diff --git a/scripts/data_platform/migrate_constituent.py b/scripts/data_platform/migrate_constituent.py
index da8dc29..821c3dd 100644
--- a/scripts/data_platform/migrate_constituent.py
+++ b/scripts/data_platform/migrate_constituent.py
@@ -77,6 +77,61 @@ def _read_baostock_constituent(c: sqlite3.Connection) -> pd.DataFrame:
     return df
 
 
+def _read_announce_union_aggregated(hist_dir: str,
+                                     index_codes: list[str]) -> pd.DataFrame:
+    """读 *_announce_union.parquet, 聚合成全集型(index_code/code/code_name/
+    in_current/was_removed/source)。
+
+    announce_union schema:
+        updateDate / index_code / code / code_name / adjust_type / notice_id / source
+        adjust_type: add | remove | current | initial
+
+    全集聚合(spec §14):
+        ever_codes   = announce_union 所有 distinct code(任意 adjust_type)
+        current_codes = announce_union 中 adjust_type='current' 的 code
+                        (∪ <idx>_snapshot.parquet 兜底, 兼容旧 announce 无 current 行)
+        in_current   = code in current_codes
+        was_removed  = not in_current(曾经入选已踢)
+        code_name    = 优先 snapshot 当前名(announce 的历史名可能过时)
+
+    缺 announce_union 文件 -> 返回空 DataFrame(上层走 snapshot 兜底)。
+    """
+    cols = ["index_code", "code", "code_name", "in_current", "was_removed", "source"]
+    rows = []
+    for idx in index_codes:
+        ann_path = os.path.join(hist_dir, f"{idx}_announce_union.parquet")
+        if not os.path.exists(ann_path):
+            continue
+        ann = pd.read_parquet(ann_path)
+        ann["code"] = ann["code"].apply(norm_code)
+        # current 兜底: announce 内 current 行 + snapshot 文件
+        current_codes = set(ann.loc[ann["adjust_type"] == "current", "code"])
+        snap_path = os.path.join(hist_dir, f"{idx}_snapshot.parquet")
+        snap_name_map: dict[str, str] = {}
+        if os.path.exists(snap_path):
+            snap = pd.read_parquet(snap_path)
+            snap["code"] = snap["code"].apply(norm_code)
+            current_codes |= set(snap["code"])
+            snap_name_map = dict(zip(snap["code"], snap["code_name"]))
+        # ever = distinct(code), name 取 announce 或 snapshot(优先 snapshot)
+        ever = (
+            ann[["code", "code_name"]]
+            .drop_duplicates(subset=["code"])
+        )
+        for _, r in ever.iterrows():
+            code = r["code"]
+            in_cur = code in current_codes
+            name = snap_name_map.get(code) or r["code_name"]
+            rows.append({
+                "index_code": idx, "code": code, "code_name": name,
+                "in_current": int(in_cur), "was_removed": int(not in_cur),
+                "source": "csindex_announce",
+            })
+    if not rows:
+        return pd.DataFrame(columns=cols)
+    return pd.DataFrame(rows, columns=cols)
+
+
 def migrate(db_path: str) -> None:
     """(幂等)重建 constituent_unified_staging。
 
@@ -115,23 +170,30 @@ def migrate(db_path: str) -> None:
         df_deep["code"] = df_deep["code"].apply(norm_code)
         print(f"[深证 union] rows={len(df_deep)}")
 
