在准备环境前提交次全部更改。

scripts/ops/gen_dataflow_report.py

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+"""
+数据流结构分析报告生成器（v3）
+
+读取 analyze_dataflow.py 采集的数据，生成带锚点链接、上下游映射列、
+业务描述、多示例值、字段差异报告的 Markdown 报告。
+
+增强内容（v3）：
+- 总览表增加 API JSON 字段数列
+- 覆盖率表增加业务描述列
+- 逐表详情增加业务描述列（来自 BD_manual 文档）
+- 说明+示例值合并，多示例展示，枚举值解释
+- 总览章节增加 API↔ODS↔DWD 字段对比差异报告
+
+用法:
+    python scripts/ops/gen_dataflow_report.py
+    python scripts/ops/gen_dataflow_report.py --output-dir export/dataflow_analysis
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import os
+from datetime import datetime
+from pathlib import Path
+
+from dotenv import load_dotenv
+
+
+def load_json(path: Path) -> dict | list | None:
+    if not path.exists():
+        return None
+    with open(path, "r", encoding="utf-8") as f:
+        return json.load(f)
+
+
+def build_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(description="生成数据流结构分析 Markdown 报告")
+    parser.add_argument("--output-dir", type=str, default=None,
+                        help="输出目录（默认读取 SYSTEM_ANALYZE_ROOT 或 export/dataflow_analysis）")
+    return parser
+
+
+def resolve_data_dir(override: str | None = None) -> Path:
+    if override:
+        return Path(override)
+    env_root = os.environ.get("SYSTEM_ANALYZE_ROOT")
+    if env_root:
+        return Path(env_root)
+    return Path("export/dataflow_analysis")
+
+
+def _esc(s: str) -> str:
+    """转义 Markdown 表格中的管道符"""
+    return str(s).replace("|", "\\|").replace("\n", " ") if s else ""
+
+
+# ── 字段用途推测规则 ──
+# 基于字段名模式 + 表名上下文推断字段可能的业务含义
+# 置信度：高(≥80%) / 中(50-79%) / 低(<50%)
+import re as _re
+
+_FIELD_GUESS_RULES: list[tuple[str, str, str]] = [
+    # (字段名模式正则, 推测用途, 置信度)
+    # ── SCD2 / ETL 元数据 ──
+    (r"^scd2_", "SCD2 缓慢变化维度元数据", "高"),
+    (r"^etl_", "ETL 流程元数据", "高"),
+    (r"^dw_insert", "数仓装载时间戳", "高"),
+    (r"^content_hash$", "数据变更检测哈希", "高"),
+    (r"^source_file$", "ETL 来源文件标识", "高"),
+    (r"^source_endpoint$", "ETL 来源接口标识", "高"),
+    (r"^fetched_at$", "ETL 抓取时间", "高"),
+    (r"^payload$", "原始 JSON 全量存储", "高"),
+    # ── 主键 / 外键 ──
+    (r"^id$", "主键标识", "高"),
+    # ── 门店 / 组织（放在通用 _id$ 之前） ──
+    (r"^(site_id|shop_id|store_id)$", "门店标识", "高"),
+    (r"^(tenant_id|org_id)$", "租户/组织标识", "高"),
+    (r"(shop_name|site_name|store_name)", "门店名称", "高"),
+    # ── 时间类 ──
+    (r"(^|_)(create|created)(_at|_time|_date)$", "记录创建时间", "高"),
+    (r"(^|_)(update|updated|modify)(_at|_time|_date)$", "记录更新时间", "高"),
+    (r"(^|_)(delete|deleted)(_at|_time|_date)$", "逻辑删除时间", "高"),
+    (r"(^|_)(start|begin)(_at|_time|_date)$", "起始时间", "中"),
+    (r"(^|_)(end|expire)(_at|_time|_date)$", "结束/过期时间", "中"),
+    (r"(^|_)entry_time$", "入职/入场时间", "中"),
+    (r"(^|_)resign_time$", "离职时间", "中"),
+    (r"_time$", "时间戳字段", "中"),
+    (r"_date$", "日期字段", "中"),
+    # ── 通用派生（放在标志位之前，确保 derived_flag 等优先匹配派生） ──
+    (r"^derived_", "ETL 派生计算列", "高"),
+    (r"^calc_", "计算字段", "中"),
+    # ── 状态 / 标志 ──
+    (r"(^|_)is_delete$", "逻辑删除标志", "高"),
+    (r"^is_", "布尔标志位", "中"),
+    (r"(^|_)status$", "状态码", "中"),
+    (r"_status$", "状态字段", "中"),
+    (r"_enabled$", "启用/禁用开关", "中"),
+    (r"_flag$", "标志位", "中"),
+    # ── 金额 / 价格 ──
+    (r"(price|amount|fee|cost|money|balance|total)", "金额/价格相关", "中"),
+    (r"(discount|coupon|refund)", "优惠/退款相关", "中"),
+    # ── 人员 ──
+    (r"(real_name|nickname|^name$)", "姓名/昵称", "中"),
+    (r"(mobile|phone|tel)", "联系电话", "中"),
+    (r"(avatar|photo|image)", "头像/图片 URL", "中"),
