migration: preserve market insights slice
This commit is contained in:
leefer
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from .repository import DragonTigerRepositoryMixin
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from .service import DragonTigerServiceMixin
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__all__ = ["DragonTigerRepositoryMixin", "DragonTigerServiceMixin"]
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from __future__ import annotations
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from datetime import datetime
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from typing import Any
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class DragonTigerRepositoryMixin:
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def list_seat_aliases(self) -> dict[str, str]:
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with self.connect() as connection:
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rows = connection.execute("SELECT seat_name, alias FROM seat_aliases").fetchall()
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return {row["seat_name"]: row["alias"] for row in rows}
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def save_seat_alias(self, seat_name: str, alias: str) -> None:
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now = datetime.now().astimezone().isoformat(timespec="seconds")
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with self.connect() as connection:
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connection.execute(
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"""
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INSERT INTO seat_aliases (seat_name, alias, updated_at)
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VALUES (?, ?, ?)
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ON CONFLICT(seat_name) DO UPDATE SET
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alias = excluded.alias,
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updated_at = excluded.updated_at
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""",
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(seat_name, alias, now),
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)
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def upsert_lhb_institutions(self, rows: list[dict[str, Any]]) -> int:
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grouped: dict[tuple[str, str], dict[str, float | int]] = {}
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for row in rows:
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trade_date = str(row.get("trade_date") or "")
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ts_code = str(row.get("ts_code") or "")
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seat_name = str(row.get("exalter") or row.get("seat_name") or "")
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if not trade_date or not ts_code or "机构专用" not in seat_name:
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continue
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group = grouped.setdefault(
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(trade_date, ts_code),
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{"net": 0.0, "buy": 0.0, "sell": 0.0, "seats": 0},
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)
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group["net"] = float(group["net"]) + float(row.get("net_buy") or row.get("net_amount") or 0)
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group["buy"] = float(group["buy"]) + float(row.get("buy") or row.get("buy_amount") or 0)
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group["sell"] = float(group["sell"]) + float(row.get("sell") or row.get("sell_amount") or 0)
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group["seats"] = int(group["seats"]) + 1
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values = [
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(trade_date, ts_code, item["net"], item["buy"], item["sell"], item["seats"])
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for (trade_date, ts_code), item in grouped.items()
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]
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with self.connect() as connection:
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connection.executemany(
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"""
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INSERT INTO lhb_institution_daily
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(trade_date, ts_code, net_buy_amount, buy_amount, sell_amount, seat_count)
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VALUES (?, ?, ?, ?, ?, ?)
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ON CONFLICT(trade_date, ts_code) DO UPDATE SET
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net_buy_amount=excluded.net_buy_amount,
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buy_amount=excluded.buy_amount,
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sell_amount=excluded.sell_amount,
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seat_count=excluded.seat_count
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""",
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values,
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)
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return len(values)
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@@ -0,0 +1,288 @@
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from __future__ import annotations
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from datetime import datetime
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from typing import Any
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from backend.bootstrap.config import normalize_date
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from backend.data.providers.tushare_client import TushareError
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class DragonTigerServiceMixin:
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def get_hot_money_profiles(self, force: bool = False) -> dict[str, Any]:
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cache_kind = "hot_money_profiles_v1"
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cache_key = "directory"
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cached = self.database.get_data_snapshot(cache_kind, cache_key)
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if cached and not force:
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cached["meta"] = {**cached.get("meta", {}), "cached": True}
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return cached
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if self.configured:
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try:
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payload = self._tushare_client().hot_money_profiles()
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except TushareError:
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if cached:
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cached["meta"] = {
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**cached.get("meta", {}),
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"cached": True,
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"stale": True,
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"notice": "名录暂未完成更新，当前展示最近一次收录结果。",
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}
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return cached
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return {
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"meta": {
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"source": "unavailable",
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"status": "unavailable",
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"schema_version": 1,
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"cached": False,
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"updated_at": datetime.now().astimezone().isoformat(timespec="seconds"),
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"notice": "游资名录暂不可用，请稍后重试。",
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},
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"summary": {
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"profile_count": 0,
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"described_count": 0,
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"organization_count": 0,
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},
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"profiles": [],
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}
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payload["meta"]["cached"] = False
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if payload.get("meta", {}).get("status") == "success":
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self.database.save_data_snapshot(cache_kind, cache_key, "tushare", payload)
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return payload
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if cached:
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cached["meta"] = {**cached.get("meta", {}), "cached": True}
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return cached
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return {
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"meta": {