-        # 3. 中证 snapshot
-        snap = []
-        for f in [os.path.join(HIST, "000852_snapshot.parquet"),
-                  os.path.join(HIST, "932000_snapshot.parquet")]:
-            if os.path.exists(f):
-                d = pd.read_parquet(f)[["index_code", "code", "code_name"]]
-                d["in_current"] = True
-                d["was_removed"] = False
-                d["source"] = "akshare_csindex"
-                snap.append(d)
-        df_snap = pd.concat(snap, ignore_index=True) if snap else pd.DataFrame(
-            columns=["index_code", "code", "code_name", "in_current", "was_removed", "source"])
-        df_snap["code"] = df_snap["code"].apply(norm_code)
-        print(f"[中证 snapshot] rows={len(df_snap)}")
+        # 3. 中证 1000/2000 announce_union 全集(优先); 缺则回退 snapshot 当前
+        ANNOUNCE_IDX = ["000852", "932000"]
+        df_csi = _read_announce_union_aggregated(HIST, ANNOUNCE_IDX)
+        if df_csi.empty:
+            # 回退: 旧 snapshot-only 路径(announce_union 未生成时)
+            snap = []
+            for f in [os.path.join(HIST, "000852_snapshot.parquet"),
+                      os.path.join(HIST, "932000_snapshot.parquet")]:
+                if os.path.exists(f):
+                    d = pd.read_parquet(f)[["index_code", "code", "code_name"]]
+                    d["in_current"] = True
+                    d["was_removed"] = False
+                    d["source"] = "akshare_csindex"
+                    snap.append(d)
+            df_csi = pd.concat(snap, ignore_index=True) if snap else pd.DataFrame(
+                columns=["index_code", "code", "code_name", "in_current", "was_removed", "source"])
+            df_csi["code"] = df_csi["code"].apply(norm_code)
+            print(f"[中证 snapshot 回退] rows={len(df_csi)}")
+        else:
+            print(f"[中证 announce_union] rows={len(df_csi)}, "
+                  f"indices={df_csi['index_code'].nunique()}")
 
         # 合并 + 去重 (同 index+code+source)
-        all_df = pd.concat([pool, df_deep, df_snap], ignore_index=True)
+        all_df = pd.concat([pool, df_deep, df_csi], ignore_index=True)
         all_df = all_df.drop_duplicates(["index_code", "code", "source"])
         print(f"\n[TOTAL] constituent_unified: {len(all_df)} rows, "
               f"{all_df['index_code'].nunique()} indices")
@@ -163,7 +225,11 @@ def migrate(db_path: str) -> None:
             "SELECT COUNT(*), SUM(in_current), SUM(was_removed) FROM "
             f"{STAGING} WHERE index_code='399001'").fetchone())
         print("sample 000852:", c.execute(
-            "SELECT COUNT(*) FROM " f"{STAGING} WHERE index_code='000852'").fetchone())
+            "SELECT COUNT(*), SUM(in_current), SUM(was_removed) FROM "
+            f"{STAGING} WHERE index_code='000852'").fetchone())
+        print("sample 932000:", c.execute(
+            "SELECT COUNT(*), SUM(in_current), SUM(was_removed) FROM "
+            f"{STAGING} WHERE index_code='932000'").fetchone())
     finally:
         c.close()
     print("\nMIGRATE STAGING DONE (未 rename, 验证 OK 后单独合并)")
diff --git a/scripts/data_platform/parse_csindex_announce.py b/scripts/data_platform/parse_csindex_announce.py
index 31e322c..c65ebff 100644
--- a/scripts/data_platform/parse_csindex_announce.py
+++ b/scripts/data_platform/parse_csindex_announce.py
@@ -118,6 +118,33 @@ def _download(url: str, target: Path, timeout: int = 60) -> int:
 
 
 # ======================== 1. 列表 ========================
+def _fetch_paginated(payload_base: dict, label: str) -> List[dict]:
+    """通用分页拉取(单线程 + sleep)"""
+    all_items = []
+    page = 1
+    while True:
+        payload = dict(payload_base)
+        payload["page"] = {"desc": "", "key": "", "page": page, "rows": 100}
+        try:
+            d = _post_json(LIST_URL, payload)
+        except Exception as e:
+            log.error(f"[{label}] page {page} err: {e}; retry once after 5s")
+            time.sleep(5)
+            d = _post_json(LIST_URL, payload)
+        if d.get("code") != "200":
+            log.error(f"[{label}] page {page} API err: {d}")
+            break
+        items = d.get("data") or []
+        all_items.extend(items)
+        total = d.get("total") or 0
+        log.info(f"  [{label}] page {page}: +{len(items)} (cum={len(all_items)}/{total})")
+        if not items or len(all_items) >= total:
+            break
+        page += 1
+        time.sleep(1.0)
+    return all_items
+
+
 def fetch_all_notices(cache_path: Path, force: bool = False) -> List[dict]:
     """拉全量公告列表 (cached)"""
     if cache_path.exists() and not force:
@@ -126,31 +153,11 @@ def fetch_all_notices(cache_path: Path, force: bool = False) -> List[dict]:
             return json.load(f)
 