+    (r"(gender|sex)", "性别", "高"),
+    (r"(birth|birthday)", "出生日期", "高"),
+    (r"(height|weight)", "身高/体重", "高"),
+    # ── 嵌套对象常见前缀 ──
+    (r"^siteProfile\.", "门店档案嵌套属性", "高"),
+    (r"^memberInfo\.", "会员信息嵌套属性", "中"),
+    (r"^assistantInfo\.", "助教信息嵌套属性", "中"),
+    (r"^tableInfo\.", "台桌信息嵌套属性", "中"),
+    (r"^orderInfo\.", "订单信息嵌套属性", "中"),
+    (r"^payInfo\.", "支付信息嵌套属性", "中"),
+    # ── 排序 / 显示 ──
+    (r"(sort|order|rank|seq)", "排序/序号", "低"),
+    (r"(remark|memo|note|comment|introduce)", "备注/说明文本", "中"),
+    (r"(url|link|qrcode|qr_code)", "链接/二维码", "中"),
+    # ── 通用 ID 后缀（放在具体 ID 规则之后） ──
+    (r"_id$", "关联实体 ID（外键）", "中"),
+]
+
+
+def _guess_field_purpose(field_name: str, table_name: str, layer: str) -> tuple[str, str]:
+    """根据字段名和表上下文推测用途，返回 (推测用途, 置信度)。"""
+    fn_lower = field_name.lower()
+    for pattern, purpose, confidence in _FIELD_GUESS_RULES:
+        if _re.search(pattern, fn_lower):
+            return purpose, confidence
+    return f"待分析（{layer}层字段）", "低"
+
+
+def _format_samples(samples: list[str], max_show: int = 5) -> str:
+    """格式化多示例值，截断过长的值"""
+    if not samples:
+        return ""
+    shown = []
+    for s in samples[:max_show]:
+        s = _esc(s)
+        if len(s) > 30:
+            s = s[:27] + "..."
+        shown.append(f"`{s}`")
+    result = ", ".join(shown)
+    if len(samples) > max_show:
+        result += f" …共{len(samples)}种"
+    return result
+
+
+def _is_enum_like(samples: list[str], total_records: int) -> bool:
+    """判断字段是否像枚举（不同值少且记录数足够多）"""
+    if total_records < 5:
+        return False
+    return 1 < len(samples) <= 8
+
+
+def generate_report(data_dir: Path) -> str:
+    """生成完整的 Markdown 报告"""
+    manifest = load_json(data_dir / "collection_manifest.json")
+    if not manifest:
+        raise FileNotFoundError(f"找不到 collection_manifest.json: {data_dir}")
+
+    tables = manifest["tables"]
+    now = datetime.now()
+    lines: list[str] = []
+
+    def w(s: str = ""):
+        lines.append(s)
+
+    # ── 报告头 ──
+    w("# 飞球连接器 — 数据流结构分析报告")
+    w()
+    w(f"> 生成时间：{now.strftime('%Y-%m-%d %H:%M:%S')} CST")
+    w(f"> 分析范围：飞球（feiqiu）连接器，共 {len(tables)} 张 ODS 表")
+    w("> 数据来源：API JSON 采样 + PostgreSQL ODS/DWD 表结构 + 三层字段映射 + BD_manual 业务文档")
+    w()
+
+    # ── 1. 总览表（增加 API JSON 字段数列） ──
+    w("## 1. 总览")
+    w()
+    w("| # | ODS 表名 | 业务描述 | 采样记录数 | API JSON 字段数 | ODS 列数 | DWD 目标表 | DWD 总列数 |")
+    w("|---|---------|---------|-----------|---------------|---------|-----------|-----------|")
+    total_records = 0
+    total_ods_cols = 0
+    total_dwd_cols = 0
+    total_json_fields = 0
+    for i, t in enumerate(tables, 1):
+        dwd_names = ", ".join(t["dwd_tables"]) if t["dwd_tables"] else "—"
+        json_fc = t.get("json_field_count", 0)
+        w(f"| {i} | `{t['table']}` | {t['description']} | {t['record_count']} | {json_fc} | {t['ods_column_count']} | {dwd_names} | {t['dwd_column_count']} |")
+        total_records += t["record_count"]
+        total_ods_cols += t["ods_column_count"]
+        total_dwd_cols += t["dwd_column_count"]
+        total_json_fields += json_fc
+    w(f"| | **合计** | | **{total_records}** | **{total_json_fields}** | **{total_ods_cols}** | | **{total_dwd_cols}** |")
+    w()
+
+    # ── 1.1 字段对比差异报告 ──
+    _write_field_diff_report(w, data_dir, tables)
+
+    # ── 2. 全局统计 ──
+    w("## 2. 全局统计")
+    w()
+
+    # 2.1 JSON→ODS 映射覆盖
+    total_json = 0
+    total_mapped = 0