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"source": "unavailable",
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"status": "unavailable",
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"schema_version": 1,
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"cached": False,
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"updated_at": datetime.now().astimezone().isoformat(timespec="seconds"),
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"notice": "游资名录暂不可用，请联系管理员检查行情配置。",
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},
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"summary": {
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"profile_count": 0,
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"described_count": 0,
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"organization_count": 0,
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},
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"profiles": [],
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}
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def get_dragon_tiger(self, trade_date: str, force: bool = False) -> dict[str, Any]:
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normalized_date = normalize_date(trade_date)
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cache_kind = "hot_money_detail_v3"
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if not force:
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cached = self.database.get_data_snapshot(cache_kind, normalized_date)
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if (
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cached
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and cached.get("meta", {}).get("source") == "tushare"
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and cached.get("meta", {}).get("status") == "success"
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and int(cached.get("meta", {}).get("schema_version") or 0) == 3
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):
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cached["meta"] = {**cached.get("meta", {}), "cached": True}
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return cached
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if self.configured:
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try:
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payload = self._tushare_client().dragon_tiger(normalized_date)
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except TushareError as exc:
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return {
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"meta": {
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"requested_date": f"{normalized_date[:4]}-{normalized_date[4:6]}-{normalized_date[6:8]}",
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"trade_date": f"{normalized_date[:4]}-{normalized_date[4:6]}-{normalized_date[6:8]}",
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"source": "tushare_error",
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"status": "error",
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"schema_version": 3,
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"cached": False,
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"updated_at": datetime.now().astimezone().isoformat(timespec="seconds"),
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"notice": "龙虎榜数据暂不可用，请稍后重试。",
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},
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"summary": {
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"trader_count": 0,
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"identity_count": 0,
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"operation_count": 0,
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"active_stock_count": 0,
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"seat_net_buy_million": 0,
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"unclassified_count": 0,
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"directory_count": 0,
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},
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"traders": [],
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"unclassified_seats": [],
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"rows": [],
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}
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payload["meta"]["cached"] = False
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if payload.get("meta", {}).get("status") == "success":
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self.database.save_data_snapshot(cache_kind, normalized_date, "tushare", payload)
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return payload
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return {
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"meta": {
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"requested_date": f"{normalized_date[:4]}-{normalized_date[4:6]}-{normalized_date[6:8]}",
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"trade_date": f"{normalized_date[:4]}-{normalized_date[4:6]}-{normalized_date[6:8]}",
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"source": "unavailable",
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"status": "unavailable",
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"schema_version": 3,
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"cached": False,
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"notice": "龙虎榜数据暂不可用，请联系管理员检查行情配置。",
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},
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"summary": {
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"trader_count": 0,
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"identity_count": 0,
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"operation_count": 0,
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"active_stock_count": 0,
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"seat_net_buy_million": 0,
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"unclassified_count": 0,
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"directory_count": 0,
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},
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"traders": [],
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"unclassified_seats": [],
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"rows": [],
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}
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def _apply_seat_aliases(self, payload: dict[str, Any]) -> dict[str, Any]:
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aliases = self.database.list_seat_aliases()
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result = dict(payload)
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rows = payload.get("rows") or []
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for row in rows:
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for institution in row.get("institutions") or []:
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institution["alias"] = aliases.get(institution.get("seat_name", ""), "")
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traders: dict[tuple[str, str], dict[str, Any]] = {}
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unclassified: dict[str, dict[str, Any]] = {}
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seen_operations: set[tuple[Any, ...]] = set()
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builtin_aliases = {
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"国泰海通证券股份有限公司南京太平南路证券营业部": "作手新一",
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}
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for row in rows:
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for institution in row.get("institutions") or []:
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seat_name = str(institution.get("seat_name") or "未知席位").strip()
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saved_alias = str(institution.get("alias") or "").strip()
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builtin_alias = builtin_aliases.get(seat_name, "")
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if saved_alias or builtin_alias:
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identity_name = saved_alias or builtin_alias
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identity_type = "trader"
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recognized = True
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identity_source = "manual" if saved_alias else "builtin"
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elif "机构专用" in seat_name:
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identity_name = "机构专用"
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identity_type = "institution"
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recognized = True
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identity_source = "system"
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elif "沪股通专用" in seat_name or "深股通专用" in seat_name:
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identity_name = "北向资金"
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identity_type = "channel"
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recognized = True