     log.info(f"分页拉取全量公告: {LIST_URL}")
-    all_items = []
-    page = 1
-    while True:
-        payload = {
-            "lang": "cn", "classlist": [], "indexlist": [],
-            "page": {"desc": "", "key": "", "page": page, "rows": 100},
-            "related_topics": [], "typelist": [],
-        }
-        try:
-            d = _post_json(LIST_URL, payload)
-        except Exception as e:
-            log.error(f"page {page} err: {e}; retry once after 5s")
-            time.sleep(5)
-            d = _post_json(LIST_URL, payload)
-        if d.get("code") != "200":
-            log.error(f"page {page} API err: {d}")
-            break
-        items = d.get("data") or []
-        all_items.extend(items)
-        total = d.get("total") or 0
-        log.info(f"  page {page}: +{len(items)} (cum={len(all_items)}/{total})")
-        if not items or len(all_items) >= total:
-            break
-        page += 1
-        time.sleep(1.0)
+    all_items = _fetch_paginated(
+        {"lang": "cn", "classlist": [], "indexlist": [],
+         "related_topics": [], "typelist": []},
+        label="all",
+    )
 
     cache_path.parent.mkdir(parents=True, exist_ok=True)
     with open(cache_path, "w", encoding="utf-8") as f:
@@ -159,6 +166,30 @@ def fetch_all_notices(cache_path: Path, force: bool = False) -> List[dict]:
     return all_items
 
 
+def fetch_notices_by_index(index_code: str, cache_path: Path, force: bool = False) -> List[dict]:
+    """按 indexCode 精准分页拉公告列表 (cached)
+
+    实证: indexCode='000852' 返 96 条(44 调样, 回溯到 2007), 远优于 title 过滤的 28 条。
+    """
+    if cache_path.exists() and not force:
+        log.info(f"使用缓存 indexCode 列表: {cache_path}")
+        with open(cache_path, encoding="utf-8") as f:
+            return json.load(f)
+
+    log.info(f"分页拉取 indexCode={index_code} 公告: {LIST_URL}")
+    items = _fetch_paginated(
+        {"lang": "cn", "classlist": [], "indexlist": [], "indexCode": index_code,
+         "related_topics": [], "typelist": []},
+        label=f"idx={index_code}",
+    )
+
+    cache_path.parent.mkdir(parents=True, exist_ok=True)
+    with open(cache_path, "w", encoding="utf-8") as f:
+        json.dump(items, f, ensure_ascii=False)
+    log.info(f"缓存 indexCode 列表: {cache_path} (total={len(items)})")
+    return items
+
+
 def filter_csi1000_notices(notices: List[dict]) -> List[dict]:
     """筛 CSI 1000 调整公告 (theme=指数调样 + title 含 中证1000)"""
     out = []
@@ -182,6 +213,29 @@ def filter_csi1000_notices(notices: List[dict]) -> List[dict]:
     return out
 
