2026-04-29 18:52:49 +08:00
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# Inventory Analytics
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Inventory Analytics 是一个内部库存数据处理项目，围绕委外批次库存上传、渠道库存统计同步、批次库存统计报表三条业务链路运行。项目从 Raw PostgreSQL、Analytics PostgreSQL 和飞书多维表格之间同步与汇总库存数据，并支持本地执行、Docker 部署和 Prefect 定时调度。
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## 项目目标
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- 上传委外批次库存文件，并写入 Raw 数据库。
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- 从 Analytics 数据库读取渠道库存、锁定库存、销售和商品信息。
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- 生成批次库存统计数据，可输出本地报表，也可同步到飞书多维表格。
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- 通过 Prefect 每天定时执行渠道库存统计和批次库存统计同步。
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- 统一日志输出，保留关键节点与异常信息，同时避免输出数据库、飞书等敏感配置。
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## 核心链路
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### 1. 委外批次库存上传
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入口：
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```bash
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python3 scripts/upload_batch_inventory.py
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```
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功能：
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- 启动本地上传页面。
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- 支持 Excel 和 CSV 文件上传。
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- 保存原始文件到 `batch_inventory_data/`。
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- 将解析后的每一行写入 Raw PostgreSQL 的 `raw_data.wangdian_batch_inventory`。
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兼容入口：
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```bash
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python3 upload_inventory_page.py
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```
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### 2. 渠道库存统计同步飞书
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入口：
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```bash
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python3 scripts/sync_channel_inventory.py
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```
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功能：
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- 读取飞书 Base 与目标表信息。
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- 查询 Analytics PostgreSQL 中的渠道库存数据。
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- 按目标品牌和飞书字段配置整理数据。
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- 清空并重写飞书目标表记录。
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可选动作：
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```bash
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python3 scripts/sync_channel_inventory.py --action feishu
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python3 scripts/sync_channel_inventory.py --action postgres
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python3 scripts/sync_channel_inventory.py --action sync-brand
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python3 scripts/sync_channel_inventory.py --action all
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```
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兼容入口：
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```bash
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python3 sync_channel_inventory.py --action all
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python3 list_feishu_base_tables.py --action all
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```
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### 3. 批次库存统计报表
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入口：
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```bash
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python3 scripts/generate_batch_inventory_report.py
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```
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功能：
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- 读取 Raw 数据库中最新的委外批次库存。
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- 查询 Analytics 数据库中的店铺库存、锁定库存、商品信息和近 30 天销售数量。
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- 按批次维度汇总库存数据。
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- 计算保质期、距离到期天数、效期比例等字段。
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- 可输出本地 Excel/CSV 报表。
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- 可同步到飞书 `批次库存` 表。
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常用参数：
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```bash
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python3 scripts/generate_batch_inventory_report.py --skip-feishu-sync
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python3 scripts/generate_batch_inventory_report.py --skip-report-output
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python3 scripts/generate_batch_inventory_report.py --output reports/custom.xlsx
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python3 scripts/generate_batch_inventory_report.py --feishu-table 批次库存
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```
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兼容入口：
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```bash
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python3 generate_batch_inventory_report.py
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python3 generate_yxt_batch_inventory_report.py
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```
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## 目录结构
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```text
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├── inventory_analytics/ # 当前主包
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│ ├── config.py # 配置加载
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│ ├── logging_utils.py # 日志与脱敏
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│ ├── paths.py # 项目路径
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│ ├── batch_upload/ # 委外批次库存上传
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│ ├── batch_inventory_report/ # 批次库存统计报表
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│ ├── channel_inventory_sync/ # 渠道库存同步入口封装
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│ ├── db/ # 数据库相关扩展位置
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│ └── feishu/ # 飞书客户端封装
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├── inventory_sync/ # 渠道库存同步历史实现，当前仍在复用
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├── scripts/ # 推荐命令入口
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├── batch_inventory_data/ # 上传原始文件归档目录
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├── logs/ # 日志目录
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├── reports/ # 本地报表输出目录
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├── Dockerfile
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├── docker-compose.yaml
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├── prefect.yaml
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├── prefect_inventory_scheduler.py # Prefect flow 定义与本地触发入口
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└── PROJECT_GUIDE.md # 更详细的维护说明
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```
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## 配置
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项目通过 `.env` 或当前 Shell 环境变量读取配置。主要配置项如下：
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Raw 数据库：
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```text
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RAW_DB_HOST
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RAW_DB_PORT
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RAW_DB_USER
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RAW_DB_PASSWORD
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RAW_DB_NAME
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```
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Analytics 数据库：
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```text
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ANALYTICS_DB_HOST
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ANALYTICS_DB_PORT
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ANALYTICS_DB_USER
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ANALYTICS_DB_PASSWORD
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ANALYTICS_DB_NAME
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```
