Normalize fullwidth punctuation to ASCII across codebase.
Add scripts/normalize_ambiguous_unicode.py; fix corrupted patch_instance_theme_templates.py. Preserves curly quotes in string literals; removes Git homoglyph warnings on .env.example. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
dekun
@@ -1,155 +1,155 @@
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"""embed 壳/片段：按 tab 裁剪 render_main_page 的数据加载，降内存与 API 压力。"""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any
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EMBED_STRATEGY_PAGES = frozenset({"strategy", "strategy_trend", "strategy_roll", "strategy_records"})
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_WIN_EPS = 1e-9
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@dataclass(frozen=True)
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class EmbedRenderPlan:
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exchange_capitals: bool
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records_rows: bool
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records_summary: bool
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key_history: bool
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key_list: bool
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orders: bool
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stats_bundle: bool
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strategy: bool
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orphan_live: bool
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def embed_render_plan(page: str, embed_mode: str | None) -> EmbedRenderPlan:
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if embed_mode not in ("fragment", "shell"):
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return EmbedRenderPlan(
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exchange_capitals=True,
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records_rows=True,
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records_summary=False,
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key_history=True,
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key_list=True,
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orders=True,
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stats_bundle=True,
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strategy=True,
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orphan_live=True,
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)
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is_shell = embed_mode == "shell"
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is_strategy = page in EMBED_STRATEGY_PAGES
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is_settings_like = page in ("settings", "risk_policy", "env_config")
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return EmbedRenderPlan(
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exchange_capitals=is_shell,
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records_rows=page == "records",
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records_summary=is_shell and page != "records" and not is_settings_like,
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key_history=page == "key_monitor",
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key_list=page in ("key_monitor", "trade") or is_strategy,
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orders=page == "trade" or is_strategy,
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stats_bundle=page == "stats",
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strategy=is_strategy,
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orphan_live=page == "trade" and is_shell,
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)
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def profit_loss_ratio_from_averages(avg_win: float | None, avg_loss: float | None) -> float | None:
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"""盈亏比 = 平均盈利 / |平均亏损|。"""
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if avg_win is None or avg_loss is None:
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return None
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try:
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aw = float(avg_win)
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al = float(avg_loss)
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except (TypeError, ValueError):
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return None
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if al == 0:
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return None
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return round(aw / abs(al), 2)
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def profit_loss_ratio_from_trades(trades: list[dict[str, Any]] | None) -> float | None:
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wins: list[float] = []
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losses: list[float] = []
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for row in trades or []:
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if not isinstance(row, dict):
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continue
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try:
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pnl = float(row.get("effective_pnl_amount") or row.get("pnl_amount") or 0)
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except (TypeError, ValueError):
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continue
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if pnl > _WIN_EPS:
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wins.append(pnl)
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elif pnl < -_WIN_EPS:
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losses.append(pnl)
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avg_win = sum(wins) / len(wins) if wins else None
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avg_loss = sum(losses) / len(losses) if losses else None
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return profit_loss_ratio_from_averages(avg_win, avg_loss)
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def options_funding_label(
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funding_usdc: float | None,
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funding_usdt: float | None = None,
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) -> str:
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parts: list[str] = []
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if funding_usdc is not None:
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parts.append(f"{float(funding_usdc):.2f} USDC")
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if funding_usdt is not None:
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parts.append(f"{float(funding_usdt):.2f} USDT")
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return " · ".join(parts) if parts else "—"
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def total_funds_usdt(
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funding_usdt: float | None,
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trading_usdt: float | None,
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options_trading_usdc: float | None = None,
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options_funding_usdc: float | None = None,
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options_funding_usdt: float | None = None,
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) -> float | None:
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if funding_usdt is None:
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return None
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try:
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total = float(funding_usdt) + float(trading_usdt or 0)
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if options_funding_usdc is not None:
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total += float(options_funding_usdc)
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if options_funding_usdt is not None:
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total += float(options_funding_usdt)
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if options_trading_usdc is not None:
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total += float(options_trading_usdc)
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return round(total, 2)
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except (TypeError, ValueError):
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return None
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def trade_records_summary(conn, start_bj: str, end_bj: str, tr_ts: str) -> dict[str, Any]:
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"""顶栏统计用 COUNT，避免 embed 壳拉 1000 行交易记录。"""
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from lib.trade.trade_result_lib import sql_effective_pnl_expr
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pnl_sql = sql_effective_pnl_expr()
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row = conn.execute(
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f"""
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SELECT
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COUNT(*) AS total,
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SUM(CASE WHEN {pnl_sql} > 0 THEN 1 ELSE 0 END) AS wins,
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AVG(CASE WHEN {pnl_sql} > 0 THEN {pnl_sql} END) AS avg_win,
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AVG(CASE WHEN {pnl_sql} < 0 THEN {pnl_sql} END) AS avg_loss
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FROM trade_records
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WHERE {tr_ts} >= ? AND {tr_ts} <= ?