+    per_table_stats: list[dict] = []
+    for t in tables:
+        fm = load_json(data_dir / "field_mappings" / f"{t['table']}.json")
+        if not fm or "json_to_ods" not in fm:
+            per_table_stats.append({
+                "table": t["table"], "description": t["description"],
+                "json_count": 0, "mapped": 0, "unmapped": 0, "pct": "—",
+            })
+            continue
+        j2o = fm["json_to_ods"]
+        json_count = len(j2o)
+        mapped = sum(1 for m in j2o if m.get("ods_col") is not None)
+        unmapped = json_count - mapped
+        pct = f"{mapped / json_count * 100:.1f}%" if json_count > 0 else "—"
+        per_table_stats.append({
+            "table": t["table"], "description": t["description"],
+            "json_count": json_count, "mapped": mapped, "unmapped": unmapped, "pct": pct,
+        })
+        total_json += json_count
+        total_mapped += mapped
+
+    total_unmapped = total_json - total_mapped
+    w("### 2.1 JSON→ODS 映射覆盖")
+    w()
+    w(f"- JSON 字段总数：{total_json}")
+    if total_json > 0:
+        w(f"- 已映射到 ODS 列：{total_mapped}（{total_mapped / total_json * 100:.1f}%）")
+        w(f"- 仅存于 payload：{total_unmapped}（{total_unmapped / total_json * 100:.1f}%）")
+    else:
+        w("- 已映射到 ODS 列：0")
+        w("- 仅存于 payload：0")
+    w()
+
+    # 2.2 ODS→DWD 映射覆盖
+    w("### 2.2 ODS→DWD 映射覆盖")
+    w()
+    w(f"- DWD 列总数：{total_dwd_cols}")
+    w()
+
+    # 2.3 各表覆盖率（增加业务描述列）
+    w("### 2.3 各表 JSON→ODS 映射覆盖率")
+    w()
+    w("| ODS 表名 | 业务描述 | JSON 字段数 | 已映射 | 仅 payload | 覆盖率 |")
+    w("|---------|---------|-----------|-------|-----------|-------|")
+    sorted_stats = sorted(per_table_stats, key=lambda x: (0 if x["pct"] == "—" else -float(x["pct"].rstrip("%"))))
+    for s in sorted_stats:
+        w(f"| `{s['table']}` | {s['description']} | {s['json_count']} | {s['mapped']} | {s['unmapped']} | {s['pct']} |")
+    w()
+
+    # ── 3. 逐表详情 ──
+    w("## 3. 逐表详情")
+    w()
+
+    for idx, t in enumerate(tables, 1):
+        table_name = t["table"]
+        fm = load_json(data_dir / "field_mappings" / f"{table_name}.json")
+        jt = load_json(data_dir / "json_trees" / f"{table_name}.json")
+        ods_schema = load_json(data_dir / "db_schemas" / f"ods_{table_name}.json")
+        bd = load_json(data_dir / "bd_descriptions" / f"{table_name}.json")
+
+        # 锚点 ID
+        anchors = fm.get("anchors", {}) if fm else {}
+        api_anchor = anchors.get("api", f"api-{table_name}")
+        ods_anchor = anchors.get("ods", f"ods-{table_name}")
+        dwd_anchors = anchors.get("dwd", {})
+
+        dwd_tables_list = t.get("dwd_tables", [])
+        json_fc = t.get("json_field_count", 0)
+
+        w(f"### 3.{idx} {table_name}（{t['description']}）")
+        w()
+        w(f"- 任务代码：`{t['task_code']}`")
+        w(f"- 采样记录数：{t['record_count']}")
+        w(f"- API JSON 字段数：{json_fc}")
+        w(f"- ODS 列数：{t['ods_column_count']}")
+        if dwd_tables_list:
+            w(f"- DWD 目标表：{', '.join(dwd_tables_list)}")
+        else:
+            w("- DWD 目标表：—（仅 ODS 落地）")
+        w()
+
+        # ── API 源字段区块 ──
+        _write_api_section(w, fm, jt, bd, table_name, api_anchor, ods_anchor)
+
+        # ── ODS 表结构区块 ──
+        _write_ods_section(w, fm, ods_schema, bd, table_name, ods_anchor, api_anchor, dwd_anchors)
+
+        # ── DWD 表结构区块 ──
+        for dwd_name in dwd_tables_list:
+            dwd_anchor = dwd_anchors.get(dwd_name, f"dwd-{dwd_name}")
