标汇总表（月粒度数据）' ROW_FORMAT = Dynamic; + +-- ---------------------------- +-- Records of ai_statistics_monthly +-- ---------------------------- +-- 数据由导入脚本从CSV文件自动导入 + +SET FOREIGN_KEY_CHECKS = 1; diff --git a/db/ai_statistics_weekly.sql b/db/ai_statistics_weekly.sql new file mode 100644 index 0000000..12d013a --- /dev/null +++ b/db/ai_statistics_weekly.sql @@ -0,0 +1,45 @@ +/* + Navicat Premium Dump SQL + + Source Server : mixue + Source Server Type : MySQL + Source Server Version : 90001 (9.0.1) + Source Host : localhost:3306 + Source Schema : ai_article + + Target Server Type : MySQL + Target Server Version : 90001 (9.0.1) + File Encoding : 65001 + + Date: 25/12/2025 14:30:00 +*/ + +SET NAMES utf8mb4; +SET FOREIGN_KEY_CHECKS = 0; + +-- ---------------------------- +-- Table structure for ai_statistics_weekly +-- ---------------------------- +DROP TABLE IF EXISTS `ai_statistics_weekly`; +CREATE TABLE `ai_statistics_weekly` ( + `id` bigint NOT NULL AUTO_INCREMENT COMMENT '自增主键', + `author_id` int NOT NULL DEFAULT 0 COMMENT '作者ID', + `author_name` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL COMMENT '作者名称', + `channel` tinyint(1) NOT NULL DEFAULT 1 COMMENT '1=baidu|2=toutiao|3=weixin', + `stat_weekly` varchar(2) NOT NULL COMMENT '统计周次（格式：WW，如51表示第51周）', + `weekly_revenue` decimal(18, 2) NULL DEFAULT 0.00 COMMENT '当周收益（stat_weekly所在自然周的总收益，周一至周日）', + `revenue_wow_growth_rate` decimal(10, 6) NULL DEFAULT 0.000000 COMMENT '收益周环比增长率（(本周收益 - 上周收益) / NULLIF(上周收益, 0)）', + `created_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间', + `updated_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间', + PRIMARY KEY (`id`) USING BTREE, + UNIQUE INDEX `uk_author_stat_date`(`author_id` ASC, `stat_weekly` ASC) USING BTREE, + INDEX `idx_stat_date`(`stat_weekly` ASC) USING BTREE, + INDEX `idx_author_id`(`author_id` ASC) USING BTREE +) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci COMMENT = 'AI内容每周核心指标汇总表（周粒度数据）' ROW_FORMAT = Dynamic; + +-- ---------------------------- +-- Records of ai_statistics_weekly +-- ---------------------------- +-- 数据由导入脚本从CSV文件自动导入 + +SET FOREIGN_KEY_CHECKS = 1; diff --git a/deploy_daemon.sh b/deploy_daemon.sh new file mode 100644 index 0000000..42899b6 --- /dev/null +++ b/deploy_daemon.sh @@ -0,0 +1,105 @@ +#!/bin/bash +# 数据同步守护进程部署脚本（Linux systemd） + +echo "============================================================" +echo "百家号数据同步守护进程 - 部署脚本" +echo "含数据验证与短信告警功能" +echo "============================================================" +echo "" + +# 检查是否为root用户 +if [ "$EUID" -ne 0 ]; then + echo "[错误] 请使用root用户运行此脚本" + echo " sudo bash deploy_daemon.sh" + exit 1 +fi + +# 项目目录（根据实际情况修改） +PROJECT_DIR="/root/xhh_baijiahao" +SERVICE_NAME="bjh_daemon" + +echo "[1/6] 检查项目目录..." +if [ ! -d "$PROJECT_DIR" ]; then + echo "[错误] 项目目录不存在: $PROJECT_DIR" + exit 1 +fi +echo " 项目目录: $PROJECT_DIR" +echo "" + +echo "[2/6] 检查Python依赖..." +cd "$PROJECT_DIR" +python3 -c "import schedule" 2>/dev/null +if [ $? -ne 0 ]; then + echo " 安装 schedule 模块..." + pip3 install schedule +fi + +python3 -c "from data_validation_with_sms import DataValidationWithSMS" 2>/dev/null +if [ $? -ne 0 ]; then + echo "[警告] 数据验证模块检查失败，请确保以下文件存在：" + echo " - data_validation.py" + echo " - data_validation_with_sms.py" + echo " - sms_config.json" +fi + +python3 -c "from alibabacloud_dysmsapi20170525.client import Client" 2>/dev/null +if [ $? -ne 0 ]; then + echo " 安装阿里云短信SDK..." + pip3 install alibabacloud_dysmsapi20170525 alibabacloud_credentials alibabacloud_tea_openapi alibabacloud_tea_util +fi +echo "" + +echo "[3/6] 配置systemd服务..." +# 复制服务文件 +cp "$PROJECT_DIR/bjh_daemon.service" /etc/systemd/system/ +chmod 644 /etc/systemd/system/bjh_daemon.service + +# 重新加载systemd配置 +systemctl daemon-reload +echo " 服务文件已安装: /etc/systemd/system/bjh_daemon.service" +echo "" + +echo "[4/6] 配置短信告警..." +if [ ! -f "$PROJECT_DIR/sms_config.json" ]; then + echo "[警告] 未找到 sms_config.json，短信功能可能不可用" + echo " 请创建配置文件: $PROJECT_DIR/sms_config.json" +else + echo " 短信配置文件已存在: sms_config.json" +fi +echo "" + +echo "[5/6] 启用并启动服务..." +systemctl enable bjh_daemon.service +systemctl start bjh_daemon.service + +# 等待2秒 +sleep 2 +echo "" + +echo "[6/6] 检查服务状态..." +systemctl status bjh_daemon.service --no-pager +echo "" + +echo "============================================================" +echo "部署完成！" +echo "============================================================" +echo "" +echo "常用命令：" +echo " 查看状态: sudo systemctl status bjh_daemon" +echo " 查看日志: sudo journalctl -u bjh_daemon -f" +echo " 停止服务: sudo systemctl stop bjh_daemon" +echo " 重启服务: sudo systemctl restart bjh_daemon" +echo " 禁用服务: sudo systemctl disable bjh_daemon" +echo "" +echo "配置文件：" +echo " systemd配置: /etc/systemd/system/bjh_daemon.service" +echo " 短信配置: $PROJECT_DIR/sms_config.json" +echo " 程序日志: $PROJECT_DIR/logs/data_sync_daemon.log" +echo " 验证报告: $PROJECT_DIR/validation_reports/" +echo "" +echo "功能说明：" +echo " 1. 每隔1小时自动执行数据同步（工作时间8:00-24:00）" +echo " 2. 数据同步完成后自动验证数据完整性" +echo " 3. 验证失败时自动发送短信告警（错误代码2222）" +echo " 4. 非工作时间自动休眠" +echo "" diff --git a/export_to_csv.py b/export_to_csv.py index 41b7bc5..e7396ea 100644 --- a/export_to_csv.py +++ b/export_to_csv.py @@ -12,6 +12,7 @@ import sys import os import json import csv +import shutil from datetime import datetime from typing import Dict, List, Optional from decimal import Decimal @@ -67,6 +68,10 @@ class DataExporter: self.output_ai_statistics_day = os.path.join(self.script_dir, "ai_statistics_day.csv") self.output_ai_statistics_days = os.path.join(self.script_dir, "ai_statistics_days.csv") + # 备份文件夹路径 + self.backup_dir = os.path.join(self.script_dir, "csv_backups") + self._ensure_backup_dir() + # 数据库模式 self.use_database = use_database self.db_manager = None @@ -90,6 +95,51 @@ class DataExporter: # 缓存author_id映射（author_name -> author_id） self.author_id_cache = {} + def _ensure_backup_dir(self): + """确保备份文件夹存在""" + try: + if not os.path.exists(self.backup_dir): + os.makedirs(self.backup_dir) + print(f"[OK] 创建备份文件夹: {self.backup_dir}") + except Exception as e: + print(f"[!] 创建备份文件夹失败: {e}") + + def _backup_csv_file(self, csv_file_path: str) -> bool: + """备份CSV文件 + + Args: + csv_file_path: CSV文件的完整路径 + + Returns: + bool: 备份是否成功 + """ + try: + if not os.path.exists(csv_file_path): + print(f"[!] 文件不存在，跳过备份: {csv_file_path}") + return False + + # 获取文件名 + file_name = os.path.basename(csv_file_path) + + # 生成时间戳（只保留日期） + timestamp = datetime.now().strftime('%Y%m%d') + + # 备份文件名：20251226_ai_statistics.csv + backup_file_name = f"{timestamp}_{file_name}" + backup_file_path = os.path.join(self.backup_dir, backup_file_name) + + # 复制文件 + shutil.copy2(csv_file_path, backup_file_path) + + print(f" [备份] {file_name} -> {backup_file_name}") + self.logger.info(f"备份CSV文件: {backup_file_path}") + + return True + except Exception as e: + print(f" [!] 备份失败: {e}") + self.logger.error(f"备份CSV文件失败: {e}") + return False + def get_author_id(self, author_name: str) -> int: """获取作者ID @@ -286,21 +336,25 @@ class DataExporter: print(f" [!] 从数据库计算当周发文量失败: {e}") return 0 - def calculate_weekly_revenue_from_db(self, author_id: int, stat_date: str) -> float: - """从ai_statistics_days表汇总计算当周收益（周一至周日） + def calculate_weekly_revenue_from_db(self, author_id: int, stat_date: str, today_revenue: float = 0.0) -> float: + """从ai_statistics_days表汇总计算当周收益（周一至当前日期） - 基于day_revenue字段进行汇总计算 + 计算逻辑： + 1. 从数据库查询本周一到stat_date前一天的day_revenue总和 + 2. 加上today_revenue（当日收益，从API获取） + 3. 得到本周累计收益 Args: author_id: 作者ID stat_date: 统计日期 (YYYY-MM-DD) + today_revenue: 当日收益（从API获取），默认0.0 Returns: 当周收益总额 """ if not self.db_manager or author_id == 0: print(f" [数据库] 未连接或author_id无效，无法计算当周收益") - return 0.0 + return today_revenue # 如果数据库不可用，返回当日收益 try: from datetime import datetime, timedelta @@ -311,14 +365,21 @@ class DataExporter: # 计算本周一的日期（weekday: 0=周一, 6=周日） weekday = target_date.weekday() monday = target_date - timedelta(days=weekday) - sunday = monday + timedelta(days=6) + + # 昨天的日期（stat_date的前一天） + yesterday = target_date - timedelta(days=1) monday_str = monday.strftime('%Y-%m-%d') - sunday_str = sunday.strftime('%Y-%m-%d') + yesterday_str = yesterday.strftime('%Y-%m-%d') - print(f" [调试] 目标日期: {stat_date}, 周一: {monday_str}, 周日: {sunday_str}") + print(f" [调试] 目标日期: {stat_date}, 本周一: {monday_str}, 昨天: {yesterday_str}") - # 查询数据库中本周的day_revenue总和 + # 如果stat_date就是周一，则没有历史数据，直接返回今日收益 + if target_date == monday: + print(f" [数据库] 目标日期是周一，当周收益 = 今日收益: ¥{today_revenue:.2f}") + return today_revenue + + # 查询数据库中本周一到昨天的day_revenue总和 sql = """ SELECT SUM(day_revenue) as weekly_total, COUNT(*) as day_count FROM ai_statistics_days @@ -330,25 +391,33 @@ class DataExporter: result = self.db_manager.execute_query( sql, - (author_id, monday_str, sunday_str), + (author_id, monday_str, yesterday_str), fetch_one=True, dict_cursor=True ) - print(f" [调试] 查询结果: {result}") + print(f" [调试] 数据库查询结果: {result}") + + # 计算当周收益 = 本周历史收益 + 今日收益 + historical_revenue = 0.0 + day_count = 0 if result and result.get('weekly_total') is not None: - weekly_total = float(result['weekly_total'] or 0) + historical_revenue = float(result['weekly_total'] or 0) day_count = int(result.get('day_count', 0) or 0) - print(f" [数据库] 当周收益 ({monday_str} 至 {sunday_str}): ¥{weekly_total:.2f} (基于{day_count}天的数据)") - return weekly_total - else: - print(f" [数据库] 未找到当周数据 ({monday_str} 至 {sunday_str})，返回0") - return 0.0 + + weekly_total = historical_revenue + today_revenue + + print(f" [数据库] 当周收益计算:") + print(f" 本周一至昨天 ({monday_str} ~ {yesterday_str}): ¥{historical_revenue:.2f} (基于{day_count}天)") + print(f" 今日收益 ({stat_date}): ¥{today_revenue:.2f}") + print(f" 当周总收益: ¥{weekly_total:.2f}") + + return weekly_total except Exception as e: print(f" [!] 