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feat: 内照明心交易日历与交易所口径成交额/手续费统计

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新增按 08:00 切日的月历（盈亏、笔数、犯病日高亮与点击筛选）；平仓时从交易所 fill 写入双边成交额与手续费，统计表与明细同步展示。

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
dekun
2026-06-30 08:05:46 +08:00
parent 865567fbd3
commit 6b872b1f43
13 changed files with 1113 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files
hub_symbol_archive_lib.py
+142 -5
View File
@@ -118,6 +118,8 @@ def init_db(db_path: Path | None = None) -> None:
closed_at_ms INTEGER,
monitor_type TEXT,
entry_reason TEXT,
exchange_turnover_usdt REAL,
exchange_commission_usdt REAL,
payload_json TEXT,
synced_at INTEGER NOT NULL,
PRIMARY KEY (exchange_key, trade_id)
@@ -159,6 +161,14 @@ def init_db(db_path: Path | None = None) -> None:
ON archive_review_quotes (quote_date DESC)
"""
)
for ddl in (
"ALTER TABLE archive_trade_cache ADD COLUMN exchange_turnover_usdt REAL",
"ALTER TABLE archive_trade_cache ADD COLUMN exchange_commission_usdt REAL",
):
try:
conn.execute(ddl)
except Exception:
pass
finally:
conn.close()
@@ -167,6 +177,15 @@ def _now_ms() -> int:
return int(time.time() * 1000)
def _optional_float(raw: Any) -> float | None:
if raw in (None, ""):
return None
try:
return float(raw)
except (TypeError, ValueError):
return None
def parse_wall_clock_ms(raw: Any, *, tz: ZoneInfo = CHART_DISPLAY_TZ) -> int | None:
"""将 YYYY-MM-DD[ HH:MM[:SS]] 按指定时区墙钟解析为 UTC 毫秒（默认 UTC+8）。"""
if raw in (None, ""):
@@ -331,8 +350,9 @@ def upsert_trades_cache(
INSERT INTO archive_trade_cache (
exchange_key, trade_id, symbol, direction, result, pnl_amount,
opened_at, closed_at, opened_at_ms, closed_at_ms,
monitor_type, entry_reason, payload_json, synced_at
) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?)
monitor_type, entry_reason, exchange_turnover_usdt, exchange_commission_usdt,
payload_json, synced_at
) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)
ON CONFLICT(exchange_key, trade_id) DO UPDATE SET
symbol=excluded.symbol,
direction=excluded.direction,
@@ -344,6 +364,8 @@ def upsert_trades_cache(
closed_at_ms=excluded.closed_at_ms,
monitor_type=excluded.monitor_type,
entry_reason=excluded.entry_reason,
exchange_turnover_usdt=excluded.exchange_turnover_usdt,
exchange_commission_usdt=excluded.exchange_commission_usdt,
payload_json=excluded.payload_json,
synced_at=excluded.synced_at
""",
@@ -360,6 +382,8 @@ def upsert_trades_cache(
t.get("closed_at_ms") or _parse_dt_ms(t.get("closed_at")),
t.get("monitor_type"),
entry_label,
_optional_float(t.get("exchange_turnover_usdt")),
_optional_float(t.get("exchange_commission_usdt")),
json.dumps(payload, ensure_ascii=False, default=str),
now,
),
@@ -437,6 +461,8 @@ def _trade_row_to_dict(row: sqlite3.Row, overlay: dict | None = None) -> dict[st
"closed_at_ms",
"monitor_type",
"entry_reason",
"exchange_turnover_usdt",
"exchange_commission_usdt",
"synced_at",
):
if key in d and d[key] not in (None, ""):
@@ -1263,6 +1289,8 @@ def _empty_pnl_bucket() -> dict[str, Any]:
"sick_count": 0,
"pnl_total": 0.0,
"pnl_ex_sick": 0.0,
"turnover_total": 0.0,
"commission_total": 0.0,
"win_count": 0,
"loss_count": 0,
"avg_win": None,
@@ -1286,6 +1314,8 @@ def _finalize_pnl_bucket(bucket: dict[str, Any]) -> None:
bucket["max_loss"] = round(min(losses), 4) if losses else None
bucket["pnl_total"] = round(float(bucket.get("pnl_total") or 0), 4)
bucket["pnl_ex_sick"] = round(float(bucket.get("pnl_ex_sick") or 0), 4)
bucket["turnover_total"] = round(float(bucket.get("turnover_total") or 0), 4)
bucket["commission_total"] = round(float(bucket.get("commission_total") or 0), 4)
bucket["win_rate"] = round(win_count / open_count * 100, 1) if open_count else None
avg_win = bucket["avg_win"]
if avg_win is not None and avg_loss is not None and avg_loss != 0:
@@ -1294,9 +1324,18 @@ def _finalize_pnl_bucket(bucket: dict[str, Any]) -> None:
bucket["profit_loss_ratio"] = None
def _accumulate_trade_stat(bucket: dict[str, Any], *, pnl: float, is_sick: bool) -> None:
def _accumulate_trade_stat(
bucket: dict[str, Any],
*,