+            dwd_schema = load_json(data_dir / "db_schemas" / f"dwd_{dwd_name}.json")
+            _write_dwd_section(w, fm, dwd_schema, bd, dwd_name, dwd_anchor, ods_anchor, table_name)
+
+    return "\n".join(lines)
+
+
+
+def _write_field_diff_report(w, data_dir: Path, tables: list[dict]):
+    """生成 API↔ODS↔DWD 字段对比差异报告（汇总表 + 逐表分表）"""
+    w("### 1.1 API↔ODS↔DWD 字段对比差异")
+    w()
+    w("以下汇总各表在三层之间的字段差异（点击数字跳转至分表详情）：")
+    w()
+    w("| ODS 表名 | API→ODS 未映射 | ODS 无 JSON 源 | ODS→DWD 未映射 | DWD 无 ODS 源 | 主要差异原因 |")
+    w("|---------|--------------|--------------|--------------|-------------|------------|")
+
+    # 收集每表差异数据，用于汇总表和分表
+    etl_meta_cols = {"source_file", "source_endpoint", "fetched_at", "payload", "content_hash"}
+    diff_rows: list[dict] = []
+
+    for t in tables:
+        table_name = t["table"]
+        fm = load_json(data_dir / "field_mappings" / f"{table_name}.json")
+        if not fm:
+            w(f"| `{table_name}` | — | — | — | — | 无映射数据 |")
+            diff_rows.append(None)
+            continue
+
+        anchors = fm.get("anchors", {})
+        api_anchor = anchors.get("api", f"api-{table_name.replace('_', '-')}")
+        ods_anchor = anchors.get("ods", f"ods-{table_name.replace('_', '-')}")
+        dwd_anchors = anchors.get("dwd", {})
+        diff_anchor = f"diff-{table_name.replace('_', '-')}"
+
+        j2o = fm.get("json_to_ods", [])
+        o2d = fm.get("ods_to_dwd", {})
+        d2o = fm.get("dwd_to_ods", {})
+
+        # ── API→ODS 未映射字段 ──
+        api_unmapped_flat: list[str] = []
+        api_unmapped_nested: list[str] = []
+        for m in j2o:
+            if m.get("ods_col") is None:
+                jp = m.get("json_path", "")
+                if "." in jp:
+                    api_unmapped_nested.append(jp)
+                else:
+                    api_unmapped_flat.append(jp)
+        api_unmapped_total = len(api_unmapped_flat) + len(api_unmapped_nested)
+
+        # ── ODS 无 JSON 源 ──
+        ods_schema = load_json(data_dir / "db_schemas" / f"ods_{table_name}.json")
+        ods_mapped_cols = {m["ods_col"] for m in j2o if m.get("ods_col")}
+        ods_no_json_fields: list[str] = []
+        if ods_schema and "columns" in ods_schema:
+            for col in ods_schema["columns"]:
+                if col["name"] not in ods_mapped_cols and col["name"] not in etl_meta_cols:
+                    ods_no_json_fields.append(col["name"])
+
+        # ── ODS→DWD 未映射 ──
+        ods_cols_with_dwd = set(o2d.keys())
+        ods_no_dwd_fields: list[str] = []
+        if ods_schema and "columns" in ods_schema:
+            for col in ods_schema["columns"]:
+                if col["name"] not in ods_cols_with_dwd and col["name"] not in etl_meta_cols:
+                    ods_no_dwd_fields.append(col["name"])
+
+        # ── DWD 无 ODS 源 ──
+        dwd_no_ods_fields: list[tuple[str, str]] = []  # (dwd_table, dwd_col)
+        for dwd_name, entries in d2o.items():
+            for entry in entries:
+                if entry.get("ods_source") == "—":
+                    dwd_no_ods_fields.append((dwd_name, entry["dwd_col"]))
+
+        # 差异原因
+        reasons: list[str] = []
+        if api_unmapped_nested:
+            reasons.append(f"嵌套对象 {len(api_unmapped_nested)} 个")
+        if api_unmapped_flat:
+            reasons.append(f"平层未映射 {len(api_unmapped_flat)} 个")
+        if dwd_no_ods_fields:
+            reasons.append(f"SCD2/派生列 {len(dwd_no_ods_fields)} 个")
+        reason_str = "；".join(reasons) if reasons else "—"
+
+        # 汇总表单元格：数量 + 跳转链接
+        def _cell(count: int) -> str:
+            if count == 0:
+                return "0"
+            return f"[{count}](#{diff_anchor})"
+
+        w(f"| `{table_name}` | {_cell(api_unmapped_total)} | {_cell(len(ods_no_json_fields))} | {_cell(len(ods_no_dwd_fields))} | {_cell(len(dwd_no_ods_fields))} | {reason_str} |")
+
+        diff_rows.append({
+            "table_name": table_name,
+            "diff_anchor": diff_anchor,
+            "api_anchor": api_anchor,
+            "ods_anchor": ods_anchor,
+            "dwd_anchors": dwd_anchors,
+            "api_unmapped_flat": api_unmapped_flat,
+            "api_unmapped_nested": api_unmapped_nested,
+            "ods_no_json_fields": ods_no_json_fields,
+            "ods_no_dwd_fields": ods_no_dwd_fields,
+            "dwd_no_ods_fields": dwd_no_ods_fields,
+        })
+
+    w()
+
+    # ── 逐表差异分表 ──
+    sub_idx = 0
+    for row in diff_rows:
+        if row is None:
+            continue
+        has_any = (row["api_unmapped_flat"] or row["api_unmapped_nested"]
+                   or row["ods_no_json_fields"] or row["ods_no_dwd_fields"]
+                   or row["dwd_no_ods_fields"])
+        if not has_any:
+            continue
+
+        sub_idx += 1
+        table_name = row["table_name"]
+        w(f'<a id="{row["diff_anchor"]}"></a>')
+        w()
+        w(f"#### 1.1.{sub_idx} {table_name} 字段差异明细")
+        w()
+
+        api_anchor = row["api_anchor"]
+        ods_anchor = row["ods_anchor"]
+        dwd_anchors = row["dwd_anchors"]
+
+        # 加载辅助数据：json_trees（示例值）、bd_descriptions（业务说明）
+        jt = load_json(data_dir / "json_trees" / f"{table_name}.json")
+        bd = load_json(data_dir / "bd_descriptions" / f"{table_name}.json")
+        jt_lookup: dict[str, dict] = {}
+        if jt and "fields" in jt:
+            for fld in jt["fields"]:
+                jt_lookup[fld["path"]] = fld
+        ods_descs = bd.get("ods_fields", {}) if bd else {}
+        dwd_descs_all = bd.get("dwd_fields", {}) if bd else {}
+
+        def _sample_str(field_name: str, layer: str, dwd_tbl: str = "") -> str:
+            """从 json_trees 或 bd_descriptions 获取示例值字符串"""
+            if layer == "API":
+                entry = jt_lookup.get(field_name, {})
+                samples = entry.get("samples", [])
+                total_recs = entry.get("total_records", 0)
+                if not samples:
+                    single = entry.get("sample", "")
+                    if single:
+                        samples = [str(single)]
+                if _is_enum_like(samples, total_recs):
+                    return ", ".join(f"`{_esc(s)}`" for s in samples[:5])
+                if samples:
+                    return _format_samples(samples, max_show=3)
+            return ""
+
+        def _desc_str(field_name: str, layer: str, dwd_tbl: str = "") -> str:
+            """从 bd_descriptions 获取业务说明"""
+            key = field_name.split(".")[-1].replace("[]", "").lower()
+            if layer in ("ODS", "API"):
+                desc = ods_descs.get(key, "")
+            elif layer == "DWD" and dwd_tbl:
+                desc = dwd_descs_all.get(dwd_tbl, {}).get(key, "")
+            else:
+                desc = ""
+            if desc and len(desc) > 40:
+                desc = desc[:37] + "..."