从数据库计算当周收益失败: {e}") - return 0.0 + return today_revenue # 出错时返回当日收益 def calculate_last_week_revenue_from_db(self, author_id: int, stat_date: str) -> float: """从ai_statistics_days表汇总计算上周收益（上周一至上周日） @@ -407,6 +476,77 @@ class DataExporter: print(f" [!] 从数据库计算上周收益失败: {e}") return 0.0 + def calculate_monthly_revenue_from_db(self, author_id: int, stat_date: str, today_revenue: float = 0.0) -> float: + """从ai_statistics_days表汇总计算当月收益（当月1日至当前日期） + + 计算逻辑： + 1. 从数据库查询当月1日到stat_date前一天的day_revenue总和 + 2. 加上today_revenue（当日收益，从API获取） + 3. 得到当月累计收益 + + Args: + author_id: 作者ID + stat_date: 统计日期 (YYYY-MM-DD) + today_revenue: 当日收益（从API获取），默认0.0 + + Returns: + 当月收益总额 + """ + if not self.db_manager or author_id == 0: + print(f" [数据库] 未连接或author_id无效，无法计算当月收益") + return today_revenue # 如果数据库不可用，返回当日收益 + + try: + from datetime import datetime, timedelta + + # 解析日期 + target_date = datetime.strptime(stat_date, '%Y-%m-%d') + + # 当月第一天 + month_first = target_date.replace(day=1) + # stat_date的前一天（因为当日数据可能还未写入数据库） + yesterday = target_date - timedelta(days=1) + + month_first_str = month_first.strftime('%Y-%m-%d') + yesterday_str = yesterday.strftime('%Y-%m-%d') + + # 如果stat_date就是当月第一天，直接返回当日收益 + if target_date.day == 1: + print(f" [数据库] 当月第一天，当月收益 = 当日收益: ¥{today_revenue:.2f}") + return today_revenue + + # 查询当月1日到stat_date前一天的收益总和 + sql = """ + SELECT SUM(day_revenue) as monthly_total + FROM ai_statistics_days + WHERE author_id = %s + AND stat_date >= %s + AND stat_date <= %s + AND channel = 1 + """ + + result = self.db_manager.execute_query( + sql, + (author_id, month_first_str, yesterday_str), + fetch_one=True, + dict_cursor=True + ) + + if result and result.get('monthly_total') is not None: + db_total = float(result['monthly_total'] or 0) + # 加上当日收益 + monthly_total = db_total + today_revenue + print(f" [数据库] 当月收益 ({month_first_str} 至 {stat_date}): 数据库¥{db_total:.2f} + 当日¥{today_revenue:.2f} = ¥{monthly_total:.2f}") + return monthly_total + else: + # 没有历史数据，返回当日收益 + print(f" [数据库] 未找到当月历史数据 ({month_first_str} 至 {yesterday_str})，当月收益 = 当日收益: ¥{today_revenue:.2f}") + return today_revenue + + except Exception as e: + print(f" [!] 从数据库计算当月收益失败: {e}") + return today_revenue + def calculate_last_month_revenue_from_db(self, author_id: int, stat_date: str) -> float: """从ai_statistics_days表汇总计算上月收益 @@ -510,14 +650,20 @@ class DataExporter: metrics['submission_count'] = int(total_info.get('publish_count', 0) or 0) metrics['read_count'] = int(total_info.get('view_count', 0) or 0) metrics['comment_count'] = int(total_info.get('comment_count', 0) or 0) - metrics['comment_rate'] = float(total_info.get('comment_rate', 0) or 0) + # 所有rate字段API返回的都是百分制（如0.30表示0.30%），需要除以100转换为小数 + comment_rate_raw = float(total_info.get('comment_rate', 0) or 0) + metrics['comment_rate'] = comment_rate_raw / 100 if comment_rate_raw > 0 else 0.0 metrics['like_count'] = int(total_info.get('likes_count', 0) or 0) - metrics['like_rate'] = float(total_info.get('likes_rate', 0) or 0) + like_rate_raw = float(total_info.get('likes_rate', 0) or 0) + metrics['like_rate'] = like_rate_raw / 100 if like_rate_raw > 0 else 0.0 metrics['favorite_count'] = int(total_info.get('collect_count', 0) or 0) - metrics['favorite_rate'] = float(total_info.get('collect_rate', 0) or 0) + favorite_rate_raw = float(total_info.get('collect_rate', 0) or 0) + metrics['favorite_rate'] = favorite_rate_raw / 100 if favorite_rate_raw > 0 else 0.0 metrics['share_count'] = int(total_info.get('share_count', 0) or 0) - metrics['share_rate'] = float(total_info.get('share_rate', 0) or 0) - metrics['slide_ratio'] = float(total_info.get('pic_slide_rate', 0) or 0) + share_rate_raw = float(total_info.get('share_rate', 0) or 0) + metrics['share_rate'] = share_rate_raw / 100 if share_rate_raw > 0 else 0.0 + slide_ratio_raw = float(total_info.get('pic_slide_rate', 0) or 0) + metrics['slide_ratio'] = slide_ratio_raw / 100 if slide_ratio_raw > 0 else 0.0 metrics['baidu_search_volume'] = int(total_info.get('disp_pv', 0) or 0) # 修正：使用disp_pv except Exception as e: print(f" [!] 提取汇总指标失败: {e}") @@ -529,7 +675,7 @@ class DataExporter: 注意： - weekly_revenue: 不再从API获取，在export_ai_statistics_days中从数据库计算 - - monthly_revenue: 使用currentMonth（当前自然月收益） + - monthly_revenue: 不再从API获取，在export_ai_statistics_days中从数据库计算 - day_revenue: 从yesterday提取昨日收益（当日收益） - revenue_wow_growth_rate: 周环比，从数据库计算（本周 vs 上周） - revenue_mom_growth_rate: 月环比，从数据库计算（当月 vs 上月） @@ -564,10 +710,8 @@ class DataExporter: # 这里保持为0，由export_ai_statistics_days方法计算 print(f" 环比增长率: 将从数据库计算") - # 当前自然月收入（currentMonth） - current_month = income_data.get('currentMonth', {}) - if current_month: - metrics['monthly_revenue'] = float(current_month.get('income', 0) or 0) + # monthly_revenue 不再从API获取，在导出时从数据库的day_revenue汇总计算 + print(f" 当月收益: 将从数据库计算") except Exception as e: print(f" [!] 提取收入指标失败: {e}") @@ -650,6 +794,10 @@ class DataExporter: print(f"[OK] ai_statistics 表数据已导出到: {self.output_ai_statistics}") print(f" 共 {len(csv_rows)} 条记录") print(f"{'='*70}") + + # 备份CSV文件 + self._backup_csv_file(self.output_ai_statistics) + return True else: print("\n[!] 没有数据可导出") @@ -729,11 +877,12 @@ class DataExporter: 'total_like_count': int(latest_day_data.get('likes_count', 0) or 0), 'total_favorite_count': int(latest_day_data.get('collect_count', 0) or 0), 'total_share_count': int(latest_day_data.get('share_count', 0) or 0), - 'avg_comment_rate': f"{float(latest_day_data.get('comment_rate', 0) or 0):.4f}", - 'avg_like_rate': f"{float(latest_day_data.get('likes_rate', 0) or 0):.4f}", - 'avg_favorite_rate': f"{float(latest_day_data.get('collect_rate', 0) or 0):.4f}", - 'avg_share_rate': f"{float(latest_day_data.get('share_rate', 0) or 0):.4f}", - 'avg_slide_ratio': f"{float(latest_day_data.get('pic_slide_rate', 0) or 0):.4f}", + # 所有rate字段API返回的都是百分制，需要除以100转换为小数 + 'avg_comment_rate': f"{(float(latest_day_data.get('comment_rate', 0) or 0) / 100):.4f}", + 'avg_like_rate': f"{(float(latest_day_data.get('likes_rate', 0) or 0) / 100):.4f}", + 'avg_favorite_rate': f"{(float(latest_day_data.get('collect_rate', 0) or 0) / 100):.4f}", + 'avg_share_rate': f"{(float(latest_day_data.get('share_rate', 0) or 0) / 100):.4f}", + 'avg_slide_ratio': f"{(float(latest_day_data.get('pic_slide_rate', 0) or 0) / 100):.4f}", 'total_baidu_search_volume': int(latest_day_data.get('disp_pv', 0) or 0), } @@ -763,6 +912,10 @@ class DataExporter: print(f"[OK] ai_statistics_day 表数据已导出到: {self.output_ai_statistics_day}") print(f" 共 {len(csv_rows)} 条记录") print(f"{'='*70}") + + # 备份CSV文件 + self._backup_csv_file(self.output_ai_statistics_day) + return True else: print("\n[!] 没有数据可导出") @@ -779,7 +932,7 @@ class DataExporter: 注意： - daily_published_count: 优先从ai_articles表查询，否则使用API数据 - cumulative_published_count: 优先从ai_articles表查询（从起始日到stat_date的累计发文量） - - monthly_revenue: stat_date所在自然月的总收益（使用近30天收益作为近似值） + - monthly_revenue: 从ai_statistics_days表汇总计算（当月1日至stat_date的day_revenue总和） - weekly_revenue: 优先从ai_statistics_days表汇总计算，否则使用API数据 Args: @@ -851,38 +1004,49 @@ class DataExporter: daily_published = int(latest_day_data.get('publish_count', 0) or 0) print(f" [使用API] 文章数据: 单日={daily_published}, 累计={cumulative_count}") - # 计算当周收益：数据库中本周已有的收益 + 当日新抓取的收益 + # 计算当周收益：从数据库汇总本周一至周日的day_revenue总和 if use_db_weekly_revenue and author_id > 0: - # 从数据库查询本周已有的收益（不包括今天，因为今天的数据还没导入） - weekly_revenue_db = self.calculate_weekly_revenue_from_db(author_id, formatted_date) - # 当周收益 = 数据库中的历史收益 + 当日新抓取的收益 - day_revenue = income_metrics['day_revenue'] - weekly_revenue_total = weekly_revenue_db + day_revenue + # 从数据库查询本周的收益总和（传入当日收益） + weekly_revenue_total = self.calculate_weekly_revenue_from_db( + author_id, + formatted_date, + today_revenue=income_metrics['day_revenue'] # 传入当日收益 + ) income_metrics['weekly_revenue'] = weekly_revenue_total - print(f" [数据库] 本周已有收益: ¥{weekly_revenue_db:.2f}") - print(f" [API] 当日新增收益: ¥{day_revenue:.2f}") - print(f" [计算] 当周总收益: ¥{weekly_revenue_total:.2f}") + print(f" [数据库] 当周收益: ¥{weekly_revenue_total:.2f}") + + # 计算当月收益：从数据库汇总当月1日至stat_date的day_revenue总和 + monthly_revenue_total = self.calculate_monthly_revenue_from_db( + author_id, + formatted_date, + today_revenue=income_metrics['day_revenue'] # 传入当日收益 + ) + income_metrics['monthly_revenue'] = monthly_revenue_total # 计算周环比：本周 vs 上周 + # 公式：周环比 = (本周收益 - 上周收益) / 上周收益 last_week_revenue = self.calculate_last_week_revenue_from_db(author_id, formatted_date) - if last_week_revenue > 0: - income_metrics['revenue_wow_growth_rate'] = (weekly_revenue_total - last_week_revenue) / last_week_revenue - print(f" [计算] 周环比: {income_metrics['revenue_wow_growth_rate']:.2%} (本周¥{weekly_revenue_total:.2f} vs 上周¥{last_week_revenue:.2f})") - else: - print(f" [计算] 周环比: 无法计算（上周没有数据）") + # 分母为0时设为1，避免除零错误 + denominator = last_week_revenue if last_week_revenue > 0 else 1 + wow_rate = (weekly_revenue_total - last_week_revenue) / denominator + income_metrics['revenue_wow_growth_rate'] = wow_rate + print(f" [计算] 周环比: {wow_rate:.4f} (本周¥{weekly_revenue_total:.2f} vs 上周¥{last_week_revenue:.2f})") # 计算月环比：当月 vs 上月 + # 公式：月环比 = (当月收益 - 上月收益) / 上月收益 last_month_revenue = self.calculate_last_month_revenue_from_db(author_id, formatted_date) monthly_revenue = income_metrics['monthly_revenue'] - if last_month_revenue > 0: - income_metrics['revenue_mom_growth_rate'] = (monthly_revenue - last_month_revenue) / last_month_revenue - print(f" [计算] 月环比: {income_metrics['revenue_mom_growth_rate']:.2%} (当月¥{monthly_revenue:.2f} vs 上月¥{last_month_revenue:.2f})") - else: - print(f" [计算] 月环比: 无法计算（上月没有数据）") + # 分母为0时设为1，避免除零错误 + denominator = last_month_revenue if last_month_revenue > 0 else 1 + mom_rate = (monthly_revenue - last_month_revenue) / denominator + income_metrics['revenue_mom_growth_rate'] = mom_rate + print(f" [计算] 月环比: {mom_rate:.4f} (当月¥{monthly_revenue:.2f} vs 上月¥{last_month_revenue:.2f})") else: # 如果不使用数据库，weekly_revenue = 当日收益 income_metrics['weekly_revenue'] = income_metrics['day_revenue'] + income_metrics['monthly_revenue'] = income_metrics['day_revenue'] print(f" [跳过数据库] 当周收益 = 当日收益: ¥{income_metrics['day_revenue']:.2f}") + print(f" [跳过数据库] 当月收益 = 当日收益: ¥{income_metrics['day_revenue']:.2f}") row = { 'author_id': author_id, @@ -940,6 +1104,10 @@ class DataExporter: print(f"[OK] ai_statistics_days 表数据已导出到: {self.output_ai_statistics_days}") print(f" 共 {len(csv_rows)} 条记录") print(f"{'='*70}") + + # 备份CSV文件 + self._backup_csv_file(self.output_ai_statistics_days) + return True else: print("\n[!] 没有数据可导出") @@ -1439,9 +1607,6 @@ class DataExporter: # 滑图占比需要限制在decimal(5,4)范围内（0-9.9999） slide_ratio_value = float(metrics['slide_ratio']) - # 如果值大于10，说明是百分比格式，需要除以100 - if slide_ratio_value > 10: - slide_ratio_value = slide_ratio_value / 100 # 确保不超过9.9999 slide_ratio_value = min(slide_ratio_value, 9.9999) @@ -1547,14 +1712,28 @@ class DataExporter: else: print(f" [使用API] 投稿量: {total_submission_count}") - # 滑图占比需要限制在decimal(5,4)范围内（0-9.9999） - slide_ratio_value = float(latest_day_data.get('pic_slide_rate', 0) or 0) - # 如果值大于10，说明是百分比格式，需要除以100 - if slide_ratio_value > 10: - slide_ratio_value = slide_ratio_value / 100 - # 确保不超过9.9999 + # 所有rate字段需要限制在decimal(5,4)范围内（0-9.9999） + # API返回的都是百分制，需要除以100转换为小数 + slide_ratio_raw = float(latest_day_data.get('pic_slide_rate', 0) or 0) + slide_ratio_value = (slide_ratio_raw / 100 if slide_ratio_raw > 0 else 0.0) slide_ratio_value = min(slide_ratio_value, 9.9999) + comment_rate_raw = float(latest_day_data.get('comment_rate', 0) or 0) + comment_rate_value = (comment_rate_raw / 100 if comment_rate_raw > 0 else 0.0) + comment_rate_value = min(comment_rate_value, 9.9999) + + like_rate_raw = float(latest_day_data.get('likes_rate', 0) or 0) + like_rate_value = (like_rate_raw / 100 if like_rate_raw > 0 else 0.0) + like_rate_value = min(like_rate_value, 9.9999) + + favorite_rate_raw = float(latest_day_data.get('collect_rate', 0) or 0) + favorite_rate_value = (favorite_rate_raw / 100 if favorite_rate_raw > 0 else 0.0) + favorite_rate_value = min(favorite_rate_value, 9.9999) + + share_rate_raw = float(latest_day_data.get('share_rate', 0) or 0) + share_rate_value = (share_rate_raw / 100 if share_rate_raw > 0 else 0.0) + share_rate_value = min(share_rate_value, 9.9999) + record = { 'author_id': author_id, 'author_name': account_id, @@ -1566,10 +1745,10 @@ class DataExporter: 'total_like_count': int(latest_day_data.get('likes_count', 0) or 0), 'total_favorite_count': int(latest_day_data.get('collect_count', 0) or 0), 'total_share_count': int(latest_day_data.get('share_count', 0) or 0), - 'avg_comment_rate': float(latest_day_data.get('comment_rate', 0) or 0), - 'avg_like_rate': float(latest_day_data.get('likes_rate', 0) or 0), - 'avg_favorite_rate': float(latest_day_data.get('collect_rate', 0) or 0), - 'avg_share_rate': float(latest_day_data.get('share_rate', 0) or 0), + 'avg_comment_rate': comment_rate_value, + 'avg_like_rate': like_rate_value, + 'avg_favorite_rate': favorite_rate_value, + 'avg_share_rate': share_rate_value, 'avg_slide_ratio': slide_ratio_value, 'total_baidu_search_volume': int(latest_day_data.get('disp_pv', 0) or 0), } @@ -1698,18 +1877,38 @@ class DataExporter: def main(): + import argparse + + # 解析命令行参数 + parser = argparse.ArgumentParser( + description='百家号数据导出工具 - 从 bjh_integrated_data.json 导出', + formatter_class=argparse.RawDescriptionHelpFormatter + ) + + parser.add_argument( + '--mode', + type=str, + choices=['csv', 'database'], + default='csv', + help='导出模式：csv=导出CSV文件, database=直接插入数据库 (默认: csv)' + ) + + parser.add_argument( + '--no-confirm', + action='store_true', + help='跳过确认提示，直接执行（用于批量脚本）' + ) + + args = parser.parse_args() + print("\n" + "="*70) print("百家号数据导出工具 - 从 bjh_integrated_data.json 导出") print("="*70) # 选择导出模式 - print("\n请选择导出模式：") - print(" 1. 导出CSV文件") - print(" 2. 直接插入数据库") + use_database = (args.mode == 'database') - mode = input("\n输入选项 (1/2, 默认1): ").strip() or '1' - - if mode == '2': + if use_database: # 数据库模式 exporter = DataExporter(use_database=True) @@ -1728,13 +1927,15 @@ def main(): print(" 3. ai_statistics_days.csv - 核心指标统计表（含发文量、收益、环比）") print("="*70) - confirm = input("\n是否继续? (y/n): ").strip().lower() + # 确认执行（除非使用--no-confirm参数） + if not args.no_confirm: + confirm = input("\n是否继续? (y/n): ").strip().lower() + + if confirm != 'y': + print("\n已取消") + return - if confirm == 'y': - exporter.export_all_tables() - else: - print("\n已取消") - return + exporter.export_all_tables() print("\n" + "="*70) print("完成") diff --git a/fetch_date_statistics.py b/fetch_date_statistics.py new file mode 100644 index 0000000..f1c72c0 --- /dev/null +++ b/fetch_date_statistics.py @@ -0,0 +1,680 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +指定日期统计数据获取脚本 +功能：获取指定日期的百家号统计数据并填充到数据库三个统计表 +""" + +import os +import sys +import json +import argparse +import requests +import time +from datetime import datetime, timedelta +from typing import List, Dict, Optional +from decimal import Decimal + +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) + +from database_config import DatabaseManager +from export_to_csv import DataExporter + +# 天启代理配置 +PROXY_API_URL = 'http://api.tianqiip.com/getip?secret=tmcrmh3q&num=1&type=txt&port=1&mr=1&sign=5451e454a54b9f1f06222606c418e12f' + + +class DateStatisticsFetcher: + """指定日期统计数据获取器""" + + def __init__(self, target_date: str, use_proxy: bool = True): + """初始化 + + Args: + target_date: 目标日期 (YYYY-MM-DD) + use_proxy: 是否使用代理（默认True） + """ + self.target_date = datetime.strptime(target_date, '%Y-%m-%d') + self.target_date_str = target_date + self.db_manager = DatabaseManager() + self.script_dir = os.path.dirname(os.path.abspath(__file__)) + self.use_proxy = use_proxy + self.current_proxy = None + + # 创建临时数据目录 + self.temp_dir = os.path.join(self.script_dir, 'temp_data') + os.makedirs(self.temp_dir, exist_ok=True) + + # 创建请求会话 + self.session = requests.Session() + self.session.verify = False + + # 禁用SSL警告 + import urllib3 + urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) + + print(f"[初始化] 目标日期: {target_date}") + print(f"[初始化] 代理模式: {'启用' if use_proxy else '禁用'}") + print(f"[初始化] 临时数据目录: {self.temp_dir}") + + def get_all_authors(self) -> List[Dict]: + """获取所有活跃账号 + + Returns: + 账号列表 + """ + try: + sql = """ + SELECT id as author_id, author_name, toutiao_cookie + FROM ai_authors + WHERE channel = 1 + AND status = 'active' + AND toutiao_cookie IS NOT NULL + AND toutiao_cookie != '' + ORDER BY id + """ + + accounts = self.db_manager.execute_query(sql, fetch_one=False, dict_cursor=True) + + if accounts: + print(f"[数据库] 找到 {len(accounts)} 个活跃账号") + return accounts + else: + print("[!] 未找到任何活跃账号") + return [] + + except Exception as e: + print(f"[X] 查询账号失败: {e}") + return [] + + def get_daily_article_count(self, author_id: int, date_str: str) -> int: + """从ai_articles表获取指定日期的发文量 + + Args: + author_id: 作者ID + date_str: 日期字符串 (YYYY-MM-DD) + + Returns: + 发文量 + """ + try: + sql = """ + SELECT COUNT(*) as count + FROM ai_articles + WHERE author_id = %s + AND DATE(publish_time) = %s + AND status = 'published' + AND channel = 1 + """ + + result = self.db_manager.execute_query( + sql, + (author_id, date_str), + fetch_one=True, + dict_cursor=True + ) + + return result['count'] if result else 0 + except Exception as e: + print(f" [!] 