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AND COALESCE(result, '') != '错过'
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AND COALESCE(reviewed_result, '') != '错过'
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""",
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(start_bj, end_bj),
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).fetchone()
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total = int(row["total"] or 0) if row else 0
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wins = int(row["wins"] or 0) if row else 0
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rate = round(wins / total * 100, 2) if total else 0
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avg_win = float(row["avg_win"]) if row and row["avg_win"] is not None else None
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avg_loss = float(row["avg_loss"]) if row and row["avg_loss"] is not None else None
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return {
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"records": [],
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"total": total,
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"rate": rate,
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"profit_loss_ratio": profit_loss_ratio_from_averages(avg_win, avg_loss),
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}
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def minimal_stats_bundle(reset_hour: int) -> dict[str, Any]:
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return {"stats_reset_hour": reset_hour, "segments": []}
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"""embed 壳/片段:按 tab 裁剪 render_main_page 的数据加载,降内存与 API 压力."""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any
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EMBED_STRATEGY_PAGES = frozenset({"strategy", "strategy_trend", "strategy_roll", "strategy_records"})
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_WIN_EPS = 1e-9
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@dataclass(frozen=True)
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class EmbedRenderPlan:
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exchange_capitals: bool
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records_rows: bool
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records_summary: bool
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key_history: bool
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key_list: bool
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orders: bool
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stats_bundle: bool
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strategy: bool
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orphan_live: bool
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def embed_render_plan(page: str, embed_mode: str | None) -> EmbedRenderPlan:
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if embed_mode not in ("fragment", "shell"):
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return EmbedRenderPlan(
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exchange_capitals=True,
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records_rows=True,
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records_summary=False,
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key_history=True,
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key_list=True,
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orders=True,
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stats_bundle=True,
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strategy=True,
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orphan_live=True,
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)
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is_shell = embed_mode == "shell"
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is_strategy = page in EMBED_STRATEGY_PAGES
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is_settings_like = page in ("settings", "risk_policy", "env_config")
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return EmbedRenderPlan(
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exchange_capitals=is_shell,
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records_rows=page == "records",
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records_summary=is_shell and page != "records" and not is_settings_like,
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key_history=page == "key_monitor",
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key_list=page in ("key_monitor", "trade") or is_strategy,
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orders=page == "trade" or is_strategy,
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stats_bundle=page == "stats",
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strategy=is_strategy,
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orphan_live=page == "trade" and is_shell,
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)
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def profit_loss_ratio_from_averages(avg_win: float | None, avg_loss: float | None) -> float | None:
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"""盈亏比 = 平均盈利 / |平均亏损|."""
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if avg_win is None or avg_loss is None:
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return None
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try:
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aw = float(avg_win)
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al = float(avg_loss)
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except (TypeError, ValueError):
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return None
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if al == 0:
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return None
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return round(aw / abs(al), 2)
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def profit_loss_ratio_from_trades(trades: list[dict[str, Any]] | None) -> float | None:
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wins: list[float] = []
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losses: list[float] = []
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for row in trades or []:
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if not isinstance(row, dict):
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continue
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try:
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pnl = float(row.get("effective_pnl_amount") or row.get("pnl_amount") or 0)
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except (TypeError, ValueError):
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continue
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if pnl > _WIN_EPS:
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wins.append(pnl)
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elif pnl < -_WIN_EPS:
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losses.append(pnl)
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avg_win = sum(wins) / len(wins) if wins else None
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avg_loss = sum(losses) / len(losses) if losses else None
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return profit_loss_ratio_from_averages(avg_win, avg_loss)
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def options_funding_label(
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funding_usdc: float | None,
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funding_usdt: float | None = None,
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) -> str:
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parts: list[str] = []
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if funding_usdc is not None:
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parts.append(f"{float(funding_usdc):.2f} USDC")
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if funding_usdt is not None:
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parts.append(f"{float(funding_usdt):.2f} USDT")
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return " · ".join(parts) if parts else "—"
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def total_funds_usdt(
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funding_usdt: float | None,
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trading_usdt: float | None,
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options_trading_usdc: float | None = None,
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options_funding_usdc: float | None = None,
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options_funding_usdt: float | None = None,
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) -> float | None:
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if funding_usdt is None:
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return None
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try:
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total = float(funding_usdt) + float(trading_usdt or 0)
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if options_funding_usdc is not None:
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total += float(options_funding_usdc)
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if options_funding_usdt is not None:
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total += float(options_funding_usdt)
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if options_trading_usdc is not None:
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total += float(options_trading_usdc)
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return round(total, 2)
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except (TypeError, ValueError):
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return None
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def trade_records_summary(conn, start_bj: str, end_bj: str, tr_ts: str) -> dict[str, Any]:
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"""顶栏统计用 COUNT,避免 embed 壳拉 1000 行交易记录."""
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from lib.trade.trade_result_lib import sql_effective_pnl_expr
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pnl_sql = sql_effective_pnl_expr()
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row = conn.execute(
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f"""
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SELECT
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COUNT(*) AS total,
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SUM(CASE WHEN {pnl_sql} > 0 THEN 1 ELSE 0 END) AS wins,
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AVG(CASE WHEN {pnl_sql} > 0 THEN {pnl_sql} END) AS avg_win,
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AVG(CASE WHEN {pnl_sql} < 0 THEN {pnl_sql} END) AS avg_loss
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FROM trade_records
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WHERE {tr_ts} >= ? AND {tr_ts} <= ?
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AND COALESCE(result, '') != '错过'
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AND COALESCE(reviewed_result, '') != '错过'
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""",
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(start_bj, end_bj),
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).fetchone()
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total = int(row["total"] or 0) if row else 0
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wins = int(row["wins"] or 0) if row else 0
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rate = round(wins / total * 100, 2) if total else 0
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avg_win = float(row["avg_win"]) if row and row["avg_win"] is not None else None
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avg_loss = float(row["avg_loss"]) if row and row["avg_loss"] is not None else None
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return {
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"records": [],
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"total": total,
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"rate": rate,
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"profit_loss_ratio": profit_loss_ratio_from_averages(avg_win, avg_loss),
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}
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def minimal_stats_bundle(reset_hour: int) -> dict[str, Any]:
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return {"stats_reset_hour": reset_hour, "segments": []}
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