 
+def filter_adjustment_notices(notices: List[dict], keyword: str = "") -> List[dict]:
+    """通用调整公告筛选: theme=指数调样 + (可选) title 含 keyword
+
+    用于 indexCode 拉取的列表(已按指数过滤,无需 title 匹配)。
+    """
+    out = []
+    seen_ids = set()
+    for x in notices:
+        if x.get("theme") != "指数调样":
+            continue
+        title = x.get("title") or ""
+        if keyword and keyword not in title:
+            continue
+        if "不实施" in title:
+            continue
+        if x["id"] in seen_ids:
+            continue
+        seen_ids.add(x["id"])
+        out.append(x)
+    out.sort(key=lambda x: x.get("publishDate", ""))
+    return out
+
+
 # ======================== 2. 详情 + 下载 ========================
 def fetch_detail(nid: int, cache_dir: Path) -> dict:
     """详情 (cached by id)"""
@@ -429,11 +483,80 @@ def process_notice(nid: int, detail_cache: Path, file_cache: Path,
     return records
 
 
+def fetch_akshare_current(index_code: str) -> List[dict]:
+    """拉 akshare 当前快照 -> records(adjust_type='current')
+
+    akshare 返列: 日期/指数代码/指数名称/指数英文名称/成分券代码/成分券名称/...
+    成分券代码 = 倒数第 2 不是 iloc[0](=日期), 用 header 名定位稳健。
+    """
+    import akshare as ak
+    log.info(f"拉 akshare 当前快照 index={index_code}...")
+    df = ak.index_stock_cons_csindex(symbol=index_code)
+    # header 定位
+    cols = list(df.columns)
+    code_col = next((c for c in cols if "成分券代码" in str(c) or "股票代码" in str(c) or "证券代码" in str(c)), None)
+    name_col = next((c for c in cols if "成分券名称" in str(c) or "股票名称" in str(c) or "证券名称" in str(c)), None)
+    if code_col is None:
+        # 兜底: 第 5 列(成分券代码 实证位置)
+        code_col = cols[4] if len(cols) > 4 else cols[0]
+    if name_col is None and len(cols) > 5:
+        name_col = cols[5]
+    out = []
+    for _, row in df.iterrows():
+        raw = row[code_col]
+        s = str(raw).strip()
+        if not s or not s.isdigit():
+            continue
+        code = s.zfill(6)
+        if len(code) != 6:
+            continue
+        name = str(row[name_col]).strip() if name_col else ""
+        out.append({
+            "updateDate": "current", "index_code": index_code,
+            "code": code, "code_name": name,
+            "adjust_type": "current", "notice_id": 0, "source": "akshare.index_stock_cons_csindex",
+        })
+    log.info(f"  akshare current {index_code}: {len(out)} stocks")
+    return out
+
+
+def parse_launch_xlsx(path: Path, index_code: str, publish_date: str, notice_id: int) -> List[dict]:
+    """解析 launch xlsx (单 sheet, header 6 列: 指数代码/指数简称/指数英文简称/证券代码/证券中文简称/证券英文名称)
+
+    用 header 定位"证券代码"和"证券中文简称"列, 不依赖固定 col index。
+    """
+    wb = openpyxl.load_workbook(path, data_only=True)
+    out = []
+    for sn in wb.sheetnames:
+        ws = wb[sn]
+        rows = list(ws.iter_rows(values_only=True))
+        if not rows:
+            continue
+        header = rows[0]
+        code_idx = next((i for i, h in enumerate(header) if h and "证券代码" in str(h)), 3)
+        name_idx = next((i for i, h in enumerate(header) if h and "证券中文简称" in str(h)), 4)
+        for row in rows[1:]:
+            if not row:
+                continue
+            code = _norm_code(row[code_idx] if len(row) > code_idx else None)
+            if not code:
+                continue
+            name = str(row[name_idx]).strip() if len(row) > name_idx and row[name_idx] else ""
+            out.append({
+                "updateDate": publish_date, "index_code": index_code,
+                "code": code, "code_name": name,
+                "adjust_type": "initial", "notice_id": notice_id, "source": path.name,
+            })
+        break  # 只用第一个 sheet
+    return out
+
+
 def main():
     parser = argparse.ArgumentParser()
     parser.add_argument("--out-dir", default=str(OUT_DIR))
     parser.add_argument("--cache-dir", default=str(CACHE_DIR))
     parser.add_argument("--refresh-list", action="store_true", help="强制重新拉全量公告列表")
+    parser.add_argument("--refresh-index", action="store_true", help="强制重新拉 indexCode 公告列表")
     parser.add_argument("--only", choices=["1000", "2000", "both"], default="both")
     args = parser.parse_args()
 
