rebuild(stage-9): deliver deterministic intelligent screening
This commit is contained in:
leefer
@@ -0,0 +1,448 @@
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from __future__ import annotations
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import json
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import sqlite3
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from datetime import datetime
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from typing import Any
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class ScreenerRepository:
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def save_factor_snapshot(
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self,
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connection: sqlite3.Connection,
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*,
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trade_date: str,
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version: str,
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observed_at: str,
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state: str,
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sources: list[str],
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coverage: dict[str, float],
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rows: list[dict[str, Any]],
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) -> int:
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connection.execute(
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"""
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INSERT OR IGNORE INTO screener_factor_snapshots (
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trade_date, version, observed_at, state, source_set_json,
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coverage_json, created_at
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) VALUES (?, ?, ?, ?, ?, ?, ?)
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""",
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(
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trade_date,
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version,
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observed_at,
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state,
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_json(sources),
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_json(coverage),
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_now(),
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),
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)
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snapshot = connection.execute(
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"""
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SELECT id FROM screener_factor_snapshots
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WHERE trade_date = ? AND version = ?
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""",
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(trade_date, version),
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).fetchone()
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if snapshot is None:
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raise RuntimeError("因子快照写入失败")
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snapshot_id = int(snapshot["id"])
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connection.executemany(
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"""
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INSERT OR REPLACE INTO screener_factor_values (
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snapshot_id, identifier, code, name, sector,
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listed_days, is_st, payload_json
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) VALUES (?, ?, ?, ?, ?, ?, ?, ?)
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""",
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(
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(
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snapshot_id,
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row["identifier"],
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row["code"],
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row["name"],
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row.get("sector"),
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int(row.get("listed_days") or 0),
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int(bool(row.get("is_st"))),
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_json(row),
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)
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for row in rows
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),
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)
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return snapshot_id
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def latest_factor_snapshot(
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self, connection: sqlite3.Connection, through: str
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) -> sqlite3.Row | None:
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return connection.execute(
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"""
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SELECT * FROM screener_factor_snapshots
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WHERE trade_date <= ? ORDER BY trade_date DESC, id DESC LIMIT 1
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""",
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(through,),
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).fetchone()
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def factor_snapshot(
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self, connection: sqlite3.Connection, snapshot_id: int
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) -> sqlite3.Row | None:
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return connection.execute(
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"SELECT * FROM screener_factor_snapshots WHERE id = ?",
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(snapshot_id,),
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).fetchone()
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def factor_rows(self, connection: sqlite3.Connection, snapshot_id: int) -> list[dict[str, Any]]:
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return [
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json.loads(str(row["payload_json"]))
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for row in connection.execute(
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"""
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SELECT payload_json FROM screener_factor_values
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WHERE snapshot_id = ? ORDER BY identifier
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""",
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(snapshot_id,),
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).fetchall()
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]
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def begin_run(
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self,
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connection: sqlite3.Connection,
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*,
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owner_user_id: int | None,
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mode: str,
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strategy_id: str,
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strategy_name: str,
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strategy_version: int,
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selection_date: str,
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factor_snapshot_id: int,
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) -> sqlite3.Row:
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connection.execute(
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"""
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INSERT OR IGNORE INTO screener_runs (
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owner_user_id, mode, strategy_id, strategy_name,
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strategy_version, selection_date, factor_snapshot_id,
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status, started_at
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) VALUES (?, ?, ?, ?, ?, ?, ?, 'running', ?)
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""",
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(
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owner_user_id,
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mode,
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strategy_id,
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strategy_name,
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strategy_version,
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selection_date,
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factor_snapshot_id,
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_now(),
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),
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)
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row = connection.execute(
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"""
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SELECT * FROM screener_runs
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WHERE mode = ? AND strategy_id = ? AND selection_date = ?
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AND strategy_version = ? AND factor_snapshot_id = ?
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AND COALESCE(owner_user_id, 0) = COALESCE(?, 0)
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""",
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(
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mode,
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strategy_id,
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selection_date,
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strategy_version,
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factor_snapshot_id,
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owner_user_id,
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),
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).fetchone()
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if row is None:
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raise RuntimeError("选股任务写入失败")
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return row
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def finish_run(
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self,
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connection: sqlite3.Connection,
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run_id: int,
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*,
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status: str,
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coverage: float,
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missing_fields: list[str],
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result: list[dict[str, Any]],
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error_message: str = "",
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) -> None:
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connection.execute(
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"""
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UPDATE screener_runs SET
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status = ?, completed_at = ?, coverage = ?,
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missing_fields_json = ?, result_json = ?, error_message = ?