+            return _esc(desc)
+
+        # ── API→ODS 未映射（平层） ──
+        if row["api_unmapped_flat"]:
+            w(f"**API→ODS 未映射（平层）** — {len(row['api_unmapped_flat'])} 个")
+            w()
+            w("| # | JSON 字段 | 推测用途 | 置信度 | 示例值 | 说明 | 状态 |")
+            w("|---|----------|---------|-------|-------|------|------|")
+            for i, f in enumerate(row["api_unmapped_flat"], 1):
+                purpose, conf = _guess_field_purpose(f, table_name, "API")
+                sample = _sample_str(f, "API")
+                desc = _desc_str(f, "API")
+                w(f"| {i} | **[`{_esc(f)}`](#{api_anchor})** | {_esc(purpose)} | {conf} | {sample} | {desc} | **⚠️ 未映射** |")
+            w()
+
+        # ── API→ODS 未映射（嵌套对象） ──
+        if row["api_unmapped_nested"]:
+            w(f"<details><summary>API→ODS 未映射（嵌套对象）— {len(row['api_unmapped_nested'])} 个</summary>")
+            w()
+            w("| # | JSON 字段 | 推测用途 | 置信度 | 示例值 | 说明 | 状态 |")
+            w("|---|----------|---------|-------|-------|------|------|")
+            for i, f in enumerate(row["api_unmapped_nested"], 1):
+                purpose, conf = _guess_field_purpose(f, table_name, "API")
+                sample = _sample_str(f, "API")
+                desc = _desc_str(f, "API")
+                w(f"| {i} | [`{_esc(f)}`](#{api_anchor}) | {_esc(purpose)} | {conf} | {sample} | {desc} | 📦 嵌套 |")
+            w()
+            w("</details>")
+            w()
+
+        # ── ODS 无 JSON 源 ──
+        if row["ods_no_json_fields"]:
+            w(f"**ODS 无 JSON 源** — {len(row['ods_no_json_fields'])} 个")
+            w()
+            w("| # | ODS 列 | 推测用途 | 置信度 | 说明 | 状态 |")
+            w("|---|-------|---------|-------|------|------|")
+            for i, f in enumerate(row["ods_no_json_fields"], 1):
+                purpose, conf = _guess_field_purpose(f, table_name, "ODS")
+                desc = _desc_str(f, "ODS")
+                w(f"| {i} | **[`{_esc(f)}`](#{ods_anchor})** | {_esc(purpose)} | {conf} | {desc} | **⚠️ 无 JSON 源** |")
+            w()
+
+        # ── ODS→DWD 未映射 ──
+        if row["ods_no_dwd_fields"]:
+            w(f"**ODS→DWD 未映射** — {len(row['ods_no_dwd_fields'])} 个")
+            w()
+            w("| # | ODS 列 | 推测用途 | 置信度 | 说明 | 状态 |")
+            w("|---|-------|---------|-------|------|------|")
+            for i, f in enumerate(row["ods_no_dwd_fields"], 1):
+                purpose, conf = _guess_field_purpose(f, table_name, "ODS")
+                desc = _desc_str(f, "ODS")
+                w(f"| {i} | **[`{_esc(f)}`](#{ods_anchor})** | {_esc(purpose)} | {conf} | {desc} | **⚠️ 无 DWD 目标** |")
+            w()
+
+        # ── DWD 无 ODS 源 ──
+        if row["dwd_no_ods_fields"]:
+            w(f"**DWD 无 ODS 源** — {len(row['dwd_no_ods_fields'])} 个")
+            w()
+            w("| # | DWD 表 | DWD 列 | 推测用途 | 置信度 | 说明 | 状态 |")
+            w("|---|-------|-------|---------|-------|------|------|")
+            for i, (dwd_name, dwd_col) in enumerate(row["dwd_no_ods_fields"], 1):
+                dwd_a = dwd_anchors.get(dwd_name, f"dwd-{dwd_name.replace('_', '-')}")
+                purpose, conf = _guess_field_purpose(dwd_col, table_name, "DWD")
+                desc = _desc_str(dwd_col, "DWD", dwd_tbl=dwd_name)
+                w(f"| {i} | {dwd_name} | **[`{_esc(dwd_col)}`](#{dwd_a})** | {_esc(purpose)} | {conf} | {desc} | **⚠️ 无 ODS 源** |")
+            w()
+
+    w()
+
+
+
+
+def _write_api_section(w, fm, jt, bd, table_name, api_anchor, ods_anchor):
+    """生成 API 源字段区块（增加业务描述列，合并说明+示例值）"""
+    w(f'<a id="{api_anchor}"></a>')
+    w()
+    w(f"#### API 源字段 — {table_name} [🔗 ODS](#{ods_anchor})")
+    w()
+
+    if not fm or "json_to_ods" not in fm:
+        w("_无 field_mappings 数据_")
+        w()
+        return
+
+    j2o = fm["json_to_ods"]
+    # 构建 json_tree 查找表（含 samples）
+    jt_lookup: dict[str, dict] = {}
+    if jt and "fields" in jt:
+        for f in jt["fields"]:
+            jt_lookup[f["path"]] = f
+
+    # BD_manual ODS 描述（用于交叉引用 JSON 字段的业务含义）
+    ods_descs = bd.get("ods_fields", {}) if bd else {}
+
+    mapped_count = sum(1 for m in j2o if m.get("ods_col") is not None)
