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Neo-ZQYY/docs/audit/prompt_logs/prompt_log_20260221_205154.md

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  • [P20260221-205154] 2026-02-21 20:51:54 +0800
    • summary: CONTEXT TRANSFER: We are continuing a conversation that had gotten too long. Here is a summary: --- ## TASK 1: Execute D…
    • prompt:
CONTEXT TRANSFER: We are continuing a conversation that had gotten too long. Here is a summary:

---
## TASK 1: Execute Dataflow Structure Analysis (Two Phases)

**STATUS**: done
**USER QUERIES**: 1 (initial request to run analyze_dataflow.py and gen_dataflow_report.py)
**DETAILS**:
- Phase 1 (Data Collection): Ran `python scripts/ops/analyze_dataflow.py` — collected 22 ODS tables, 3388 records, date range 2025-11-23 ~ 2026-02-21 (adaptive expansion: 10→30→90 days)
- Phase 2 (Report Generation): Ran `python scripts/ops/gen_dataflow_report.py` — generated 526.1 KB Markdown report at `export/SYSTEM/REPORTS/dataflow_analysis/dataflow_2026-02-21_154548.md`
- Major blocker: Windows file lock on `field_mappings/` directory (from previous run). Could not delete/rename/iterate. Fixed by adding fallback logic to use `field_mappings_new/` directory when original is locked.
- Code changes made to handle Windows file locks:
  - `scripts/ops/dataflow_analyzer.py`: Added `_ensure_writable_dir()` helper in `dump_collection_results()` that tries original dir, falls back to `{name}_new/`. Also added retry logic in `_write_json()`.
  - `scripts/ops/gen_dataflow_report.py`: Added `_fm_dir` variable at top of `generate_report()` that detects `field_mappings_new/` and uses it. Updated `_write_field_diff_report()` and `_write_source_file_manifest()` to accept `fm_dir` parameter.
- Output directory structure: `export/SYSTEM/REPORTS/dataflow_analysis/` contains: json_trees/, db_schemas/, field_mappings_new/ (actual data), field_mappings/ (locked empty dir), bd_descriptions/, collection_manifest.json
- Temporary script `scripts/ops/_clean_dataflow.py` was created and deleted.
**FILEPATHS**: `scripts/ops/analyze_dataflow.py`, `scripts/ops/gen_dataflow_report.py`, `scripts/ops/dataflow_analyzer.py`, `export/SYSTEM/REPORTS/dataflow_analysis/collection_manifest.json`

## TASK 2: Investigate Two Missing Field Mappings

**STATUS**: in-progress
**USER QUERIES**: Last user message asking about `time_slot_sale` (store_goods_master) and `commoditycode` (tenant_goods_master)
**DETAILS**:
Database and DDL investigation completed. Results:

1. **`time_slot_sale`** (store_goods_master, API→ODS unmapped):
   - ODS column: **does NOT exist** in `ods.store_goods_master` (confirmed by DB query and DDL grep — zero hits in any .sql file)
   - DWD column: does not exist
   - FACT_MAPPINGS: not present
   - The API returns `time_slot_sale` (example value: `2`) but it was never added to ODS DDL
   - `scripts/ops/gen_field_review_doc.py` line ~908 explicitly lists it as skipped: "ODS 列不存在。需确认 API 是否返回该字段,如有则需先更新 ODS DDL"

2. **`commoditycode`** (tenant_goods_master, ODS→DWD unmapped):
   - ODS column: **EXISTS** as `text` type in `ods.tenant_goods_master` (confirmed by DB query, DDL in `ods.sql` line 1479)
   - ODS sample values: `{10000028}`, `{10000002}`, etc. (curly-brace wrapped arrays)
   - DWD column: **does NOT exist** in any `dwd.*tenant_goods*` table
   - FACT_MAPPINGS: not present
   - `scripts/ops/gen_field_review_doc.py` line ~634 explicitly lists it as skipped: "冗余字段。DWD 已有 commodity_code自动映射+ commodity_code_listFACT_MAPPINGS 映射自 ODS commodity_code覆盖该语义"

- A one-off check script `scripts/ops/_check_two_fields.py` was created and still exists (should be cleaned up)
- The user asked "这两个字段的确不存在么之前没有被DDL加入么" — the investigation results were gathered but **no response was delivered to the user yet**

**NEXT STEPS**:
- Deliver the investigation findings to the user in a clear summary
- Clean up `scripts/ops/_check_two_fields.py` (one-off script)
- If user wants to add these fields: `time_slot_sale` needs ODS DDL + DWD DDL + FACT_MAPPINGS; `commoditycode` is intentionally skipped as redundant (already covered by `commodity_code` + `commodity_code_list`)