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WHERE id = ?
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""",
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(
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status,
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_now(),
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max(0, min(coverage, 1)),
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_json(missing_fields),
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_json(result),
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error_message,
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run_id,
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),
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)
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def latest_runs(
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self,
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connection: sqlite3.Connection,
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mode: str,
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through: str,
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owner_user_id: int | None = None,
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) -> tuple[sqlite3.Row, ...]:
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return tuple(
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connection.execute(
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"""
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SELECT run.* FROM screener_runs run
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JOIN (
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SELECT strategy_id, MAX(id) AS latest_id
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FROM screener_runs
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WHERE mode = ? AND selection_date = ?
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AND COALESCE(owner_user_id, 0) = COALESCE(?, 0)
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GROUP BY strategy_id
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) latest ON latest.latest_id = run.id
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ORDER BY run.strategy_id
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""",
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(mode, through, owner_user_id),
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).fetchall()
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)
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def run_for_user(
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self, connection: sqlite3.Connection, run_id: int, user_id: int
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) -> sqlite3.Row | None:
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return connection.execute(
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"""
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SELECT * FROM screener_runs
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WHERE id = ? AND (owner_user_id IS NULL OR owner_user_id = ?)
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""",
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(run_id, user_id),
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).fetchone()
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def save_custom_strategy(
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self,
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connection: sqlite3.Connection,
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user_id: int,
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name: str,
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formula: dict[str, Any],
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) -> sqlite3.Row:
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now = _now()
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connection.execute(
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"""
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INSERT INTO custom_screener_strategies (
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user_id, name, version, formula_json, created_at, updated_at
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) VALUES (?, ?, 1, ?, ?, ?)
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ON CONFLICT(user_id, name) DO UPDATE SET
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version = version + 1,
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formula_json = excluded.formula_json,
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updated_at = excluded.updated_at
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""",
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(user_id, name, _json(formula), now, now),
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)
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row = connection.execute(
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"""
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SELECT * FROM custom_screener_strategies
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WHERE user_id = ? AND name = ?
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""",
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(user_id, name),
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).fetchone()
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if row is None:
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raise RuntimeError("自定义策略写入失败")
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return row
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def custom_strategies(
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self, connection: sqlite3.Connection, user_id: int
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) -> tuple[sqlite3.Row, ...]:
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return tuple(
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connection.execute(
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"""
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SELECT * FROM custom_screener_strategies
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WHERE user_id = ? ORDER BY updated_at DESC, id DESC
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""",
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(user_id,),
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).fetchall()
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)
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def custom_strategy(
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self, connection: sqlite3.Connection, user_id: int, strategy_id: int
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) -> sqlite3.Row | None:
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return connection.execute(
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"""
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SELECT * FROM custom_screener_strategies
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WHERE id = ? AND user_id = ?
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""",
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(strategy_id, user_id),
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).fetchone()
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def delete_custom_strategy(
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self, connection: sqlite3.Connection, user_id: int, strategy_id: int
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) -> bool:
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cursor = connection.execute(
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"DELETE FROM custom_screener_strategies WHERE id = ? AND user_id = ?",
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(strategy_id, user_id),
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)
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return cursor.rowcount > 0
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def add_track(
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self,
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connection: sqlite3.Connection,
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*,
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user_id: int,
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run: sqlite3.Row,
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candidate: dict[str, Any],
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) -> int:
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connection.execute(
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"""
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INSERT OR IGNORE INTO strategy_tracks (
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user_id, run_id, identifier, code, name, sector,
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selection_date, strategy_name, entry_price, added_at
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) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
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""",
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(
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user_id,
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int(run["id"]),
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candidate["identifier"],
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candidate["code"],
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candidate["name"],
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candidate.get("sector"),
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str(run["selection_date"]),
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str(run["strategy_name"]),
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float(candidate["close"]),
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_now(),
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),
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)
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row = connection.execute(
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"""
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SELECT id FROM strategy_tracks
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WHERE user_id = ? AND run_id = ? AND identifier = ?