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飞书：
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```text
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FEISHU_APP_ID
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FEISHU_APP_SECRET
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FEISHU_BASE_URL
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FEISHU_APP_TOKEN
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```
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Prefect：
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```text
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PREFECT_API_URL
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```
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说明：
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- `.env` 不应提交到版本库。
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- 日志默认不会输出数据库连接信息、飞书 app token、飞书 base URL、表 ID、密码或密钥。
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- `FEISHU_APP_TOKEN` 可选；当 `FEISHU_BASE_URL` 已包含 `/base/` 或 `/wiki/` 时，可以不单独配置。
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## Prefect 调度
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项目定义了两个 Prefect deployment：
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2026-05-11 16:56:27 +08:00
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- `channel-inventory-sync-0915-1915`：每天 09:15 和 19:15 执行渠道库存统计并写入飞书。
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- `batch-inventory-report-0915-1915`：每天 09:15 和 19:15 执行批次库存统计并写入飞书。
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2026-04-29 18:52:49 +08:00
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注册 deployment：
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```bash
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sh scripts/register_prefect_deployments.sh
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```
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该脚本会进入 Docker 容器内，按 deployment 名称分别注册：
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```bash
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2026-05-11 16:56:27 +08:00
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docker compose exec -T prefect-inventory-worker prefect --no-prompt deploy --name channel-inventory-sync-0915-1915
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docker compose exec -T prefect-inventory-worker prefect --no-prompt deploy --name batch-inventory-report-0915-1915
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2026-04-29 18:52:49 +08:00
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```
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启动 Docker worker：
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```bash
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docker compose up -d --build
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```
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手动触发：
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```bash
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python3 prefect_inventory_scheduler.py --run-channel-inventory-sync
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python3 prefect_inventory_scheduler.py --run-batch-inventory-report
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```
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本地 serve：
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```bash
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python3 prefect_inventory_scheduler.py --serve-channel-inventory-sync
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python3 prefect_inventory_scheduler.py --serve-batch-inventory-report
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```
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Prefect 调度下，批次库存统计默认不生成本地 `reports/` 文件，只同步飞书。如需同时生成本地报表，可使用：
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```bash
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python3 prefect_inventory_scheduler.py --run-batch-inventory-report --write-report-output
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```
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## 日志策略
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日志采用结构化事件格式：
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```text
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YYYY-MM-DD HH:MM:SS LEVEL logger_name 事件=事件名称 字段=字段值
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```
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正常执行会输出关键节点：
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- 任务启动与完成
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- 配置加载完成
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- 数据库查询开始与完成
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- 数据整理与汇总完成
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- 飞书访问令牌获取
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- 飞书表读取
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- 飞书记录删除与新增数量
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- 本地报表是否输出
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- 总耗时
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异常情况会输出：
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- 失败阶段
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- 异常类型
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- 脱敏后的错误信息
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- 已执行耗时
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日志不会输出：
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- 数据库 host、port、user、password、database name
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- 飞书 app id、app secret、app token、base URL
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- 飞书 table id、field id、record id
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- `.env` 完整路径
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- 含 token 的 URL
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主要日志文件：
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```text
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logs/upload_inventory_page.log
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logs/sync_channel_inventory.log
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logs/generate_batch_inventory_report.log
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```
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## 开发与验证
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安装依赖：
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```bash
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pip install -e .
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```
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语法检查：
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```bash
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PYTHONPYCACHEPREFIX=/tmp/inventory_analytics_pycache python3 -m compileall inventory_analytics inventory_sync scripts prefect_inventory_scheduler.py
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```
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验证上传页：
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```bash
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python3 scripts/upload_batch_inventory.py
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```
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验证渠道库存飞书连接：
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```bash
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python3 scripts/sync_channel_inventory.py --action feishu
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```
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验证批次库存本地报表：
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```bash
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python3 scripts/generate_batch_inventory_report.py --skip-feishu-sync
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```
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## 维护约定
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- 新增业务代码优先放入 `inventory_analytics/`。
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- 新命令优先放入 `scripts/`，根目录脚本只作为兼容入口。
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- 公共配置、路径和日志逻辑统一使用 `config.py`、`paths.py`、`logging_utils.py`。
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- 当前渠道库存同步仍复用 `inventory_sync/`，后续可逐步迁移到 `inventory_analytics/channel_inventory_sync/`。
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- 涉及日志输出时，默认只记录业务状态和计数，不记录连接配置、密钥、Token 或内部资源 ID。
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