+    total_count = len(j2o)
+    if total_count > 0:
+        w(f"已映射 {mapped_count}/{total_count}，覆盖率 {mapped_count / total_count * 100:.1f}%")
+    else:
+        w("无字段")
+    w()
+    w("| # | JSON 字段 | 类型 | → ODS 列 | 业务描述 | 示例值与说明 |")
+    w("|---|----------|------|---------|---------|------------|")
+
+    for i, m in enumerate(j2o, 1):
+        json_path = m["json_path"]
+        json_type = m.get("json_type", "")
+        ods_col = m.get("ods_col")
+        match_type = m.get("match_type", "")
+        occurrence_pct = m.get("occurrence_pct", 0)
+
+        # 从 json_tree 获取示例值（优先用 samples 多示例）
+        jt_entry = jt_lookup.get(json_path, {})
+        samples = jt_entry.get("samples", [])
+        total_recs = jt_entry.get("total_records", 0)
+        if not samples:
+            single = jt_entry.get("sample", "")
+            if single:
+                samples = [str(single)]
+
+        # 构建 ODS 列链接
+        if ods_col:
+            ods_link = f"[`{ods_col}`](#{ods_anchor})"
+        else:
+            ods_link = "⚠️ 未映射"
+
+        # 业务描述（从 BD_manual 查找，用 ODS 列名或 JSON 叶子名）
+        leaf = json_path.split(".")[-1].replace("[]", "").lower()
+        biz_desc = ods_descs.get(leaf, "")
+        if biz_desc and len(biz_desc) > 60:
+            biz_desc = biz_desc[:57] + "..."
+        biz_desc = _esc(biz_desc)
+
+        # 合并说明+示例值
+        notes_parts: list[str] = []
+        if json_path.startswith("siteProfile.") or ("." in json_path and match_type == "unmapped"):
+            notes_parts.append("📦 嵌套对象")
+        if match_type == "case_insensitive":
+            notes_parts.append("大小写匹配")
+        if occurrence_pct < 100:
+            notes_parts.append(f"出现率 {occurrence_pct:.0f}%")
+
+        # 示例值展示
+        if _is_enum_like(samples, total_recs):
+            notes_parts.append(f"枚举值: {', '.join(f'`{_esc(s)}`' for s in samples[:8])}")
+        elif samples:
+            notes_parts.append(f"示例: {_format_samples(samples)}")
+
+        note_str = "；".join(notes_parts) if notes_parts else ""
+
+        w(f"| {i} | `{_esc(json_path)}` | {json_type} | {ods_link} | {biz_desc} | {note_str} |")
+
+    w()
+
+
+def _write_ods_section(w, fm, ods_schema, bd, table_name, ods_anchor, api_anchor, dwd_anchors):
+    """生成 ODS 表结构区块（含上下游双向映射列 + 业务描述）"""
+    w(f'<a id="{ods_anchor}"></a>')
+    w()
+    w(f"#### ODS 表结构 — ods.{table_name} [🔗 API](#{api_anchor})")
+    w()
+
+    if not ods_schema or "columns" not in ods_schema:
+        w("_无 DB schema 数据_")
+        w()
+        return
+
+    # 构建 json_to_ods 反向查找：ods_col → json_path
+    ods_to_json: dict[str, str] = {}
+    if fm and "json_to_ods" in fm:
+        for m in fm["json_to_ods"]:
+            if m.get("ods_col"):
+                ods_to_json.setdefault(m["ods_col"], m["json_path"])
+
+    # 构建 ods_to_dwd 查找
+    ods_to_dwd: dict[str, list[dict]] = {}
+    if fm and "ods_to_dwd" in fm:
+        ods_to_dwd = fm["ods_to_dwd"]
+
+    # BD_manual ODS 描述
+    ods_descs = bd.get("ods_fields", {}) if bd else {}
+
+    cols = ods_schema["columns"]
+    w(f"共 {len(cols)} 列")
+    w()
+    w("| # | ODS 列名 | 类型 | ← JSON 源 | → DWD 目标 | 业务描述 |")
+    w("|---|---------|------|----------|-----------|---------|")
+
+    for i, col in enumerate(cols, 1):
+        col_name = col["name"]
+        col_type = col["data_type"]
+
+        # ← JSON 源
+        json_src = ods_to_json.get(col_name)
+        if json_src:
+            json_link = f"[`{_esc(json_src)}`](#{api_anchor})"
+        else:
+            json_link = "—"
+
+        # → DWD 目标
+        dwd_targets = ods_to_dwd.get(col_name, [])
+        if dwd_targets:
+            dwd_links = []
+            for dt in dwd_targets:
+                dwd_tbl = dt["dwd_table"]
+                dwd_col = dt["dwd_col"]
+                dwd_anc = dwd_anchors.get(dwd_tbl, f"dwd-{dwd_tbl}")
+                dwd_links.append(f"[`{dwd_tbl}.{dwd_col}`](#{dwd_anc})")
+            dwd_link = ", ".join(dwd_links)
+        else:
+            dwd_link = "—"
+
+        # 业务描述
+        biz_desc = ods_descs.get(col_name.lower(), "")
+        if biz_desc and len(biz_desc) > 60:
+            biz_desc = biz_desc[:57] + "..."
