chemavxandClaude Fable 5
43d9577fb2
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sharpe_ratio was hardcoded to 0.0 in MetricsTracker and exposed as 'or 0' in /api/summary. With only 1 resolved trade (~40 flat days plus one +299 jump) any computed Sharpe is statistically meaningless, so: - bot/metrics/sharpe.py: annualized Sharpe (sqrt(365)) from daily total_pnl closes, normalized by bankroll; sharpe_with_gate() returns None + status until >=30 days observed AND >=10 resolved trades. - Database.get_daily_pnl_closes(): last metrics_daily snapshot per UTC day, oldest first — the return series input. - MetricsTracker: stores the real (gated) Sharpe in the snapshot, NULL below the gate; log line now includes sharpe. - /api/summary: live Sharpe + sharpe_status/days_observed/min_* fields explaining why it is null; resolved_count now live from COUNT(*). - promotion_ready: requires resolved>=10, days>=30, and non-null win_rate/calibration/sharpe plus existing thresholds — a single lucky resolved trade can no longer promote. - Dashboard Sharpe card shows the insufficient-sample explanation when null instead of a bare em dash. Tests: 13 new in tests/test_sharpe_gate.py (formula, gate, API contract, tracker snapshot); verified failing pre-fix. Suite: 62 passed. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
107 lines
3.4 KiB
Python
107 lines
3.4 KiB
Python
"""
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Tests for bug #7 — /api/summary must agree with the executor's cash model.
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Regression: /api/summary computed total_trades as len() over a LIMIT-500
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query (capped once history grows) and reimplemented cash as
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bankroll - sum(net_cost of open trades) from that same capped query.
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Fix: counts come from COUNT(*) (compute_metrics_from_db) and cash comes from
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cash_available() — the same helper PaperExecutor.initialize() uses — fed by
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the same source (get_open_position_data). This test runs both consumers
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against one fake DB state and asserts they report identical cash.
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"""
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import asyncio
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import pytest
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import api.main as api_main
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from bot.executor.paper import PaperExecutor, cash_available
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BANKROLL = 10_000.0 # PAPER_BANKROLL default used by both bot and API
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class FakeDB:
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"""One DB state served to both the API endpoint and the executor."""
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def __init__(self, positions: dict[str, float], total_net_cost: float,
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total_trades: int, open_count: int):
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self._positions = positions
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self._total_net_cost = total_net_cost
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self._total = total_trades
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self._open = open_count
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# Shared source: executor.initialize() and /api/summary both call this.
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async def get_open_position_data(self):
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return dict(self._positions), self._total_net_cost
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# /api/summary only:
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async def get_metrics_history(self, days=1):
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return []
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async def compute_metrics_from_db(self):
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return {
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"total_trades": self._total,
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"open_count": self._open,
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"closed_count": self._total - self._open,
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"resolved_count": 0,
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}
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async def get_recently_closed_inverted(self, hours=24):
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return set()
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async def get_legacy_incomplete_count(self):
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return 0
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async def get_daily_pnl_closes(self):
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return []
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def _run(db: FakeDB, monkeypatch) -> tuple[dict, PaperExecutor]:
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monkeypatch.setattr(api_main, "db", db)
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monkeypatch.delenv("PAPER_BANKROLL", raising=False)
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async def run():
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summary = await api_main.get_summary()
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ex = PaperExecutor(db=db, bankroll=BANKROLL)
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await ex.initialize()
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return summary, ex
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return asyncio.run(run())
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def test_api_and_executor_report_same_cash(monkeypatch):
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db = FakeDB(
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positions={"m1": 100.0, "m2": 80.0},
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total_net_cost=183.60, # 180 + fees
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total_trades=12,
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open_count=2,
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)
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summary, ex = _run(db, monkeypatch)
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assert summary["cash_available"] == pytest.approx(ex.get_portfolio().cash)
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assert summary["cash_available"] == pytest.approx(
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cash_available(BANKROLL, 183.60)
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)
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assert summary["total_deployed"] == pytest.approx(183.60)
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def test_total_trades_not_capped_by_query_limit(monkeypatch):
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"""700 trades in DB: the old len(LIMIT 500) reported 500."""
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db = FakeDB(
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positions={"m1": 100.0},
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total_net_cost=102.0,
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total_trades=700,
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open_count=1,
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)
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summary, _ = _run(db, monkeypatch)
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assert summary["total_trades"] == 700
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assert summary["open_trades_count"] == 1
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assert summary["closed_trades_count"] == 699
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def test_cash_consistency_with_no_open_positions(monkeypatch):
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db = FakeDB(positions={}, total_net_cost=0.0, total_trades=0, open_count=0)
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summary, ex = _run(db, monkeypatch)
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assert summary["cash_available"] == pytest.approx(BANKROLL)
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assert ex.get_portfolio().cash == pytest.approx(BANKROLL)
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