**FILEPATHS**: `scripts/ops/_check_two_fields.py`, `db/etl_feiqiu/schemas/ods.sql`, `scripts/ops/gen_field_review_doc.py`, `scripts/ops/export_dwd_field_review.py`

## USER CORRECTIONS AND INSTRUCTIONS:
- All output must go to `export/` directory structure via `.env` environment variables
- Scripts run from `scripts/ops/` with cwd set to that directory
- Database testing uses `TEST_DB_DSN` (test_etl_feiqiu), never production
- All explanatory text in simplified Chinese
- Python scripts preferred over PowerShell for complex operations
- `scripts/ops/` scripts use `_env_paths.get_output_path()` for path resolution
- The locked `field_mappings/` directory in `export/SYSTEM/REPORTS/dataflow_analysis/` should be manually deleted after system restart

## Files to read
- `scripts/ops/_check_two_fields.py`
- `scripts/ops/gen_field_review_doc.py`
- `db/etl_feiqiu/schemas/ods.sql`
- `scripts/ops/dataflow_analyzer.py`
- `scripts/ops/gen_dataflow_report.py`

USER QUERIES(most recent first):
1. 1.1.20 store_goods_master 字段差异明细API→ODS 未映射(平层) — 1 个#	JSON 字段	示例值	说明	状态1	time_slot_sale	2		⚠️ 未映射1.1.22 tenant_goods_master 字段差异明细ODS→DWD 未映射 — 1 个#	ODS 列	说明	状态1	commoditycode	(待补充)	⚠️ 无 DWD 目标这两个字段的确不存在么之前没有被DDL加入么
2. Output:
Command executed successfully with no output.

Exit Code: 0
3. Output:
Command executed successfully with no output.

Exit Code: 0
4. 1.1.20 store_goods_master 字段差异明细API→ODS 未映射(平层) — 1 个#	JSON 字段	示例值	说明	状态1	time_slot_sale	2		⚠️ 未映射1.1.22 tenant_goods_master 字段差异明细ODS→DWD 未映射 — 1 个#	ODS 列	说明	状态1	commoditycode	(待补充)	⚠️ 无 DWD 目标这两个字段的确不存在么之前没有被DDL加入么
5. <source-event>
    The user manually invoked this action
    The user is focued on the following file: docs/database/etl_feiqiu_schema_migration.md
    The user has the following paths open: docs/database/etl_feiqiu_schema_migration.md
</source-event>

执行数据流结构分析,按以下步骤完成。若发现已完成或有历史任务痕迹则清空,重新执行:

第一阶段:数据采集
1. 运行 `python scripts/ops/analyze_dataflow.py` 完成数据采集(如需指定日期范围,加 --date-from / --date-to 参数)
2. 确认采集结果已落盘,包括:
   - json_trees/(含 samples 多示例值)
   - db_schemas/
   - field_mappings/(三层映射 + 锚点)
   - bd_descriptions/BD_manual 业务描述)
   - collection_manifest.json含 json_field_count、date_from、date_to

第二阶段:报告生成
3. 运行 `python scripts/ops/gen_dataflow_report.py` 生成 Markdown 报告
4. 报告包含以下增强内容:
   - 报告头含 API 请求日期范围date_from ~ date_to和 JSON 数据总量
   - 总览表含 API JSON 字段数列
   - 1.1 API↔ODS↔DWD 字段对比差异报告(白名单字段折叠汇总,不展开详细表格行)
   - 2.3 覆盖率表含业务描述列
   - API 源字段表含业务描述列 + 多示例值(枚举值解释)
   - ODS 表结构含业务描述列 + 上下游双向映射锚点链接
   - DWD 表结构含业务描述列 + ODS 来源锚点链接
5. 输出文件路径和关键统计摘要

白名单规则v4
- ETL 元数据列source_file, source_endpoint, fetched_at, payload, content_hash
- DWD 维表 SCD2 管理列valid_from, valid_to, is_current, etl_loaded_at, etl_batch_id
- API siteProfile 嵌套对象字段
- 白名单字段仍正常参与检查和统计,仅在报告中折叠显示并注明原因

注意当前仅分析飞球feiqiu连接器。未来新增连接器时应自动发现并纳入分析范围。
6. <implicit-rules>## Implicit Rules
Focus on creating a new spec file or identifying an existing spec to update. 
If starting a new spec, create a requirements.md file in the .kiro/specs directory with clear user stories and acceptance criteria. 
If working with an existing spec, review the current requirements and suggest improvements if needed. 
Do not make direct code changes yet. First establish or review the spec file that will guide our implementation.</implicit-rules>
---

METADATA:
The previous conversation had 4 messages.

INSTRUCTIONS:
Continue working until the user query has been fully addressed. Do not ask for clarification - proceed with the work based on the context provided.
IMPORTANT: you need to read from the files to Read section