@@ -443,17 +566,29 @@ def main():
     detail_cache = cache_dir / "detail"
     file_cache = cache_dir / "files"
 
-    # 1. 拉/缓存全量列表
+    # 1. 拉/缓存全量列表(兜底) + indexCode 精准列表(主源)
     notices = fetch_all_notices(cache_dir / "all_notices.json", force=args.refresh_list)
+    notices_000852 = fetch_notices_by_index(
+        "000852", cache_dir / "notices_000852.json", force=args.refresh_index,
+    )
 
     # ========== CSI 1000 ==========
     if args.only in ("1000", "both"):
         log.info("\n========== CSI 1000 (000852) ==========")
-        # 过滤 + 附加已知 id
-        filtered = filter_csi1000_notices(notices)
-        log.info(f"filtered CSI 1000 adjustment notices: {len(filtered)}")
+        # 主源: indexCode=000852 精准拉, theme=指数调样
+        adj_idx = filter_adjustment_notices(notices_000852)
+        log.info(f"indexCode=000852 调整公告: {len(adj_idx)}")
+        # 兜底: 旧 title 过滤(防 indexCode 接口变动)
+        filtered_old = filter_csi1000_notices(notices)
+        log.info(f"title 过滤兜底: {len(filtered_old)}")
 
-        all_ids = sorted({x["id"] for x in filtered} | set(CSI1000_REGULAR_IDS) | set(CSI1000_TEMP_IDS))
+        all_ids = (
+            {x["id"] for x in adj_idx}
+            | {x["id"] for x in filtered_old}
+            | set(CSI1000_REGULAR_IDS)
+            | set(CSI1000_TEMP_IDS)
+        )
+        all_ids = sorted(all_ids)
         log.info(f"total CSI 1000 notice ids to process: {len(all_ids)}")
 
         records_1000 = []
@@ -464,24 +599,11 @@ def main():
             except Exception as e:
                 log.error(f"  {nid} FAILED: {e}")
 
-        # 加 initial 集合 (launch 2014-09 -> 2014-09-18 id=2998, 无初始样本 xlsx, 跳过)
-        # 加 current (akshare 现快照)
+        # 加 current (akshare 现快照, header 定位列, 修 iloc[0] bug)
         try:
-            import akshare as ak
-            log.info("拉 akshare 中证1000 当前快照...")
-            df = ak.index_stock_cons_csindex(symbol="000852")
-            for _, row in df.iterrows():
-                code = str(row.iloc[0]).zfill(6) if str(row.iloc[0]).isdigit() else str(row.iloc[0])
-                if not code.isdigit() or len(code) != 6:
-                    continue
-                records_1000.append({
-                    "updateDate": "current", "index_code": "000852",
-                    "code": code, "code_name": str(row.iloc[1]) if df.shape[1] > 1 else "",
-                    "adjust_type": "current", "notice_id": 0, "source": "akshare.index_stock_cons_csindex",
-                })
-            log.info(f"  akshare current: {sum(1 for r in records_1000 if r['adjust_type']=='current')} stocks")
+            records_1000.extend(fetch_akshare_current("000852"))
         except Exception as e:
-            log.warning(f"akshare 当前快照拉取失败 (非致命): {e}")
+            log.warning(f"akshare 000852 当前快照失败 (非致命): {e}")
 
         df_1000 = pd.DataFrame(records_1000, columns=[
             "updateDate", "index_code", "code", "code_name", "adjust_type", "notice_id", "source"])
@@ -504,7 +626,7 @@ def main():
         log.warning("     仅可从 2023-08-10 launch xlsx 获取初始 2000 只样本")
         records_2000 = []
 
