"""标的维表同步服务。 盘前 9:10 调用 tf.exchanges.get_instruments("SH"/"SZ"/"BJ", type="stock") 获取全量标的元数据,flatten ext 字段,写入 instruments.parquet。 Starter+ 盘后可用 quotes.get(universes) 顺便补充 name。 """ from __future__ import annotations import logging from datetime import date from pathlib import Path import polars as pl from app.tickflow.client import get_client logger = logging.getLogger(__name__) _EXCHANGES = ["SH", "SZ", "BJ"] def _flatten_instruments(items: list[dict]) -> list[dict]: """把 SDK 返回的 Instrument 列表 flatten 成扁平行。""" rows = [] for item in items: row = { "symbol": item.get("symbol"), "name": item.get("name"), "code": item.get("code"), "exchange": item.get("exchange"), "region": item.get("region"), "type": item.get("type"), } ext = item.get("ext") or {} row["listing_date"] = ext.get("listing_date") row["total_shares"] = ext.get("total_shares") row["float_shares"] = ext.get("float_shares") row["tick_size"] = ext.get("tick_size") row["limit_up"] = ext.get("limit_up") row["limit_down"] = ext.get("limit_down") rows.append(row) return rows def sync_instruments(data_dir: Path) -> int: """全量同步标的维表 → data/instruments/instruments.parquet。 返回写入的行数。 """ tf = get_client() all_rows: list[dict] = [] for ex in _EXCHANGES: try: items = tf.exchanges.get_instruments(ex, instrument_type="stock") if items: all_rows.extend(_flatten_instruments(items)) logger.info("instruments %s: %d stocks", ex, len(items)) except Exception as e: logger.warning("get_instruments(%s) failed: %s", ex, e) if not all_rows: return 0 df = pl.DataFrame(all_rows) df = df.with_columns(pl.lit(date.today()).alias("as_of")) out = data_dir / "instruments" / "instruments.parquet" out.parent.mkdir(parents=True, exist_ok=True) df.write_parquet(out) logger.info("instruments synced: %d rows → %s", df.height, out) return df.height def enrich_names_from_quotes( data_dir: Path, quotes_data: list[dict], ) -> int: """从 quotes 响应中提取 name,更新 instruments 维表(兜底补充)。 盘后 quotes.get(universes) 返回的数据中包含 ext.name, 用来补充 instruments 中可能缺失的 name。 """ if not quotes_data: return 0 # 构建 symbol → name 映射 name_map: dict[str, str] = {} for q in quotes_data: symbol = q.get("symbol", "") ext = q.get("ext") or {} name = ext.get("name") or q.get("name", "") if symbol and name: name_map[symbol] = name if not name_map: return 0 inst_path = data_dir / "instruments" / "instruments.parquet" if not inst_path.exists(): return 0 df = pl.read_parquet(inst_path) # 只更新空 name 的行 updates = pl.DataFrame({ "symbol": list(name_map.keys()), "_new_name": list(name_map.values()), }) df = df.join(updates, on="symbol", how="left") df = df.with_columns( pl.when(pl.col("name").is_null() | (pl.col("name") == "")) .then(pl.col("_new_name")) .otherwise(pl.col("name")) .alias("name"), ).drop("_new_name") df.write_parquet(inst_path) logger.info("instruments name enriched from quotes: %d names", len(name_map)) return len(name_map)