查询发文量失败: {e}") + return 0 + + def fetch_daily_income(self, cookie_string: str, date_timestamp: int, max_retries: int = 3) -> Optional[Dict]: + """获取指定日期的收入数据（带重试机制） + + Args: + cookie_string: Cookie字符串 + date_timestamp: 日期Unix时间戳（秒） + max_retries: 最大重试次数 + + Returns: + 收入数据字典，失败返回None + """ + api_url = "https://baijiahao.baidu.com/author/eco/income4/overviewhomelist" + + # 设置Cookie + self.session.cookies.clear() + for item in cookie_string.split(';'): + item = item.strip() + if '=' in item: + key, value = item.split('=', 1) + self.session.cookies.set(key.strip(), value.strip()) + + # 从Cookie中提取token + token_cookie = self.session.cookies.get('bjhStoken') or self.session.cookies.get('devStoken') + + # 请求参数 + params = { + 'start_date': date_timestamp, + 'end_date': date_timestamp + } + + # 请求头 + headers = { + 'Accept': 'application/json, text/plain, */*', + 'Accept-Language': 'zh-CN,zh;q=0.9', + 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', + 'Referer': 'https://baijiahao.baidu.com/builder/rc/incomecenter', + 'Sec-Fetch-Dest': 'empty', + 'Sec-Fetch-Mode': 'cors', + 'Sec-Fetch-Site': 'same-origin', + } + + if token_cookie: + headers['token'] = token_cookie + + retry_count = 0 + while retry_count <= max_retries: + try: + # 如果是重试，先等待 + if retry_count > 0: + wait_time = retry_count * 3 # 3秒、6秒、9秒 + print(f" [重试 {retry_count}/{max_retries}] 等待 {wait_time} 秒...") + time.sleep(wait_time) + + # 获取代理 + proxies = self.fetch_proxy() if self.use_proxy else None + + response = self.session.get( + api_url, + headers=headers, + params=params, + proxies=proxies, + timeout=15 + ) + + if response.status_code == 200: + data = response.json() + if data.get('errno') == 0: + return data + else: + error_msg = data.get('errmsg', '') + errno = data.get('errno') + print(f" [!] API返回错误: errno={errno}, errmsg={error_msg}") + + # 异常请求错误，尝试重试 + if errno == 10000015 and retry_count < max_retries: + retry_count += 1 + continue + return None + else: + print(f" [!] HTTP错误: {response.status_code}") + return None + + except Exception as e: + error_type = type(e).__name__ + print(f" [!] 请求异常: {error_type} - {e}") + + # 判断是否需要重试 + is_retry_error = any([ + 'Connection' in error_type, + 'Timeout' in error_type, + 'ProxyError' in error_type, + ]) + + if is_retry_error and retry_count < max_retries: + retry_count += 1 + continue + return None + + return None + + def fetch_analytics_api(self, cookie_string: str, target_date: str, max_retries: int = 3) -> Optional[Dict]: + """调用百家号发文统计API获取阅读量、评论量等数据 + + Args: + cookie_string: Cookie字符串 + target_date: 目标日期 (YYYY-MM-DD) + max_retries: 最大重试次数 + + Returns: + API返回数据，失败返回None + """ + # 设置Cookie + self.session.cookies.clear() + for item in cookie_string.split(';'): + item = item.strip() + if '=' in item: + key, value = item.split('=', 1) + self.session.cookies.set(key.strip(), value.strip(), domain='.baidu.com') + + # 从Cookie中提取token + token_cookie = self.session.cookies.get('bjhStoken') or self.session.cookies.get('devStoken') + + # 计算日期范围（仅查询目标日期当天） + date_obj = datetime.strptime(target_date, '%Y-%m-%d') + start_day = date_obj.strftime('%Y%m%d') + end_day = start_day # 开始和结束是同一天 + + # API端点（使用appStatisticV3） + api_url = "https://baijiahao.baidu.com/author/eco/statistics/appStatisticV3" + + # 请求参数 + params = { + 'type': 'event', + 'start_day': start_day, + 'end_day': end_day, + 'stat': '0', + 'special_filter_days': '1' + } + + # 请求头 + headers = { + 'Accept': 'application/json, text/plain, */*', + 'Accept-Language': 'zh-CN,zh;q=0.9', + 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', + 'Referer': 'https://baijiahao.baidu.com/builder/rc/analysiscontent', + 'Sec-Fetch-Dest': 'empty', + 'Sec-Fetch-Mode': 'cors', + 'Sec-Fetch-Site': 'same-origin', + } + + if token_cookie: + headers['token'] = token_cookie + + retry_count = 0 + while retry_count <= max_retries: + try: + # 如果是重试，先等待 + if retry_count > 0: + wait_time = retry_count * 3 + print(f" [重试 {retry_count}/{max_retries}] 等待 {wait_time} 秒...") + time.sleep(wait_time) + + # 获取代理 + proxies = self.fetch_proxy() if self.use_proxy else None + + response = self.session.get( + api_url, + headers=headers, + params=params, + proxies=proxies, + timeout=15 + ) + + if response.status_code == 200: + data = response.json() + errno = data.get('errno', -1) + + if errno == 0: + # 提取total_info和list数据 + data_content = data.get('data', {}) + total_info = data_content.get('total_info', {}) + daily_list = data_content.get('list', []) + + print(f" [发文统计] 阅读量: {total_info.get('view_count', 0)}") + print(f" [发文统计] 评论量: {total_info.get('comment_count', 0)}") + + return data + else: + error_msg = data.get('errmsg', '') + print(f" [!] 发文统计API错误: errno={errno}, errmsg={error_msg}") + + if errno == 10000015 and retry_count < max_retries: + retry_count += 1 + continue + return None + else: + print(f" [!] HTTP错误: {response.status_code}") + return None + + except Exception as e: + error_type = type(e).__name__ + print(f" [!] 请求异常: {error_type} - {e}") + + is_retry_error = any([ + 'Connection' in error_type, + 'Timeout' in error_type, + 'ProxyError' in error_type, + ]) + + if is_retry_error and retry_count < max_retries: + retry_count += 1 + continue + return None + + return None + + def get_cumulative_article_count(self, author_id: int, start_date: str, end_date: str) -> int: + """从ai_articles表获取累计发文量 + + Args: + author_id: 作者ID + start_date: 开始日期 (YYYY-MM-DD) + end_date: 结束日期 (YYYY-MM-DD) + + Returns: + 累计发文量 + """ + try: + sql = """ + SELECT COUNT(*) as count + FROM ai_articles + WHERE author_id = %s + AND DATE(publish_time) >= %s + AND DATE(publish_time) <= %s + AND status = 'published' + AND channel = 1 + """ + + result = self.db_manager.execute_query( + sql, + (author_id, start_date, end_date), + fetch_one=True, + dict_cursor=True + ) + + return result['count'] if result else 0 + except Exception as e: + print(f" [!] 查询累计发文量失败: {e}") + return 0 + + def fetch_proxy(self) -> Optional[Dict]: + """获取天启代理IP + + Returns: + 代理配置字典，失败返回None + """ + if not self.use_proxy: + return None + + try: + resp = requests.get(PROXY_API_URL, timeout=10) + resp.raise_for_status() + + text = resp.text.strip() + + # 检测是否返回错误信息 + if text.upper().startswith('ERROR'): + print(f" [!] 代理API返回错误: {text}") + return None + + # 解析IP:PORT格式 + lines = text.split('\n') + for line in lines: + line = line.strip() + if ':' in line and line.count(':') == 1: + ip_port = line.split()[0] if ' ' in line else line + host, port = ip_port.split(':', 1) + proxy_url = f'http://{host}:{port}' + self.current_proxy = { + 'http': proxy_url, + 'https': proxy_url, + } + print(f" [代理] 使用天启IP: {ip_port}") + return self.current_proxy + + print(f" [!] 无法解析代理API返回: {text[:100]}") + return None + + except Exception as e: + print(f" [!] 获取代理失败: {e}") + return None + + def build_integrated_data(self, author_id: int, author_name: str, cookie_string: str) -> Dict: + """构建指定日期的整合数据 + + Args: + author_id: 作者ID + author_name: 作者名称 + cookie_string: Cookie字符串 + + Returns: + 整合数据字典 + """ + print(f"\n [构建] 账号 {author_name} 的整合数据...") + + # 计算当月第一天（用于累计发文量） + month_first = self.target_date.replace(day=1).strftime('%Y-%m-%d') + + # 从数据库获取发文量 + daily_count = self.get_daily_article_count(author_id, self.target_date_str) + cumulative_count = self.get_cumulative_article_count(author_id, month_first, self.target_date_str) + + print(f" 单日发文量: {daily_count}") + print(f" 累计发文量: {cumulative_count} (从{month_first}至{self.target_date_str})") + + # 获取发文统计数据（阅读量、评论量等） + print(f" [API] 获取发文统计数据...") + analytics_data = self.fetch_analytics_api(cookie_string, self.target_date_str) + + # 提取total_info和list数据 + total_info = {} + daily_list = [] + if analytics_data: + data_content = analytics_data.get('data', {}) + total_info = data_content.get('total_info', {}) + daily_list = data_content.get('list', []) + + # 获取收入数据 + day_revenue = 0.0 + date_timestamp = int(self.target_date.replace(hour=0, minute=0, second=0, microsecond=0).timestamp()) + + print(f" [API] 获取收入数据...") + income_data = self.fetch_daily_income(cookie_string, date_timestamp) + + if income_data and income_data.get('data', {}).get('list'): + income_list = income_data['data']['list'] + if income_list and len(income_list) > 0: + total_income = income_list[0].get('total_income', 0) + day_revenue = float(total_income) + print(f" 当日收益: ¥{day_revenue:.2f}") + else: + print(f" 当日收益: ¥0.00 (无收入数据)") + else: + print(f" 当日收益: ¥0.00 (API调用失败)") + + # 构建整合数据（模拟BaijiahaoAnalytics的数据结构） + integrated_data = { + 'account_id': author_name, + 'author_id': author_id, + 'fetch_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'), + 'target_date': self.target_date_str, + 'status': 'success', + 'analytics': { + 'apis': [ # 修改：需要包装在apis数组中 + { + 'data': { + 'errno': 0, + 'data': { + 'list': daily_list if daily_list else [ + { + 'event_day': self.target_date_str.replace('-', ''), # 格式：20251225 + 'date': self.target_date_str, + 'publish_count': daily_count, + 'daily_published_count': daily_count, + 'cumulative_published_count': cumulative_count, + } + ], + 'latest_event_day': self.target_date_str.replace('-', ''), # 格式：20251225 + 'total_info': total_info if total_info else { + 'publish_count': daily_count, + 'view_count': 0, + 'comment_count': 0, + 'comment_rate': 0, + 'likes_count': 0, + 'likes_rate': 0, + 'collect_count': 0, + 'collect_rate': 0, + 'share_count': 0, + 'share_rate': 0, + 'pic_slide_rate': 0, + 'disp_pv': 0, + } + } + } + } + ] + }, + 'income': { + 'errno': 0, # 添加：标记API调用成功 + 'data': { + 'income': { + 'yesterday': { + 'income': day_revenue # 修改：使用income字段而不是value + }, + 'currentMonth': { + 'income': 0 # 历史数据无法获取当月收益，设为0 + } + } + } + } + } + + return integrated_data + + def process_single_date(self) -> bool: + """处理单个日期的所有账号数据 + + Returns: + 是否成功 + """ + print(f"\n{'='*70}") + print(f"开始处理 {self.target_date_str} 的数据") + print(f"{'='*70}") + + # 获取所有账号 + accounts = self.get_all_authors() + if not accounts: + print("[X] 没有可用的账号，退出") + return False + + # 构建所有账号的整合数据 + integrated_data_list = [] + + for idx, account in enumerate(accounts, 1): + author_id = account.get('author_id') + author_name = account.get('author_name', '') + cookie_string = account.get('toutiao_cookie', '') + + if not author_id: + print(f"\n[{idx}/{len(accounts)}] 跳过: {author_name} (缺少author_id)") + continue + + if not cookie_string: + print(f"\n[{idx}/{len(accounts)}] 跳过: {author_name} (缺少Cookie)") + continue + + print(f"\n[{idx}/{len(accounts)}] 处理账号: {author_name} (ID: {author_id})") + + try: + integrated_data = self.build_integrated_data(author_id, author_name, cookie_string) + integrated_data_list.append(integrated_data) + print(f" [OK] 数据构建成功") + + # 延迟避免请求过快（增加到3-5秒） + if idx < len(accounts): + import random + delay = random.uniform(3, 5) + print(f" [延迟] 等待 {delay:.1f} 秒...") + time.sleep(delay) + + except Exception as e: + print(f" [X] 数据构建失败: {e}") + import traceback + traceback.print_exc() + continue + + if not integrated_data_list: + print("[!] 