-        # launch xlsx (initial)
+        # launch xlsx (initial) — header 定位列, 修 row[0] bug
         try:
             detail = fetch_detail(CSI2000_LAUNCH_ID, detail_cache)
             if detail.get("data"):
@@ -515,45 +637,16 @@ def main():
                 for f in files:
                     if f.suffix.lower() != ".xlsx":
                         continue
-                    wb = openpyxl.load_workbook(f, data_only=True)
-                    for sn in wb.sheetnames:
-                        ws = wb[sn]
-                        rows = list(ws.iter_rows(values_only=True))
-                        if not rows:
-                            continue
-                        header = rows[0]
-                        # 找 code 列 (通常第 1 列 或 命名"证券代码"/"成分券代码")
-                        for row in rows[1:]:
-                            if not row:
-                                continue
-                            code = _norm_code(row[0] if len(row) > 0 else None)
-                            if not code:
-                                continue
-                            name = str(row[1]).strip() if len(row) > 1 and row[1] else ""
-                            records_2000.append({
-                                "updateDate": publish_date, "index_code": "932000",
-                                "code": code, "code_name": name,
-                                "adjust_type": "initial", "notice_id": CSI2000_LAUNCH_ID, "source": f.name,
-                            })
-                    break  # 只用第一个 xlsx
+                    recs = parse_launch_xlsx(f, "932000", publish_date, CSI2000_LAUNCH_ID)
+                    records_2000.extend(recs)
+                    log.info(f"  launch xlsx {f.name}: {len(recs)} initial stocks")
+                    break
         except Exception as e:
             log.error(f"CSI 2000 launch xlsx ERR: {e}")
 
-        # current snapshot via akshare
+        # current snapshot via akshare (header 定位列)
         try:
-            import akshare as ak
-            log.info("拉 akshare 中证2000 当前快照...")
-            df = ak.index_stock_cons_csindex(symbol="932000")
-            for _, row in df.iterrows():
-                code = str(row.iloc[0]).zfill(6) if str(row.iloc[0]).isdigit() else str(row.iloc[0])
-                if not code.isdigit() or len(code) != 6:
-                    continue
-                records_2000.append({
-                    "updateDate": "current", "index_code": "932000",
-                    "code": code, "code_name": str(row.iloc[1]) if df.shape[1] > 1 else "",
-                    "adjust_type": "current", "notice_id": 0, "source": "akshare.index_stock_cons_csindex",
-                })
-            log.info(f"  akshare current: {sum(1 for r in records_2000 if r['adjust_type']=='current')} stocks")
+            records_2000.extend(fetch_akshare_current("932000"))
         except Exception as e:
             log.warning(f"akshare CSI 2000 当前快照失败: {e}")
 
