在前后端开发联调前 的提交20260223
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docs/audit/prompt_logs/prompt_log_20260221_205154.md
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- [P20260221-205154] 2026-02-21 20:51:54 +0800
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- summary: CONTEXT TRANSFER: We are continuing a conversation that had gotten too long. Here is a summary: --- ## TASK 1: Execute D…
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- prompt:
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```text
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CONTEXT TRANSFER: We are continuing a conversation that had gotten too long. Here is a summary:
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---
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## TASK 1: Execute Dataflow Structure Analysis (Two Phases)
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**STATUS**: done
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**USER QUERIES**: 1 (initial request to run analyze_dataflow.py and gen_dataflow_report.py)
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**DETAILS**:
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- 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)
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- 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`
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- 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.
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- Code changes made to handle Windows file locks:
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- `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()`.
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- `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.
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- 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
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- Temporary script `scripts/ops/_clean_dataflow.py` was created and deleted.
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**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`
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## TASK 2: Investigate Two Missing Field Mappings
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**STATUS**: in-progress
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**USER QUERIES**: Last user message asking about `time_slot_sale` (store_goods_master) and `commoditycode` (tenant_goods_master)
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**DETAILS**:
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Database and DDL investigation completed. Results:
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1. **`time_slot_sale`** (store_goods_master, API→ODS unmapped):
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- ODS column: **does NOT exist** in `ods.store_goods_master` (confirmed by DB query and DDL grep — zero hits in any .sql file)
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- DWD column: does not exist
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- FACT_MAPPINGS: not present
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- The API returns `time_slot_sale` (example value: `2`) but it was never added to ODS DDL
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- `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"
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2. **`commoditycode`** (tenant_goods_master, ODS→DWD unmapped):
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- ODS column: **EXISTS** as `text` type in `ods.tenant_goods_master` (confirmed by DB query, DDL in `ods.sql` line 1479)
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- ODS sample values: `{10000028}`, `{10000002}`, etc. (curly-brace wrapped arrays)
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- DWD column: **does NOT exist** in any `dwd.*tenant_goods*` table
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- FACT_MAPPINGS: not present
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- `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_list(FACT_MAPPINGS 映射自 ODS commodity_code)覆盖该语义"
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- A one-off check script `scripts/ops/_check_two_fields.py` was created and still exists (should be cleaned up)
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- 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**
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**NEXT STEPS**:
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- Deliver the investigation findings to the user in a clear summary
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- Clean up `scripts/ops/_check_two_fields.py` (one-off script)
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- 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`)
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**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`
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## USER CORRECTIONS AND INSTRUCTIONS:
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- All output must go to `export/` directory structure via `.env` environment variables
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- Scripts run from `scripts/ops/` with cwd set to that directory
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- Database testing uses `TEST_DB_DSN` (test_etl_feiqiu), never production
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- All explanatory text in simplified Chinese
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- Python scripts preferred over PowerShell for complex operations
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- `scripts/ops/` scripts use `_env_paths.get_output_path()` for path resolution
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- The locked `field_mappings/` directory in `export/SYSTEM/REPORTS/dataflow_analysis/` should be manually deleted after system restart
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## Files to read
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- `scripts/ops/_check_two_fields.py`
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- `scripts/ops/gen_field_review_doc.py`
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- `db/etl_feiqiu/schemas/ods.sql`
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- `scripts/ops/dataflow_analyzer.py`
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- `scripts/ops/gen_dataflow_report.py`
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USER QUERIES(most recent first):
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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?
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2. Output:
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Command executed successfully with no output.
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Exit Code: 0
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3. Output:
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Command executed successfully with no output.
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Exit Code: 0
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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?
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5. <source-event>
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The user manually invoked this action
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The user is focued on the following file: docs/database/etl_feiqiu_schema_migration.md
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The user has the following paths open: docs/database/etl_feiqiu_schema_migration.md
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</source-event>
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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:
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第一阶段:数据采集
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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)
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2. 确认采集结果已落盘,包括:
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- json_trees/(含 samples 多示例值)
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- db_schemas/
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- field_mappings/(三层映射 + 锚点)
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- bd_descriptions/(BD_manual 业务描述)
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- collection_manifest.json(含 json_field_count、date_from、date_to)
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第二阶段:报告生成
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3. 运行 `python scripts/ops/gen_dataflow_report.py` 生成 Markdown 报告
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4. 报告包含以下增强内容:
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- 报告头含 API 请求日期范围(date_from ~ date_to)和 JSON 数据总量
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- 总览表含 API JSON 字段数列
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- 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)
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- 2.3 覆盖率表含业务描述列
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- API 源字段表含业务描述列 + 多示例值(枚举值解释)
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- ODS 表结构含业务描述列 + 上下游双向映射锚点链接
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- DWD 表结构含业务描述列 + ODS 来源锚点链接
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5. 输出文件路径和关键统计摘要
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白名单规则(v4):
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- ETL 元数据列(source_file, source_endpoint, fetched_at, payload, content_hash)
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- DWD 维表 SCD2 管理列(valid_from, valid_to, is_current, etl_loaded_at, etl_batch_id)
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- API siteProfile 嵌套对象字段
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- 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
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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。
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6. <implicit-rules>## Implicit Rules
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Focus on creating a new spec file or identifying an existing spec to update.
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If starting a new spec, create a requirements.md file in the .kiro/specs directory with clear user stories and acceptance criteria.
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If working with an existing spec, review the current requirements and suggest improvements if needed.
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Do not make direct code changes yet. First establish or review the spec file that will guide our implementation.</implicit-rules>
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---
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METADATA:
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The previous conversation had 4 messages.
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INSTRUCTIONS:
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Continue working until the user query has been fully addressed. Do not ask for clarification - proceed with the work based on the context provided.
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IMPORTANT: you need to read from the files to Read section
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```
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