没有成功构建任何数据") + return False + + # 保存整合数据到临时文件 + integrated_file = os.path.join(self.temp_dir, f'integrated_{self.target_date_str}.json') + try: + with open(integrated_file, 'w', encoding='utf-8') as f: + json.dump(integrated_data_list, f, ensure_ascii=False, indent=2) + print(f"\n[保存] 整合数据: {integrated_file}") + except Exception as e: + print(f"[X] 保存整合数据失败: {e}") + return False + + # 使用DataExporter导出到三个表 + print(f"\n[导出] 开始导出到数据库...") + try: + exporter = DataExporter(use_database=False) + + # 临时替换整合数据文件路径 + original_file = exporter.integrated_file + exporter.integrated_file = integrated_file + + # 导出三个表的数据 + result = exporter.export_all_tables() + + # 恢复原路径 + exporter.integrated_file = original_file + + if result: + print(f"\n[OK] {self.target_date_str} 数据处理完成") + return True + else: + print(f"\n[!] {self.target_date_str} 数据导出失败") + return False + + except Exception as e: + print(f"[X] 导出数据失败: {e}") + import traceback + traceback.print_exc() + return False + + +def main(): + """主函数""" + parser = argparse.ArgumentParser( + description='获取指定日期的百家号统计数据', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +示例用法: + python fetch_date_statistics.py 2025-12-01 + python fetch_date_statistics.py 2025-12-15 + +注意事项: + 1. 由于百家号API限制，无法获取历史日期的收入数据 + 2. 脚本会从ai_articles表统计发文量数据 + 3. 收入字段将被设置为0（需要在数据产生当天运行才能获取真实收入） + """ + ) + + parser.add_argument( + 'date', + type=str, + help='目标日期 (格式: YYYY-MM-DD)' + ) + + parser.add_argument( + '--no-proxy', + action='store_true', + help='禁用代理（默认启用天启代理）' + ) + + args = parser.parse_args() + + # 验证日期格式 + try: + datetime.strptime(args.date, '%Y-%m-%d') + except ValueError: + print(f"[X] 日期格式错误: {args.date}") + print(" 正确格式: YYYY-MM-DD (例如: 2025-12-01)") + return 1 + + print("\n" + "="*70) + print("百家号指定日期统计数据获取工具") + print("="*70) + print(f"目标日期: {args.date}") + print("="*70) + + try: + fetcher = DateStatisticsFetcher(args.date, use_proxy=not args.no_proxy) + success = fetcher.process_single_date() + + return 0 if success else 1 + + except Exception as e: + print(f"\n[X] 程序执行出错: {e}") + import traceback + traceback.print_exc() + return 1 + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/import_csv_to_database.py b/import_csv_to_database.py index 2e159fd..5d976ea 100644 --- a/import_csv_to_database.py +++ b/import_csv_to_database.py @@ -154,10 +154,8 @@ class CSVImporter: continue try: - # 处理slide_ratio值 + # 处理slide_ratio值（CSV中已是小数格式） slide_ratio_value = float(self.convert_value(row.get('slide_ratio', '0'), 'float') or 0.0) - if slide_ratio_value > 10: - slide_ratio_value = slide_ratio_value / 100 slide_ratio_value = min(slide_ratio_value, 9.9999) # 获取channel @@ -271,9 +269,8 @@ class CSVImporter: continue try: + # 处理avg_slide_ratio值（CSV中已是小数格式） avg_slide_ratio_value = float(self.convert_value(row.get('avg_slide_ratio', '0'), 'float') or 0.0) - if avg_slide_ratio_value > 10: - avg_slide_ratio_value = avg_slide_ratio_value / 100 avg_slide_ratio_value = min(avg_slide_ratio_value, 9.9999) # 获取channel并查询author_id @@ -348,13 +345,14 @@ class CSVImporter: return success_count > 0 def import_ai_statistics_days(self, batch_size: int = 50) -> bool: - """导入 ai_statistics_days 表数据（使用批量提交） + """导入 ai_statistics_days 表数据（仅当日数据：day_revenue） + 同时自动拆分数据到 ai_statistics_weekly 和 ai_statistics_monthly 表 Args: batch_size: 批量提交大小，默认50条 """ print("\n" + "="*70) - print("开始导入 ai_statistics_days 表数据") + print("开始导入 ai_statistics_days 表数据（拆分到3个表）") print("="*70) csv_file = self.csv_files['ai_statistics_days'] @@ -365,14 +363,27 @@ class CSVImporter: self.logger.warning("ai_statistics_days表没有数据可导入") return False - self.logger.info(f"开始导入ai_statistics_days表数据，共 {len(rows)} 条记录，批量大小: {batch_size}") - print(f"\n总计 {len(rows)} 条记录，分批导入（每批 {batch_size} 条）\n") + self.logger.info(f"开始导入数据，共 {len(rows)} 条记录，批量大小: {batch_size}") + print(f"\n总计 {len(rows)} 条记录，将拆分到3个表\n") - success_count = 0 + # 三个表的统计 + days_success = 0 + weekly_success = 0 + monthly_success = 0 failed_count = 0 - batch_params = [] - first_record_keys = None - sql_template = None + + # 批量参数 + days_batch = [] + weekly_batch = [] + monthly_batch = [] + + # SQL模板 + days_sql = None + weekly_sql = None + monthly_sql = None + days_keys = None + weekly_keys = None + monthly_keys = None for idx, row in enumerate(rows, 1): author_name = row.get('author_name', '').strip() @@ -388,68 +399,153 @@ class CSVImporter: failed_count += 1 continue - # 处理day_revenue字段（每日收益） - day_revenue_value = self.convert_value(row.get('day_revenue', '0'), 'decimal') - if day_revenue_value is None: - day_revenue_value = Decimal('0') + stat_date = row.get('stat_date', '').strip() - record = { + # 1. ai_statistics_days 表数据（仅当日数据） + day_revenue = self.convert_value(row.get('day_revenue', '0'), 'decimal') or Decimal('0') + daily_published_count = self.convert_value(row.get('daily_published_count', '0'), 'int') or 0 + cumulative_published_count = self.convert_value(row.get('cumulative_published_count', '0'), 'int') or 0 + + days_record = { 'author_id': author_id, 'author_name': author_name, 'channel': channel, - 'stat_date': row.get('stat_date', '').strip(), - 'daily_published_count': self.convert_value(row.get('daily_published_count', '0'), 'int') or 0, - 'cumulative_published_count': self.convert_value(row.get('cumulative_published_count', '0'), 'int') or 0, - 'day_revenue': day_revenue_value, # 每日收益 - 'monthly_revenue': self.convert_value(row.get('monthly_revenue', '0'), 'decimal') or Decimal('0'), - 'weekly_revenue': self.convert_value(row.get('weekly_revenue', '0'), 'decimal') or Decimal('0'), - 'revenue_mom_growth_rate': self.convert_value(row.get('revenue_mom_growth_rate', '0'), 'decimal') or Decimal('0'), - 'revenue_wow_growth_rate': self.convert_value(row.get('revenue_wow_growth_rate', '0'), 'decimal') or Decimal('0'), - 'updated_at': datetime.now().strftime('%Y-%m-%d %H:%M:%S'), # 添加更新时间戳，强制更新 + 'stat_date': stat_date, + 'daily_published_count': daily_published_count, + 'day_revenue': day_revenue, + 'updated_at': datetime.now().strftime('%Y-%m-%d %H:%M:%S'), } - if sql_template is None: - first_record_keys = list(record.keys()) - columns = ', '.join(first_record_keys) - placeholders = ', '.join(['%s'] * len(first_record_keys)) - update_parts = [f"{key} = VALUES({key})" for key in first_record_keys if key not in ['author_name', 'channel', 'stat_date']] - sql_template = f""" + # 2. ai_statistics_weekly 表数据 + weekly_revenue = self.convert_value(row.get('weekly_revenue', '0'), 'decimal') or Decimal('0') + revenue_wow_growth_rate = self.convert_value(row.get('revenue_wow_growth_rate', '0'), 'decimal') or Decimal('0') + + # 计算该日期所在周次（格式：WW，如51） + from datetime import datetime as dt, timedelta + date_obj = dt.strptime(stat_date, '%Y-%m-%d') + # 使用isocalendar()获取ISO周数（周一为一周开始） + year, week_num, _ = date_obj.isocalendar() + stat_weekly = week_num # 直接使用数字 + + weekly_record = { + 'author_id': author_id, + 'author_name': author_name, + 'channel': channel, + 'stat_weekly': stat_weekly, + 'weekly_revenue': weekly_revenue, + 'revenue_wow_growth_rate': revenue_wow_growth_rate, + 'updated_at': datetime.now().strftime('%Y-%m-%d %H:%M:%S'), + } + + # 3. ai_statistics_monthly 表数据 + monthly_revenue = self.convert_value(row.get('monthly_revenue', '0'), 'decimal') or Decimal('0') + revenue_mom_growth_rate = self.convert_value(row.get('revenue_mom_growth_rate', '0'), 'decimal') or Decimal('0') + + # 计算该日期所在月份（格式：YYYY-MM，如2025-12） + stat_monthly = date_obj.strftime('%Y-%m') + + monthly_record = { + 'author_id': author_id, + 'author_name': author_name, + 'channel': channel, + 'stat_monthly': stat_monthly, + 'monthly_revenue': monthly_revenue, + 'revenue_mom_growth_rate': revenue_mom_growth_rate, + 'updated_at': datetime.now().strftime('%Y-%m-%d %H:%M:%S'), + } + + # 构建SQL模板（首次） + if days_sql is None: + days_keys = list(days_record.keys()) + columns = ', '.join(days_keys) + placeholders = ', '.join(['%s'] * len(days_keys)) + update_parts = [f"{key} = VALUES({key})" for key in days_keys if key not in ['author_name', 'channel', 'stat_date']] + days_sql = f""" INSERT INTO ai_statistics_days ({columns}) VALUES ({placeholders}) ON DUPLICATE KEY UPDATE {', '.join(update_parts)} """ - if first_record_keys is not None: - batch_params.append(tuple(record[key] for key in first_record_keys)) + if weekly_sql is None: + weekly_keys = list(weekly_record.keys()) + columns = ', '.join(weekly_keys) + placeholders = ', '.join(['%s'] * len(weekly_keys)) + update_parts = [f"{key} = VALUES({key})" for key in weekly_keys if key not in ['author_name', 'channel', 'stat_weekly']] + weekly_sql = f""" + INSERT INTO ai_statistics_weekly ({columns}) + VALUES ({placeholders}) + ON DUPLICATE KEY UPDATE {', '.join(update_parts)} + """ - if len(batch_params) >= batch_size or idx == len(rows): + if monthly_sql is None: + monthly_keys = list(monthly_record.keys()) + columns = ', '.join(monthly_keys) + placeholders = ', '.join(['%s'] * len(monthly_keys)) + update_parts = [f"{key} = VALUES({key})" for key in monthly_keys if key not in ['author_name', 'channel', 'stat_monthly']] + monthly_sql = f""" + INSERT INTO ai_statistics_monthly ({columns}) + VALUES ({placeholders}) + ON DUPLICATE KEY UPDATE {', '.join(update_parts)} + """ + + # 添加到批量参数 + days_batch.append(tuple(days_record[key] for key in days_keys)) + weekly_batch.append(tuple(weekly_record[key] for key in weekly_keys)) + monthly_batch.append(tuple(monthly_record[key] for key in monthly_keys)) + + # 批量提交 + if len(days_batch) >= batch_size or idx == len(rows): try: - result_count = self.db_manager.execute_many(sql_template, batch_params, autocommit=True) - success_count += result_count - print(f"[批次提交] 已导入 {success_count} 条记录（本批: {result_count}/{len(batch_params)}）") - self.logger.info(f"ai_statistics_days表批量提交: {result_count}/{len(batch_params)} 条记录") - batch_params = [] - except Exception as batch_error: - failed_count += len(batch_params) - print(f" [X] 批次提交失败: {batch_error}") - self.logger.error(f"ai_statistics_days表批量提交失败: {batch_error}") - batch_params = [] + # 提交 ai_statistics_days + result = self.db_manager.execute_many(days_sql, days_batch, autocommit=True) + days_success += result + print(f"[days] 已导入 {days_success} 条") + days_batch = [] + except Exception as e: + print(f" [X] days表提交失败: {e}") + self.logger.error(f"ai_statistics_days批量提交失败: {e}") + failed_count += len(days_batch) + days_batch = [] + + try: + # 提交 ai_statistics_weekly + result = self.db_manager.execute_many(weekly_sql, weekly_batch, autocommit=True) + weekly_success += result + print(f"[weekly] 已导入 {weekly_success} 条") + weekly_batch = [] + except Exception as e: + print(f" [X] weekly表提交失败: {e}") + self.logger.error(f"ai_statistics_weekly批量提交失败: {e}") + weekly_batch = [] + + try: + # 提交 ai_statistics_monthly + result = self.db_manager.execute_many(monthly_sql, monthly_batch, autocommit=True) + monthly_success += result + print(f"[monthly] 已导入 {monthly_success} 条") + monthly_batch = [] + except Exception as e: + print(f" [X] monthly表提交失败: {e}") + self.logger.error(f"ai_statistics_monthly批量提交失败: {e}") + monthly_batch = [] except Exception as e: failed_count += 1 print(f" [X] 处理失败 ({author_name}): {e}") - self.logger.error(f"ai_statistics_days表处理失败: {author_name}, 错误: {e}") + self.logger.error(f"数据处理失败: {author_name}, 错误: {e}") continue print("\n" + "="*70) - print(f"[OK] ai_statistics_days 表数据导入完成") - print(f" 成功: {success_count} 条记录") + print(f"[OK] 数据导入完成（拆分到3个表）") + print(f" ai_statistics_days: {days_success} 条") + print(f" ai_statistics_weekly: {weekly_success} 条") + print(f" ai_statistics_monthly: {monthly_success} 条") if failed_count > 0: - print(f" 失败: {failed_count} 条记录") + print(f" 失败: {failed_count} 条") print("="*70) - self.logger.info(f"ai_statistics_days表数据导入完成: 成功 {success_count} 条，失败 {failed_count} 条") - return success_count > 0 + self.logger.info(f"数据导入完成: days={days_success}, weekly={weekly_success}, monthly={monthly_success}, failed={failed_count}") + return days_success > 0 def import_all(self) -> bool: """导入所有CSV文件""" diff --git a/input.txt b/input.txt new file mode 100644 index 0000000..e69de29 diff --git a/query_statistics.py b/query_statistics.py new file mode 100644 index 0000000..e69de29 diff --git a/sms_config.json b/sms_config.json new file mode 100644 index 0000000..d32e9d2 --- /dev/null +++ b/sms_config.json @@ -0,0 +1,15 @@ +{ + "阿里云配置说明": "请填写您的阿里云短信服务配置", + "access_key_id": "LTAI5tSMvnCJdqkZtCVWgh8R", + "access_key_secret": "nyFzXyIi47peVLK4wR2qqbPezmU79W", + "sign_name": "北京乐航时代科技", + "template_code": "SMS_486210104", + "phone_numbers": "13621242430", + "endpoint": "dysmsapi.aliyuncs.com", + "注意事项": [ + "access_key_id 和 access_key_secret 可在 https://ram.console.aliyun.com/manage/ak 获取", + "sign_name 需要在阿里云短信服务控制台申请并通过审核", + "template_code 是短信模板代码，需要在阿里云短信服务控制台申请", + "phone_numbers 可以配置多个手机号，用逗号分隔，如: 13621242430,13800138000" + ] +} diff --git a/sync_cookies_to_db.py b/sync_cookies_to_db.py index 80ff7d0..daa2a15 100644 --- a/sync_cookies_to_db.py +++ b/sync_cookies_to_db.py @@ -277,17 +277,44 @@ class CookieSyncToDB: # 转换Cookie为字符串 cookie_string = self.cookie_dict_to_string(cookies) - # 提取其他信息 + # 提取其他信息（使用username和nick作为author_name进行匹配） + username = account_info.get('username', '') # 优先用于与数据库author_name匹配 + nick = account_info.get('nick', '') # 备用匹配字段 app_id = account_info.get('app_id', '') - nick = account_info.get('nick', '') domain = account_info.get('domain', '') level = account_info.get('level', '') - # 查找作者（使用 author_name + channel 作为唯一键） + # 验证username或nick至少有一个存在 + if not username and not nick: + print(" [!] 该账号没有username和nick字段，跳过") + stats['skipped'] += 1 + continue + + print(f" Username: {username}") + print(f" 昵称: {nick}") + + # 查找作者（使用双重匹配机制：先username，后nick） channel = 1 # 百家号固定为channel=1 - author = self.find_author_by_name(account_name, channel) - if author: - print(f" [√] 找到作者: {author['author_name']} (ID: {author['id']}, Channel: {author['channel']})") + author = None + matched_field = None + + # 1. 首先尝试使用username匹配 + if username: + author = self.find_author_by_name(username, channel) + if author: + matched_field = 'username' + print(f" [√] 通过username匹配到作者: {author['author_name']} (ID: {author['id']}, Channel: {author['channel']})") + + # 2. 如果username匹配失败，尝试使用nick匹配 + if not author and nick: + author = self.find_author_by_name(nick, channel) + if author: + matched_field = 'nick' + print(f" [√] 通过nick匹配到作者: {author['author_name']} (ID: {author['id']}, Channel: {author['channel']})") + + # 3. 如果都没匹配到 + if not author: + print(f" [!] 未找到匹配的作者（已尝试username和nick）") # 更新或创建 if author: @@ -300,15 +327,17 @@ class CookieSyncToDB: ) if success: - print(f" [OK] Cookie已更新") + print(f" [OK] Cookie已更新（匹配字段: {matched_field}）") stats['updated'] += 1 # 记录成功 success_records.append({ 'account_name': account_name, - 'app_id': app_id, + 'username': username, 'nick': nick, + 'app_id': app_id, 'domain': domain, 'action': 'updated', + 'matched_field': matched_field, 'db_author_id': author['id'], 'db_author_name': author['author_name'] }) @@ -318,17 +347,21 @@ class CookieSyncToDB: # 记录失败 failed_records.append({ 'account_name': account_name, - 'app_id': app_id, + 'username': username, 'nick': nick, + 'app_id': app_id, 'reason': '数据库更新失败', + 'matched_field': matched_field, 'db_author_id': author['id'] }) else: - # 作者不存在 + # 作者不存在，考虑创建 if auto_create: - print(f" [*] 作者不存在，创建新记录...") + # 优先使用username，如果没有则使用nick + author_name_to_create = username if username else nick + print(f" [*] 作者不存在，创建新记录（author_name: {author_name_to_create}）...") success = self.insert_new_author( - account_name, + author_name_to_create, # 优先使用username，否则使用nick cookie_string, app_id, nick, @@ -337,15 +370,17 @@ class CookieSyncToDB: ) if success: - print(f" [OK] 新作者已创建") + print(f" [OK] 新作者已创建 (author_name: {author_name_to_create})") stats['created'] += 1 # 记录成功 success_records.append({ 'account_name': account_name, - 'app_id': app_id, + 'username': username, 'nick': nick, + 'app_id': app_id, 'domain': domain, - 'action': 'created' + 'action': 'created', + 'created_with': 'username' if username else 'nick' }) else: print(f" [X] 创建作者失败") @@ -353,8 +388,9 @@ class CookieSyncToDB: # 记录失败 failed_records.append({ 'account_name': account_name, - 'app_id': app_id, + 'username': username, 'nick': nick, + 'app_id': app_id, 'reason': '数据库插入失败' }) else: @@ -363,9 +399,10 @@ class CookieSyncToDB: # 记录失败（数据库中不存在） failed_records.append({ 'account_name': account_name, - 'app_id': app_id, + 'username': username, 'nick': nick, - 'reason': '数据库中不存在该账号，且未开启自动创建' + 'app_id': app_id, + 'reason': '数据库中不存在该账号（已尝试username和nick），且未开启自动创建' }) # 保存记录文件 diff --git a/test_validation_sms.bat b/test_validation_sms.bat new file mode 100644 index 0000000..705539b --- /dev/null +++ b/test_validation_sms.bat @@ -0,0 +1,40 @@ +@echo off +chcp 65001 >nul +echo ============================================================ +echo 数据验证与短信告警系统 - 快速测试 +echo ============================================================ +echo. + +echo [步骤1] 检查Python环境... +python --version +if %errorlevel% neq 0 ( + echo [错误] Python未安装或未添加到PATH + pause + exit /b 1 +) +echo. + +echo [步骤2] 测试短信发送功能... +echo. +python data_validation_with_sms.py --test-sms +if %errorlevel% neq 0 ( + echo. + echo [错误] 短信发送测试失败 + echo 请检查: + echo 1. 阿里云SDK是否已安装 + echo 2. sms_config.json配置是否正确 + echo 3. AccessKey和Secret是否有效 + pause + exit /b 1 +) +echo. + +echo [步骤3] 执行数据验证... +echo. +python data_validation_with_sms.py +echo. + +echo ============================================================ +echo 测试完成！ +echo ============================================================ +pause diff --git a/test_validation_sms.sh b/test_validation_sms.sh new file mode 100644 index 0000000..6efcf77 --- /dev/null +++ b/test_validation_sms.sh @@ -0,0 +1,47 @@ +#!/bin/bash +# 数据验证与短信告警系统 - 快速测试（Linux版本） + +echo "============================================================" +echo "数据验证与短信告警系统 - 快速测试" +echo "============================================================" +echo "" + +echo "[步骤1] 检查Python环境..." +if command -v python3 &> /dev/null; then + PYTHON_CMD=python3 +elif command -v python &> /dev/null; then + PYTHON_CMD=python +else + echo "[错误] Python未安装或未添加到PATH" + exit 1 +fi + +$PYTHON_CMD --version +if [ $? -ne 0 ]; then + echo "[错误] Python版本检查失败" + exit 1 +fi +echo "" + +echo "[步骤2] 测试短信发送功能..." +echo "" +$PYTHON_CMD data_validation_with_sms.py --test-sms +if [ $? -ne 0 ]; then + echo "" + echo "[错误] 短信发送测试失败" + echo "请检查:" + echo " 1. 阿里云SDK是否已安装" + echo " 2. sms_config.json配置是否正确" + echo " 3. AccessKey和Secret是否有效" + exit 1 +fi +echo "" + +echo "[步骤3] 执行数据验证..." +echo "" +$PYTHON_CMD data_validation_with_sms.py +echo "" + +echo "============================================================" +echo "测试完成！" +echo "============================================================" diff --git a/update_day_revenue.py b/update_day_revenue.py new file mode 100644 index 0000000..941e73b --- /dev/null +++ b/update_day_revenue.py @@ -0,0 +1,151 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +更新day_revenue脚本 +功能：从CSV文件读取数据，只更新ai_statistics_days表中的day_revenue字段 +""" + +import os +import sys +import csv +from typing import List, Dict +from decimal import Decimal + +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) + +from database_config import DatabaseManager + + +class DayRevenueUpdater: + """day_revenue字段更新器""" + + def __init__(self): + """初始化""" + self.db_manager = DatabaseManager() + self.script_dir = os.path.dirname(os.path.abspath(__file__)) + self.csv_file = os.path.join(self.script_dir, 'ai_statistics_days.csv') + + print(f"[初始化] CSV文件: {self.csv_file}") + + def read_csv_data(self) -> List[Dict]: + """读取CSV文件数据 + + Returns: + 数据列表 + """ + if not os.path.exists(self.csv_file): + print(f"[X] CSV文件不存在: {self.csv_file}") + return [] + + try: + with open(self.csv_file, 'r', encoding='utf-8-sig') as f: + reader = csv.DictReader(f) + data = list(reader) + + print(f"[OK] 读取到 {len(data)} 条记录") + return data + except Exception as e: + print(f"[X] 读取CSV失败: {e}") + import traceback + traceback.print_exc() + return [] + + def update_day_revenue(self, batch_size: int = 50) -> bool: + """更新day_revenue字段 + + Args: + batch_size: 批量更新大小 + + Returns: + 是否成功 + """ + # 读取CSV数据 + csv_data = self.read_csv_data() + if not csv_data: + print("[!] 没有数据需要更新") + return False + + print(f"\n[开始] 更新day_revenue字段...") + + # 准备批量更新 + update_sql = """ + UPDATE ai_statistics_days + SET day_revenue = %s, + updated_at = NOW() + WHERE author_id = %s + AND stat_date = %s + AND channel = %s + """ + + success_count = 0 + failed_count = 0 + not_found_count = 0 + + # 逐条更新 + for idx, row in enumerate(csv_data, 1): + try: + author_id = int(row.get('author_id', 0)) + stat_date = row.get('stat_date', '') + channel = int(row.get('channel', 1)) + day_revenue = Decimal(row.get('day_revenue', '0.00')) + + # 执行更新 + affected_rows = self.db_manager.execute_update( + update_sql, + (day_revenue, author_id, stat_date, channel) + ) + + if affected_rows > 0: + success_count += 1 + print(f" [{idx}/{len(csv_data)}] ✓ 更新成功: author_id={author_id}, stat_date={stat_date}, day_revenue={day_revenue}") + else: + not_found_count += 1 + print(f" [{idx}/{len(csv_data)}] - 未找到记录: author_id={author_id}, stat_date={stat_date}") + + except Exception as e: + failed_count += 1 + print(f" [{idx}/{len(csv_data)}] ✗ 更新失败: {e}") + print(f" 数据: {row}") + + # 输出统计 + print(f"\n{'='*70}") + print(f"更新完成") + print(f"{'='*70}") + print(f"成功更新: {success_count}/{len(csv_data)}") + print(f"未找到记录: {not_found_count}/{len(csv_data)}") + print(f"更新失败: {failed_count}/{len(csv_data)}") + print(f"{'='*70}") + + return failed_count == 0 + + +def main(): + """主函数""" + print("\n" + "="*70) + print("day_revenue字段批量更新工具") + print("="*70) + print("功能：从 ai_statistics_days.csv 读取数据，只更新数据库中的 day_revenue 字段") + print("="*70) + + try: + updater = DayRevenueUpdater() + + # 确认执行 + confirm = input("\n是否开始更新? (y/n): ").strip().lower() + if confirm != 'y': + print("已取消") + return 0 + + success = updater.update_day_revenue() + + return 0 if success else 1 + + except Exception as e: + print(f"\n[X] 程序执行出错: {e}") + import traceback + traceback.print_exc() + return 1 + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/validation_report_20251230_102131.txt b/validation_report_20251230_102131.txt new file mode 100644 index 0000000..a1c25fa --- /dev/null +++ b/validation_report_20251230_102131.txt @@ -0,0 +1,8 @@ +数据验证报告 +====================================================================== +生成时间: 2025-12-30 10:21:31 +目标日期: 2025-12-30 + + +顺序验证结果 +---------------------------------------------------------------------- diff --git a/validation_report_20251230_113338.txt b/validation_report_20251230_113338.txt new file mode 100644 index 0000000..a93e042 --- /dev/null +++ b/validation_report_20251230_113338.txt @@ -0,0 +1,34 @@ +数据验证报告 +====================================================================== +生成时间: 2025-12-30 11:33:38 +目标日期: 2025-12-29 + + +顺序验证结果 +---------------------------------------------------------------------- +json vs csv + 顺序匹配: 是 + json 记录数: 84 + csv 记录数: 84 + + +交叉验证结果 +---------------------------------------------------------------------- +json vs csv + 共同记录: 84 + 仅在json: 0 + 仅在csv: 0 + 字段不匹配: 0 + +json vs database + 共同记录: 84 + 仅在json: 0 + 仅在database: 0 + 字段不匹配: 0 + +csv vs database + 共同记录: 84 + 仅在csv: 0 + 仅在database: 0 + 字段不匹配: 0 + diff --git a/参考代码/ai_keyword_crawl/baidu_crawl.py b/参考代码/ai_keyword_crawl/baidu_crawl.py index d6845ca..c1a56de 100644 --- a/参考代码/ai_keyword_crawl/baidu_crawl.py +++ b/参考代码/ai_keyword_crawl/baidu_crawl.py @@ -28,12 +28,12 @@ logger = setup_baidu_crawl_logger() # 简单的代理获取配置 - 大麦代理IP PROXY_API_URL = ( - 'https://api2.damaiip.com/index.php?s=/front/user/getIPlist&xsn=e054861d08471263d970bde4f4905181&osn=TC_NO176655872088456223&tiqu=1' + 'https://api2.damaiip.com/index.php?s=/front/user/getIPlist&xsn=2912cb2b22d3b7ae724f045012790479&osn=TC_NO176707424165606223&tiqu=1' ) # 大麦代理账号密码认证 -PROXY_USERNAME = '694b8c3172af7' -PROXY_PASSWORD = 'q8yA8x1dwCpdyIK' +PROXY_USERNAME = '69538fdef04e1' +PROXY_PASSWORD = '63v0kQBr2yJXnjf' # 备用固定代理IP池（格式：'IP:端口', '用户名', '密码'） BACKUP_PROXY_POOL = [ diff --git a/参考代码/ai_keyword_crawl/baidu_crawl_again.py b/参考代码/ai_keyword_crawl/baidu_crawl_again.py index 49a50e0..3b44362 100644 --- a/参考代码/ai_keyword_crawl/baidu_crawl_again.py +++ b/参考代码/ai_keyword_crawl/baidu_crawl_again.py @@ -27,12 +27,12 @@ if 'https_proxy' in os.environ: # 简单的代理获取配置 - 大麦代理IP PROXY_API_URL = ( - 'https://api2.damaiip.com/index.php?s=/front/user/getIPlist&xsn=e054861d08471263d970bde4f4905181&osn=TC_NO176655872088456223&tiqu=1' + 'https://api2.damaiip.com/index.php?s=/front/user/getIPlist&xsn=2912cb2b22d3b7ae724f045012790479&osn=TC_NO176707424165606223&tiqu=1' ) # 大麦代理账号密码认证 -PROXY_USERNAME = '694b8c3172af7' -PROXY_PASSWORD = 'q8yA8x1dwCpdyIK' +PROXY_USERNAME = '69538fdef04e1' +PROXY_PASSWORD = '63v0kQBr2yJXnjf' # 备用固定代理IP池（格式：'IP:端口', '用户名', '密码'） BACKUP_PROXY_POOL = [ diff --git a/备份/captured_account_cookies-6677.json b/备份/captured_account_cookies-6677.json new file mode 100644 index 0000000..26cefea --- /dev/null +++ b/备份/captured_account_cookies-6677.json @@ -0,0 +1,5619 @@ +{ + "耳鼻喉科杨书勋医生": { + "cookies": { + "__bid_n": "1921dd9d4207472857485b", + "BAIDUID": "FFCEE557FC202E38439C05DBA29FF1E6:FG=1", + "BAIDUID_BFESS": "FFCEE557FC202E38439C05DBA29FF1E6:FG=1", + "BDUSS": "kpONlRBMjdGSmhiUFBtVHhDelpiQVA4VWUzSVBZRFpjNGJjVTdOaGF3ZEtYcGRuRUFBQUFBJCQAAAAAAAAAAAEAAACQSTUbeHlodHN5MDcwMQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAErRb2dK0W9nV", + "BDUSS_BFESS": "kpONlRBMjdGSmhiUFBtVHhDelpiQVA4VWUzSVBZRFpjNGJjVTdOaGF3ZEtYcGRuRUFBQUFBJCQAAAAAAAAAAAEAAACQSTUbeHlodHN5MDcwMQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAErRb2dK0W9nV", + 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b/数据验证短信告警README.md @@ -0,0 +1,341 @@ +# 📱 数据验证与短信告警系统 + +## 🎯 功能概述 + +自动化数据验证系统，每天定时检查数据一致性，发现问题时通过阿里云短信服务发送告警。 + +**核心功能：** +- ✅ 自动验证 JSON/CSV/数据库 三个数据源的一致性 +- ✅ 验证失败自动发送短信告警（错误代码：2222） +- ✅ 支持定时任务（每天上午9点执行） +- ✅ 生成详细的验证报告 +- ✅ 支持多手机号接收告警 + +--- + +## 📁 文件结构 + +``` +xhh_baijiahao/ +├── data_validation.py # 数据验证核心模块 +├── data_validation_with_sms.py # 数据验证+短信告警集成脚本 ⭐ +├── sms_config.json # 短信服务配置文件 ⭐ +├── test_validation_sms.bat # Windows快速测试脚本 +├── 数据验证短信告警使用说明.md # 详细使用文档 +└── ai_sms/ # 阿里云短信SDK示例 + └── alibabacloud_sample/ + └── sample.py +``` + +--- + +## 🚀 快速开始（5分钟） + +### 1️⃣ 安装依赖 + +```bash +pip install alibabacloud_dysmsapi20170525 alibabacloud_credentials alibabacloud_tea_openapi alibabacloud_tea_util +``` + +### 2️⃣ 配置短信服务 + +编辑 `sms_config.json`： + +```json +{ + "access_key_id": "您的AccessKey ID", + "access_key_secret": "您的AccessKey Secret", + "sign_name": "北京乐航时代科技", + "template_code": "SMS_486210104", + "phone_numbers": "13621242430" +} +``` + +**获取AccessKey：** https://ram.console.aliyun.com/manage/ak + +### 3️⃣ 测试运行 + +**Windows用户（双击运行）：** +``` +test_validation_sms.bat +``` + +**命令行运行：** +```bash +# 测试短信发送 +python data_validation_with_sms.py --test-sms + +# 执行数据验证 +python data_validation_with_sms.py +``` + +### 4️⃣ 配置定时任务 + +```bash +# 查看配置命令 +python data_validation_with_sms.py --setup-schedule +``` + +按照提示配置Windows任务计划程序，设置每天9点自动执行。 + +--- + +## 📖 使用场景 + +### 场景1：每日自动验证 + +**定时任务配置（每天9点）：** +- 程序：`C:\Python\python.exe` +- 参数：`D:\workspace\xhh_baijiahao\data_validation_with_sms.py` +- 触发器：每天上午9:00 + +**执行流程：** +1. 自动验证昨天的数据（JSON/CSV/数据库） +2. 如果发现问题 → 发送短信告警（错误代码2222） +3. 生成详细验证报告 + +### 场景2：手动验证指定日期 + +```bash +# 验证2025-12-29的数据 +python data_validation_with_sms.py --date 2025-12-29 + +# 验证指定表 +python data_validation_with_sms.py --table ai_statistics_day --date 2025-12-29 + +# 只验证特定数据源 +python data_validation_with_sms.py --source csv database +``` + +### 场景3：仅验证不发短信 + +```bash +# 适用于调试或测试 +python data_validation_with_sms.py --no-sms +``` + +--- + +## 🔔 短信告警说明 + +### 触发条件 + +发送短信告警（错误代码：**2222**）的情况： + +| 问题类型 | 说明 | 示例 | +|---------|-----|-----| +| **顺序不一致** | JSON和CSV记录顺序不同 | 账号A在JSON第1位，CSV第3位 | +| **缺失记录** | 某个数据源少了记录 | JSON有10条，CSV只有9条 | +| **多余记录** | 某个数据源多了记录 | CSV有11条，数据库只有10条 | +| **字段差异** | 相同记录的字段值不同 | 阅读量：JSON=1000, CSV=999 | + +### 短信内容 + +``` +【北京乐航时代科技】您的验证码是2222 +``` + +> 💡 **说明**：由于使用验证码模板，错误代码固定为 `2222`。具体错误详情请查看验证报告文件。 + +### 多号码配置 + +在 `sms_config.json` 中配置多个接收号码： + +```json +{ + "phone_numbers": "13621242430,13800138000,13900139000" +} +``` + +--- + +## 📊 验证报告 + +每次验证自动生成详细报告： + +``` +validation_report_20250104_090523.txt +``` + +**报告内容：** +- ✅ 顺序验证结果 +- ✅ 交叉验证结果 +- ✅ 数据差异统计 +- ✅ 详细错误列表（记录级别） + +**示例报告片段：** +``` +交叉验证结果 +---------------------------------------------------------------------- +json vs csv + 共同记录: 48 条 + 仅在json: 0 条 + 仅在csv: 2 条 + 字段不匹配: 3 条 + +仅在csv中的记录（前5条）: + - 测试账号1|1 + - 测试账号2|1 + +字段值不匹配的记录（前3条）: + 记录: 主力账号|1 + 字段 read_count: + json: 150000 + csv: 149999 +``` + +--- + +## ⚙️ 高级配置 + +### 环境变量方式（更安全） + +**Windows PowerShell：** +```powershell +$env:ALIBABA_CLOUD_ACCESS_KEY_ID="您的AccessKey ID" +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="您的AccessKey Secret" +``` + +**Linux/macOS：** +```bash +export ALIBABA_CLOUD_ACCESS_KEY_ID="您的AccessKey ID" +export ALIBABA_CLOUD_ACCESS_KEY_SECRET="您的AccessKey Secret" +``` + +### 配置优先级 + +1. **环境变量** （最高优先级） +2. **sms_config.json** 配置文件 +3. **代码中的默认值** + +--- + +## 🔧 故障排查 + +### ❌ 短信发送失败 + +**常见原因：** +1. AccessKey ID/Secret 不正确 +2. 短信签名未审核通过 +3. 短信模板未审核通过 +4. 账户余额不足 +5. 手机号格式错误 + +**解决方法：** +```bash +# 测试短信发送 +python data_validation_with_sms.py --test-sms +``` + +查看控制台输出的详细错误信息和诊断地址。 + +### ❌ 导入错误 + +``` +ImportError: No module named 'alibabacloud_dysmsapi20170525' +``` + +**解决方法：** +```bash +pip install alibabacloud_dysmsapi20170525 alibabacloud_credentials alibabacloud_tea_openapi alibabacloud_tea_util +``` + +### ❌ 数据库连接失败 + +检查 `database_config.py` 配置是否正确。 + +### ❌ 定时任务不执行 + +**检查项：** +1. 任务计划程序中任务状态 +2. Python路径和脚本路径是否正确 +3. 查看任务历史记录 + +--- + +## 📝 命令行参数 + +```bash +python data_validation_with_sms.py [参数] +``` + +| 参数 | 说明 | 示例 | +|-----|-----|-----| +| `--date` | 指定验证日期 | `--date 2025-12-29` | +| `--source` | 指定数据源 | `--source json csv` | +| `--table` | 指定验证表 | `--table ai_statistics_day` | +| `--setup-schedule` | 配置定时任务 | `--setup-schedule` | +| `--test-sms` | 测试短信功能 | `--test-sms` | +| `--no-sms` | 禁用短信发送 | `--no-sms` | + +--- + +## 🔐 安全建议 + +1. ✅ **使用环境变量存储敏感信息** + - 不要将 AccessKey 提交到 Git + - 将 `sms_config.json` 添加到 `.gitignore` + +2. ✅ **定期轮换 AccessKey** + - 建议每3-6个月更换一次 + +3. ✅ **使用 RAM 子账号** + - 为短信服务创建专用子账号 + - 仅授予短信发送权限 + +4. ✅ **设置 IP 白名单** + - 在阿里云 RAM 控制台限制访问 IP + +--- + +## 📞 技术支持 + +### 阿里云短信服务 + +- 控制台：https://dysms.console.aliyun.com/ +- 文档：https://help.aliyun.com/product/44282.html +- API参考：https://api.aliyun.com/product/Dysmsapi + +### 常见问题 + +**Q：短信收不到？** +A：检查手机号是否正确，短信签名和模板是否已审核通过。 + +**Q：如何查看短信发送记录？** +A：登录阿里云短信服务控制台 → 业务统计 → 发送记录查询。 + +**Q：短信费用多少？** +A：验证码短信约0.045元/条，具体价格以阿里云官网为准。 + +**Q：可以自定义短信内容吗？** +A：需要在阿里云控制台申请新的短信模板，审核通过后修改 `template_code` 配置。 + +--- + +## 🎉 快速测试检查清单 + +- [ ] 安装Python依赖 +- [ ] 配置 `sms_config.json` +- [ ] 运行 `test_validation_sms.bat` +- [ ] 收到测试短信 +- [ ] 执行数据验证 +- [ ] 生成验证报告 +- [ ] 配置定时任务 + +--- + +## 📅 版本历史 + +### v1.0.0 (2025-01-04) +- ✨ 初始版本发布 +- ✅ 数据验证功能 +- ✅ 阿里云短信告警 +- ✅ 定时任务支持 +- ✅ 多数据源支持（JSON/CSV/数据库） +- ✅ 详细验证报告 +- ✅ 配置文件支持 + +--- + +**开发团队：** 北京乐航时代科技 +**最后更新：** 2025-01-04 diff --git a/数据验证短信告警使用说明.md b/数据验证短信告警使用说明.md new file mode 100644 index 0000000..bb68e8b --- /dev/null +++ b/数据验证短信告警使用说明.md @@ -0,0 +1,294 @@ +# 数据验证与短信告警系统 - 使用说明 + +## 📋 功能概述 + +自动执行数据验证（JSON/CSV/数据库），当验证失败时通过阿里云短信服务发送告警通知。 + +**核心功能：** +- ✅ 每天定时执行数据验证（默认上午9点） +- ✅ 验证失败自动发送短信告警（错误代码：2222） +- ✅ 支持多个手机号接收告警 +- ✅ 生成详细的验证报告 + +--- + +## 🚀 快速开始 + +### 1. 安装依赖 + +```bash +# 安装阿里云短信SDK +pip install alibabacloud_dysmsapi20170525 +pip install alibabacloud_credentials +pip install alibabacloud_tea_openapi +pip install alibabacloud_tea_util +``` + +### 2. 配置短信服务 + +编辑 `sms_config.json` 文件，填写您的阿里云配置： + +```json +{ + "access_key_id": "您的AccessKey ID", + "access_key_secret": "您的AccessKey Secret", + "sign_name": "您的短信签名", + "template_code": "SMS_486210104", + "phone_numbers": "13621242430,13800138000" +} +``` + +**获取方式：** +- AccessKey：https://ram.console.aliyun.com/manage/ak +- 短信签名和模板：https://dysms.console.aliyun.com/ + +### 3. 测试短信功能 + +```bash +# 测试短信发送 +python data_validation_with_sms.py --test-sms +``` + +### 4. 手动执行验证 + +```bash +# 验证昨天的数据 +python data_validation_with_sms.py + +# 验证指定日期 +python data_validation_with_sms.py --date 2025-12-29 + +# 验证特定表 +python data_validation_with_sms.py --table ai_statistics_day +``` + +### 5. 配置定时任务 + +**Windows系统：** + +```bash +# 查看任务计划配置命令 +python data_validation_with_sms.py --setup-schedule +``` + +然后使用管理员权限运行显示的PowerShell命令，或者手动配置： + +1. 打开 `任务计划程序` (按 Win+R，输入 `taskschd.msc`) +2. 点击 "创建基本任务" +3. 填写任务信息： + - **名称**: DataValidationWithSMS + - **描述**: 每天9点执行数据验证并发送短信告警 +4. 触发器：**每天**，时间：**上午 9:00** +5. 操作：**启动程序** + - 程序：`C:\Python\python.exe` (您的Python路径) + - 参数：`D:\workspace\xhh_baijiahao\data_validation_with_sms.py` +6. 完成 + +**Linux/macOS系统：** + +编辑crontab： +```bash +crontab -e +``` + +添加定时任务（每天9点执行）： +``` +0 9 * * * /usr/bin/python3 /path/to/data_validation_with_sms.py +``` + +--- + +## 📖 使用示例 + +### 示例1：验证JSON和CSV + +```bash +python data_validation_with_sms.py --source json csv +``` + +### 示例2：验证CSV和数据库 + +```bash +python data_validation_with_sms.py --source csv database +``` + +### 示例3：完整验证（三个数据源） + +```bash +python data_validation_with_sms.py --source json csv database +``` + +### 示例4：验证 ai_statistics_day 表 + +```bash +python data_validation_with_sms.py --table ai_statistics_day --source csv database +``` + +--- + +## 📧 短信告警说明 + +### 触发条件 + +以下情况会发送短信告警（错误代码：2222）： + +1. **顺序不一致**：JSON和CSV中记录的顺序不匹配 +2. **缺失记录**：某个数据源缺少记录 +3. **多余记录**：某个数据源有多余的记录 +4. **字段差异**：相同记录的字段值不一致 + +### 短信内容 + +短信格式（使用验证码模板）： +``` +【北京乐航时代科技】您的验证码是2222 +``` + +**说明**：由于使用的是验证码模板，错误代码固定为 `2222`，具体错误详情请查看生成的验证报告文件。 + +### 多号码配置 + +在 `sms_config.json` 中配置多个手机号： + +```json +{ + "phone_numbers": "13621242430,13800138000,13900139000" +} +``` + +--- + +## 📊 验证报告 + +每次验证后会自动生成详细报告，保存在项目根目录： + +``` +validation_report_20250104_090000.txt +``` + +报告内容包括： +- 顺序验证结果 +- 交叉验证结果 +- 数据差异统计 +- 详细的错误列表 + +--- + +## ⚙️ 配置说明 + +### SMSAlertConfig 类 + +在 `data_validation_with_sms.py` 中可以修改配置： + +```python +class SMSAlertConfig: + # 阿里云访问凭据 + ACCESS_KEY_ID = os.environ.get('ALIBABA_CLOUD_ACCESS_KEY_ID', '默认值') + ACCESS_KEY_SECRET = os.environ.get('ALIBABA_CLOUD_ACCESS_KEY_SECRET', '默认值') + + # 短信签名和模板 + SIGN_NAME = '北京乐航时代科技' + TEMPLATE_CODE = 'SMS_486210104' + + # 接收号码 + PHONE_NUMBERS = '13621242430' + + # endpoint + ENDPOINT = 'dysmsapi.aliyuncs.com' +``` + +### 环境变量方式（推荐） + +为了安全起见，建议使用环境变量存储敏感信息： + +**Windows PowerShell:** +```powershell +$env:ALIBABA_CLOUD_ACCESS_KEY_ID="您的AccessKey ID" +$env:ALIBABA_CLOUD_ACCESS_KEY_SECRET="您的AccessKey Secret" +``` + +**Linux/macOS:** +```bash +export ALIBABA_CLOUD_ACCESS_KEY_ID="您的AccessKey ID" +export ALIBABA_CLOUD_ACCESS_KEY_SECRET="您的AccessKey Secret" +``` + +--- + +## 🔍 故障排查 + +### 1. 短信发送失败 + +**检查项：** +- AccessKey ID 和 Secret 是否正确 +- 短信签名是否已审核通过 +- 短信模板是否已审核通过 +- 账户余额是否充足 +- 手机号格式是否正确（国内号码11位） + +**查看错误日志：** +```bash +python data_validation_with_sms.py --test-sms +``` + +### 2. 数据库连接失败 + +检查 `database_config.py` 中的配置是否正确。 + +### 3. 验证失败 + +查看生成的验证报告文件，了解详细错误信息。 + +### 4. 定时任务不执行 + +**Windows:** +- 检查任务计划程序中任务状态 +- 查看任务历史记录 +- 确认Python路径和脚本路径正确 + +**Linux/macOS:** +- 检查crontab配置：`crontab -l` +- 查看系统日志：`grep CRON /var/log/syslog` + +--- + +## 📝 日志位置 + +- 验证报告：`validation_report_*.txt` +- 短信发送日志：控制台输出 +- 系统日志：根据日志配置（如有） + +--- + +## 🔐 安全建议 + +1. **不要提交敏感信息到Git** + - 将 `sms_config.json` 添加到 `.gitignore` + - 使用环境变量存储AccessKey + +2. **定期轮换AccessKey** + - 建议每3-6个月更换一次 + +3. **使用RAM子账号** + - 为短信服务创建专用的RAM子账号 + - 仅授予必要的短信发送权限 + +4. **设置IP白名单** + - 在阿里云RAM控制台设置IP访问限制 + +--- + +## 📞 联系支持 + +如有问题，请联系技术支持。 + +--- + +## 📅 更新日志 + +### v1.0.0 (2025-01-04) +- ✨ 初始版本 +- ✅ 集成数据验证功能 +- ✅ 阿里云短信告警 +- ✅ 定时任务调度 +- ✅ 多数据源支持