diff --git a/tests/portfolio/test_migrate_announce_union.py b/tests/portfolio/test_migrate_announce_union.py
new file mode 100644
index 0000000..be8e47d
--- /dev/null
+++ b/tests/portfolio/test_migrate_announce_union.py
@@ -0,0 +1,191 @@
+"""tests/portfolio/test_migrate_announce_union.py
+
+TDD for migrate_constituent._read_announce_union_aggregated()
+
+聚合逻辑(全集型):
+- ever_codes = announce_union 所有 distinct code (add/remove/initial/current 任一)
+- current_codes = announce_union 中 adjust_type='current' 的 code (∪ snapshot 兜底)
+- in_current = code in current_codes
+- was_removed = not in_current (曾经入选但当前不在)
+
+对应 plan: docs/superpowers/plans/2026-07-23-csi1000-constituent-backfill.md Task 2
+"""
+import os
+import sys
+from pathlib import Path
+
+import pandas as pd
+import pytest
+
+# 让测试能 import scripts/...
+ROOT = Path(__file__).resolve().parents[2]
+sys.path.insert(0, str(ROOT))
+sys.path.insert(0, str(ROOT / "scripts" / "data_platform"))
+
+
+# ---------- import target ----------
+@pytest.fixture(scope="module")
+def migrate_module():
+    """import migrate_constituent 模块(不走 main, 只用函数)"""
+    import importlib.util
+    spec = importlib.util.spec_from_file_location(
+        "migrate_constituent_for_test",
+        ROOT / "scripts" / "data_platform" / "migrate_constituent.py",
+    )
+    mod = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(mod)
+    return mod
+
+
+# ---------- 合成 announce_union ----------
+def _make_announce_df(rows):
+    """rows: list of (code, code_name, adjust_type)"""
+    return pd.DataFrame(
+        [{"updateDate": "2024-01-01", "index_code": "000852",
+          "code": c, "code_name": n, "adjust_type": t,
+          "notice_id": 1, "source": "synthetic.xlsx"} for c, n, t in rows]
+    )
+
+
+# ============================================================
+# Unit: 聚合逻辑(ever/in_current/was_removed)
+# ============================================================
+def test_aggregation_basic(migrate_module, tmp_path):
+    """announce(add A,B + remove C) + current(A,B,D) -> ever={A,B,C,D},
+    in_current={A,B,D}, was_removed={C}
+    """
+    # build announce_union parquet (含 current 行)
+    ann = _make_announce_df([
+        ("000001", "A", "add"),
+        ("000002", "B", "add"),
+        ("000003", "C", "remove"),
+        ("000001", "A", "current"),
+        ("000002", "B", "current"),
+        ("000004", "D", "current"),
+    ])
+    hist = tmp_path / "hist"
+    hist.mkdir()
+    ann.to_parquet(hist / "000852_announce_union.parquet", index=False)
+
+    df = migrate_module._read_announce_union_aggregated(str(hist), ["000852"])
+    assert len(df) == 4  # ever set 4 stocks
+    # index_code 全是 000852
+    assert set(df["index_code"]) == {"000852"}
+    # ever = {A,B,C,D}
+    assert set(df["code"]) == {"000001", "000002", "000003", "000004"}
+    # in_current = {A,B,D}, was_removed = {C}
+    in_cur = set(df[df["in_current"] == 1]["code"])
+    removed = set(df[df["was_removed"] == 1]["code"])
+    assert in_cur == {"000001", "000002", "000004"}
+    assert removed == {"000003"}
+    # 不存在既 in_current 又 was_removed 的行
+    assert ((df["in_current"] == 1) & (df["was_removed"] == 1)).sum() == 0
+    # 每行至少一个标记(全集型的硬条件)
+    assert ((df["in_current"] == 1) | (df["was_removed"] == 1)).sum() == 4
+
+
+def test_aggregation_no_current_rows_uses_snapshot(migrate_module, tmp_path):
+    """announce_union 只有 add/remove 时, 从 snapshot.parquet 兜底 current_codes"""
+    ann = _make_announce_df([
+        ("000001", "A", "add"),
+        ("000002", "B", "add"),
+        ("000003", "C", "remove"),
+    ])
+    snap = pd.DataFrame({
+        "index_code": ["000852", "000852"],
+        "code": ["000001", "000002"],
+        "code_name": ["A", "B"],
+    })
+    hist = tmp_path / "hist"
+    hist.mkdir()
+    ann.to_parquet(hist / "000852_announce_union.parquet", index=False)