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""",
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(user_id, int(run["id"]), candidate["identifier"]),
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).fetchone()
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if row is None:
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raise RuntimeError("策略跟踪写入失败")
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return int(row["id"])
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def tracks(self, connection: sqlite3.Connection, user_id: int) -> tuple[sqlite3.Row, ...]:
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return tuple(
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connection.execute(
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"""
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SELECT track.*, run.mode, run.strategy_id
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FROM strategy_tracks track
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JOIN screener_runs run ON run.id = track.run_id
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WHERE track.user_id = ? ORDER BY track.added_at DESC, track.id DESC
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""",
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(user_id,),
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).fetchall()
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)
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def track_bars(self, connection: sqlite3.Connection, track_id: int) -> tuple[sqlite3.Row, ...]:
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return tuple(
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connection.execute(
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"""
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SELECT * FROM strategy_track_bars
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WHERE track_id = ? ORDER BY trade_date
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""",
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(track_id,),
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).fetchall()
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)
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def tracked_before(
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self, connection: sqlite3.Connection, trade_date: str
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) -> tuple[sqlite3.Row, ...]:
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return tuple(
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connection.execute(
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"""
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SELECT * FROM strategy_tracks
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WHERE selection_date < ? ORDER BY id
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""",
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(trade_date,),
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).fetchall()
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)
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def save_track_bar(
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self,
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connection: sqlite3.Connection,
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track_id: int,
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trade_date: str,
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row: dict[str, Any],
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) -> None:
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connection.execute(
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"""
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INSERT INTO strategy_track_bars (
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track_id, trade_date, open, high, low, close
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) VALUES (?, ?, ?, ?, ?, ?)
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ON CONFLICT(track_id, trade_date) DO UPDATE SET
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open = excluded.open,
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high = excluded.high,
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low = excluded.low,
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close = excluded.close
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""",
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(
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track_id,
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trade_date,
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float(row["open"]),
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float(row["high"]),
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float(row["low"]),
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float(row["close"]),
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),
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)
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def record_track_event(
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self, connection: sqlite3.Connection, track_id: int, milestone: str
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) -> bool:
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cursor = connection.execute(
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"""
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INSERT OR IGNORE INTO strategy_track_events (track_id, milestone, created_at)
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VALUES (?, ?, ?)
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""",
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(track_id, milestone, _now()),
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)
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return cursor.rowcount > 0
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def remove_track(self, connection: sqlite3.Connection, user_id: int, track_id: int) -> bool:
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cursor = connection.execute(
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"DELETE FROM strategy_tracks WHERE id = ? AND user_id = ?",
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(track_id, user_id),
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)
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return cursor.rowcount > 0
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def decode_run(row: sqlite3.Row | None) -> dict[str, Any] | None:
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if row is None:
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return None
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result = dict(row)
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result["missing_fields"] = json.loads(str(row["missing_fields_json"]))
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result["items"] = json.loads(str(row["result_json"]))
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result.pop("missing_fields_json", None)
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result.pop("result_json", None)
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return result
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def decode_custom(row: sqlite3.Row) -> dict[str, Any]:
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result = dict(row)
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result["formula"] = json.loads(str(row["formula_json"]))
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result.pop("formula_json", None)
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return result
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def decode_track(row: sqlite3.Row, bars: tuple[sqlite3.Row, ...]) -> dict[str, Any]:
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result = dict(row)
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entry = float(row["entry_price"])
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closes = [float(item["close"]) for item in bars]
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highs = [float(item["high"]) for item in bars]
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lows = [float(item["low"]) for item in bars]
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result["t1_open_return"] = (
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round((float(bars[0]["open"]) / entry - 1) * 100, 2) if bars else None
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)
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for index in (1, 3, 5):
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result[f"t{index}_return"] = (
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round((closes[index - 1] / entry - 1) * 100, 2) if len(closes) >= index else None
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)
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result["max_gain"] = round((max(highs) / entry - 1) * 100, 2) if highs else None
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result["max_drawdown"] = round((min(lows) / entry - 1) * 100, 2) if lows else None
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result["observed_days"] = len(bars)
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return result
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def _json(value: Any) -> str:
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return json.dumps(value, ensure_ascii=False, separators=(",", ":"), sort_keys=True)
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def _now() -> str:
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return datetime.now().astimezone().isoformat(timespec="seconds")
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Reference in New Issue
Block a user