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identity_source = "system"
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else:
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identity_name = seat_name
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identity_type = "unclassified"
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recognized = False
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identity_source = "raw"
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buy = round(float(institution.get("buy_million") or 0), 2)
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sell = round(float(institution.get("sell_million") or 0), 2)
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net_buy = round(float(institution.get("net_buy_million") or 0), 2)
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operation_key = (row.get("code"), seat_name, buy, sell, net_buy)
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if operation_key in seen_operations:
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continue
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seen_operations.add(operation_key)
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group_key = (identity_type, identity_name)
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group = traders.setdefault(
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group_key,
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{
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"name": identity_name,
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"identity_type": identity_type,
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"identity_source": identity_source,
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"recognized": recognized,
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"buy_million": 0.0,
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"sell_million": 0.0,
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"net_buy_million": 0.0,
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"seat_names": set(),
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"stock_codes": set(),
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"operations": [],
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},
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)
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group["buy_million"] += buy
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group["sell_million"] += sell
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group["net_buy_million"] += net_buy
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group["seat_names"].add(seat_name)
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group["stock_codes"].add(str(row.get("code") or ""))
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group["operations"].append(
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{
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"code": row.get("code") or "",
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"name": row.get("name") or "--",
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"change": row.get("change") or 0,
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"direction": "买入" if net_buy > 0 else "卖出" if net_buy < 0 else "持平",
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"buy_million": buy,
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"sell_million": sell,
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"net_buy_million": net_buy,
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"reason": row.get("reason") or "--",
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"seat_name": seat_name,
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"seat_alias": identity_name if recognized else "",
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}
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)
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if not recognized:
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pending = unclassified.setdefault(
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seat_name,
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{
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"seat_name": seat_name,
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"stock_codes": set(),
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"operation_count": 0,
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"buy_million": 0.0,
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"sell_million": 0.0,
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"net_buy_million": 0.0,
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},
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)
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pending["stock_codes"].add(str(row.get("code") or ""))
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pending["operation_count"] += 1
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pending["buy_million"] += buy
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pending["sell_million"] += sell
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pending["net_buy_million"] += net_buy
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type_order = {"trader": 0, "institution": 1, "channel": 2, "unclassified": 3}
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aggregated = list(traders.values())
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aggregated.sort(
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key=lambda item: (
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type_order.get(item["identity_type"], 9),
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-abs(item["net_buy_million"]),
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item["name"],
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)
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)
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for index, group in enumerate(aggregated, start=1):
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group["id"] = f"identity-{index}"
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group["buy_million"] = round(group["buy_million"], 2)
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group["sell_million"] = round(group["sell_million"], 2)
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group["net_buy_million"] = round(group["net_buy_million"], 2)
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group["seat_count"] = len(group.pop("seat_names"))
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group["stock_count"] = len(group.pop("stock_codes"))
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group["operation_count"] = len(group["operations"])
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group["operations"].sort(
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key=lambda item: abs(float(item.get("net_buy_million") or 0)), reverse=True
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)
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pending_seats = list(unclassified.values())
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for pending in pending_seats:
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pending["stock_count"] = len(pending.pop("stock_codes"))
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pending["buy_million"] = round(pending["buy_million"], 2)
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pending["sell_million"] = round(pending["sell_million"], 2)
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pending["net_buy_million"] = round(pending["net_buy_million"], 2)
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pending_seats.sort(key=lambda item: abs(item["net_buy_million"]), reverse=True)
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operation_count = sum(item["operation_count"] for item in aggregated)
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active_stocks = {
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operation["code"] for item in aggregated for operation in item["operations"]
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}
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seat_net_buy = round(sum(item["net_buy_million"] for item in aggregated), 2)
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result["rows"] = rows
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result["traders"] = aggregated
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result["unclassified_seats"] = pending_seats
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result["summary"] = {
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**(payload.get("summary") or {}),
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"trader_count": sum(item["identity_type"] == "trader" for item in aggregated),
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"identity_count": len(aggregated),
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"operation_count": operation_count,
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"active_stock_count": len(active_stocks),
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"seat_net_buy_million": seat_net_buy,
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"unclassified_count": len(pending_seats),
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}
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return result
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