pnl: float,
is_sick: bool,
turnover: float = 0.0,
commission: float = 0.0,
) -> None:
bucket["open_count"] += 1
bucket["pnl_total"] += pnl
bucket["turnover_total"] += turnover
bucket["commission_total"] += commission
if is_sick:
bucket["sick_count"] += 1
else:
@@ -1316,10 +1355,16 @@ def _compute_period_stats(trade_rows: list[dict[str, Any]]) -> dict[str, Any]:
pnl = float(td_row.get("pnl_amount") or 0)
tag = str(td_row.get("behavior_tag") or "")
is_sick = tag == "sick"
_accumulate_trade_stat(total_bucket, pnl=pnl, is_sick=is_sick)
turnover = float(td_row.get("exchange_turnover_usdt") or 0)
commission = float(td_row.get("exchange_commission_usdt") or 0)
_accumulate_trade_stat(
total_bucket, pnl=pnl, is_sick=is_sick, turnover=turnover, commission=commission
)
if ex not in by_ex:
by_ex[ex] = _empty_pnl_bucket()
_accumulate_trade_stat(by_ex[ex], pnl=pnl, is_sick=is_sick)
_accumulate_trade_stat(
by_ex[ex], pnl=pnl, is_sick=is_sick, turnover=turnover, commission=commission
)
_finalize_pnl_bucket(total_bucket)
for ex in by_ex:
_finalize_pnl_bucket(by_ex[ex])
@@ -1340,6 +1385,8 @@ def _compute_period_stats(trade_rows: list[dict[str, Any]]) -> dict[str, Any]:
"max_loss": total_bucket["max_loss"],
"win_rate": total_bucket["win_rate"],
"profit_loss_ratio": total_bucket["profit_loss_ratio"],
"turnover_total": total_bucket["turnover_total"],
"commission_total": total_bucket["commission_total"],
"by_exchange": by_ex,
}
@@ -1537,3 +1584,93 @@ def list_daily_trades(
}
finally:
conn.close()
def list_archive_calendar(
year: int,
month: int,
*,
exchange_key: str = "",
db_path: Path | None = None,
reset_hour: int = TRADING_DAY_RESET_HOUR,
) -> dict[str, Any]:
"""按月返回每个交易日的盈亏、笔数、犯病标记（08:00 切日）。"""
init_db(db_path)
y = int(year)
m = int(month)
if m < 1 or m > 12:
raise ValueError("month 无效")
first = f"{y:04d}-{m:02d}-01"
if m == 12:
next_first = datetime(y + 1, 1, 1)
else:
next_first = datetime(y, m + 1, 1)
last = (next_first - timedelta(days=1)).strftime("%Y-%m-%d")
start_ms, _ = trading_day_bounds_ms(first, reset_hour=reset_hour)
_, end_ms = trading_day_bounds_ms(last, reset_hour=reset_hour)
ex_filter = (exchange_key or "").strip().lower()
conn = _connect(db_path)
try:
params: list[Any] = [start_ms, end_ms]
where = "closed_at_ms IS NOT NULL AND closed_at_ms >= ? AND closed_at_ms < ?"
if ex_filter:
where += " AND exchange_key=?"
params.append(ex_filter)
rows = conn.execute(
f"SELECT * FROM archive_trade_cache WHERE {where}",
params,
).fetchall()
overlays_by_ex: dict[str, dict[int, dict]] = {}
days: dict[str, dict[str, Any]] = {}
for r in rows:
ex_k = r["exchange_key"]
if ex_k not in overlays_by_ex:
overlays_by_ex[ex_k] = load_overlays(ex_k, db_path=db_path)
td_row = _trade_row_to_dict(r, overlays_by_ex[ex_k].get(int(r["trade_id"])))
closed_ms = td_row.get("closed_at_ms") or _parse_dt_ms(td_row.get("closed_at"))
if not closed_ms:
continue
day = ms_to_trading_day(int(closed_ms), reset_hour=reset_hour)
if not day:
continue
if day < first or day > last:
continue
bucket = days.setdefault(
day,
{
"trading_day": day,
"open_count": 0,
"sick_count": 0,
"pnl_total": 0.0,
"turnover_total": 0.0,
"commission_total": 0.0,
"has_sick": False,
},
)
pnl = float(td_row.get("pnl_amount") or 0)
tag = str(td_row.get("behavior_tag") or "")
is_sick = tag == "sick"
bucket["open_count"] += 1
bucket["pnl_total"] += pnl
bucket["turnover_total"] += float(td_row.get("exchange_turnover_usdt") or 0)
bucket["commission_total"] += float(td_row.get("exchange_commission_usdt") or 0)
if is_sick:
bucket["sick_count"] += 1
bucket["has_sick"] = True
for d in days.values():
d["pnl_total"] = round(float(d["pnl_total"]), 4)
d["turnover_total"] = round(float(d["turnover_total"]), 4)
d["commission_total"] = round(float(d["commission_total"]), 4)
month_pnl = sum(float(d["pnl_total"]) for d in days.values())
month_count = sum(int(d["open_count"]) for d in days.values())
return {
"year": y,
"month": m,
"date_from": first,
"date_to": last,
"days": days,
"month_pnl_total": round(month_pnl, 4),
"month_open_count": month_count,
}
finally:
conn.close()