+    snap.to_parquet(hist / "000852_snapshot.parquet", index=False)
+
+    df = migrate_module._read_announce_union_aggregated(str(hist), ["000852"])
+    assert set(df["code"]) == {"000001", "000002", "000003"}
+    in_cur = set(df[df["in_current"] == 1]["code"])
+    assert in_cur == {"000001", "000002"}  # snapshot 兜底
+    removed = set(df[df["was_removed"] == 1]["code"])
+    assert removed == {"000003"}
+
+
+def test_aggregation_idempotent(migrate_module, tmp_path):
+    """跑两次结果一致(幂等)"""
+    ann = _make_announce_df([
+        ("000001", "A", "add"),
+        ("000002", "B", "remove"),
+        ("000001", "A", "current"),
+    ])
+    hist = tmp_path / "hist"
+    hist.mkdir()
+    ann.to_parquet(hist / "000852_announce_union.parquet", index=False)
+
+    df1 = migrate_module._read_announce_union_aggregated(str(hist), ["000852"])
+    df2 = migrate_module._read_announce_union_aggregated(str(hist), ["000852"])
+    pd.testing.assert_frame_equal(
+        df1.reset_index(drop=True), df2.reset_index(drop=True),
+        check_like=True,
+    )
+
+
+def test_aggregation_missing_file_returns_empty(migrate_module, tmp_path):
+    """文件不存在 -> 空 DataFrame(不崩)"""
+    hist = tmp_path / "hist"
+    hist.mkdir()
+    df = migrate_module._read_announce_union_aggregated(str(hist), ["000852"])
+    assert df.empty
+    assert list(df.columns) == [
+        "index_code", "code", "code_name", "in_current", "was_removed", "source"]
+
+
+def test_aggregation_prefers_snapshot_name(migrate_module, tmp_path):
+    """code_name 优先 snapshot 当前名(announce 的历史名可能过时)"""
+    ann = _make_announce_df([
+        ("000001", "旧名", "add"),
+        ("000001", "旧名", "current"),
+    ])
+    snap = pd.DataFrame({
+        "index_code": ["000852"],
+        "code": ["000001"],
+        "code_name": ["新名"],
+    })
+    hist = tmp_path / "hist"
+    hist.mkdir()
+    ann.to_parquet(hist / "000852_announce_union.parquet", index=False)
+    snap.to_parquet(hist / "000852_snapshot.parquet", index=False)
+
+    df = migrate_module._read_announce_union_aggregated(str(hist), ["000852"])
+    assert df.iloc[0]["code_name"] == "新名"
+
+
+# ============================================================
+# Integration: 真实 announce_union.parquet (Mac parse 产出)
+# ============================================================
+MAC_HIST = ROOT / "data" / "index_const_hist"
+
+
+@pytest.mark.integration
+def test_real_000852_distinct_greater_1000(migrate_module):
+    """000852 治偏差证据: distinct > 1000(plan 验证标准)"""
+    if not (MAC_HIST / "000852_announce_union.parquet").exists():
+        pytest.skip("000852_announce_union.parquet 未生成, 先跑 parse_csindex_announce.py")
+    df = migrate_module._read_announce_union_aggregated(str(MAC_HIST), ["000852"])
+    n_distinct = df["code"].nunique()
+    n_removed = (df["was_removed"] == 1).sum()
+    assert n_distinct > 1000, f"000852 distinct={n_distinct}, 期望 >1000(治偏差)"
+    assert n_removed > 0, f"000852 was_removed={n_removed}, 期望 >0"
+    print(f"\n000852: distinct={n_distinct}, in_current={int((df['in_current']==1).sum())}, "
+          f"was_removed={n_removed}")
+
+
+@pytest.mark.integration
+def test_real_932000_distinct_approx_2000(migrate_module):
+    """932000 launch xlsx bug 修复: distinct ≈ 2000+(launch ∪ current)"""
+    if not (MAC_HIST / "932000_announce_union.parquet").exists():
+        pytest.skip("932000_announce_union.parquet 未生成, 先跑 parse_csindex_announce.py")
+    df = migrate_module._read_announce_union_aggregated(str(MAC_HIST), ["932000"])
+    n_distinct = df["code"].nunique()
+    # launch 修复后 distinct 不再=1, 应在 2000+(launch ∪ current 重叠后 2684 实证)
+    assert n_distinct >= 2000, f"932000 distinct={n_distinct}, 期望 ≥2000(launch 修复)"
+    print(f"\n932000: distinct={n_distinct}, in_current={int((df['in_current']==1).sum())}, "
+          f"was_removed={int((df['was_removed']==1).sum())}")