+        biz_desc = _esc(biz_desc)
+
+        w(f"| {i} | `{col_name}` | {col_type} | {json_link} | {dwd_link} | {biz_desc} |")
+
+    w()
+
+
+def _write_dwd_section(w, fm, dwd_schema, bd, dwd_name, dwd_anchor, ods_anchor, table_name):
+    """生成 DWD 表结构区块（增加业务描述列）"""
+    w(f'<a id="{dwd_anchor}"></a>')
+    w()
+    w(f"#### DWD 表结构 — dwd.{dwd_name} [🔗 ODS](#{ods_anchor})")
+    w()
+
+    if not dwd_schema or "columns" not in dwd_schema:
+        w("_无 DB schema 数据_")
+        w()
+        return
+
+    # 构建 dwd_to_ods 查找
+    dwd_to_ods_map: dict[str, dict] = {}
+    if fm and "dwd_to_ods" in fm and dwd_name in fm["dwd_to_ods"]:
+        for entry in fm["dwd_to_ods"][dwd_name]:
+            dwd_to_ods_map[entry["dwd_col"]] = entry
+
+    # BD_manual DWD 描述
+    dwd_descs = {}
+    if bd and "dwd_fields" in bd:
+        dwd_descs = bd["dwd_fields"].get(dwd_name, {})
+
+    cols = dwd_schema["columns"]
+    w(f"共 {len(cols)} 列")
+    w()
+    w("| # | DWD 列名 | 类型 | ← ODS 来源 | 转换 | 业务描述 |")
+    w("|---|---------|------|----------|------|---------|")
+
+    for i, col in enumerate(cols, 1):
+        col_name = col["name"]
+        col_type = col["data_type"]
+
+        mapping = dwd_to_ods_map.get(col_name)
+        if mapping:
+            ods_src = mapping.get("ods_source", "")
+            ods_link = f"[`{ods_src}`](#{ods_anchor})" if ods_src and ods_src != "—" else "—"
+            transform = mapping.get("mapping_type", "")
+            note = mapping.get("note", "")
+        else:
+            ods_link = "—"
+            transform = ""
+            note = ""
+            if col_name in ("valid_from", "valid_to", "is_current", "etl_loaded_at", "etl_batch_id"):
+                transform = "ETL 生成"
+
+        # 业务描述（优先 BD_manual，其次 mapping note，最后 DB comment）
+        biz_desc = dwd_descs.get(col_name.lower(), "")
+        if not biz_desc and note:
+            biz_desc = note
+        if not biz_desc:
+            db_comment = col.get("comment", "")
+            if db_comment:
+                if "【说明】" in db_comment:
+                    desc_part = db_comment.split("【说明】")[1]
+                    if "【" in desc_part:
+                        desc_part = desc_part.split("【")[0]
+                    biz_desc = desc_part.strip().rstrip("。").strip()
+                else:
+                    biz_desc = db_comment
+        if biz_desc and len(biz_desc) > 60:
+            biz_desc = biz_desc[:57] + "..."
+        biz_desc = _esc(biz_desc)
+
+        w(f"| {i} | `{col_name}` | {col_type} | {ods_link} | {_esc(transform)} | {biz_desc} |")
+
+    w()
+
+
+def main() -> None:
+    load_dotenv(Path(".env"), override=False)
+
+    parser = build_parser()
+    args = parser.parse_args()
+
+    data_dir = resolve_data_dir(args.output_dir)
+    if not data_dir.exists():
+        print(f"错误：数据目录不存在: {data_dir}")
+        return
+
+    print(f"读取数据目录: {data_dir}")
+    report = generate_report(data_dir)
+
+    now = datetime.now()
+    filename = f"dataflow_{now.strftime('%Y-%m-%d_%H%M%S')}.md"
+    output_path = data_dir / filename
+
+    with open(output_path, "w", encoding="utf-8") as f:
+        f.write(report)
+
+    print(f"\n{'='*60}")
+    print(f"报告生成完成")
+    print(f"{'='*60}")
+    print(f"  输出路径: {output_path}")
+    print(f"  文件大小: {output_path.stat().st_size / 1024:.1f} KB")
+    print(f"{'='*60}")
+
+
+if __name__ == "__main__":
+    main()