ebdcff5a6e
CI/CD / build-and-push (push) Successful in 2m23s
FASE 1 — market_family_key() general election fix
General elections now group by office, not by party, so complementary
markets ("Republicans win Ohio governor" / "Democrats win Ohio governor")
share the same family key (ohio-gubernatorial-2026). The second market
is blocked by the occupied_families check rather than traded as independent.
Primaries still keep the party (texas-republican-2026) because each party
runs its own separate primary race.
FASE 2 — Manifold party inversion guard
_detect_party() identifies the winning side in both the Polymarket question
and the matched Manifold title. If they are confirmed opposites (republican
vs democrat), the probability is inverted (1 - prob) before use.
Full audit log per query:
poly_question / manifold_title / manifold_url / match_score /
prob_raw / inverted / prob_final
Root cause of Ohio Manifold:0.95 on both sides: both queries matched the
same Manifold market ("Republicans win Ohio governor" prob=0.95). For the
"Democrats win" query the inversion now produces prob_final=0.05 instead of
blindly applying 0.95 to the wrong direction.
FASE 4 — startup contradiction scan
get_open_position_details() added to db.py. main.py checks all open
positions at startup, warns on any family with >1 position, and recommends
keeping the one with the highest edge_net. No auto-close.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
122 lines
5.2 KiB
Python
122 lines
5.2 KiB
Python
"""Database layer using asyncpg for PostgreSQL."""
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import logging
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import os
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from typing import Optional
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import asyncpg
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log = logging.getLogger(__name__)
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class Database:
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def __init__(self) -> None:
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self._url = os.getenv("DATABASE_URL", "postgresql://bot:bot@localhost:5432/polymarket")
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self._pool: Optional[asyncpg.Pool] = None
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async def connect(self) -> None:
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self._pool = await asyncpg.create_pool(self._url)
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log.info("Database connected")
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async def disconnect(self) -> None:
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if self._pool:
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await self._pool.close()
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async def run_migrations(self) -> None:
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schema_path = os.path.join(os.path.dirname(__file__), "schema.sql")
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with open(schema_path) as f:
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schema = f.read()
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async with self._pool.acquire() as conn:
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await conn.execute(schema)
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log.info("Migrations applied")
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async def save_trade(self, trade) -> None:
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async with self._pool.acquire() as conn:
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await conn.execute("""
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INSERT INTO trades (
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id, market_id, question, direction, size_usdc,
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entry_price, shares, fee_usdc, net_cost, timestamp, reasoning, paper,
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edge_gross, edge_net, prior_prob, final_prob,
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mid_price, spread_estimate, commission, family_key
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) VALUES (
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$1,$2,$3,$4,$5,$6,$7,$8,$9,$10,$11,$12,
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$13,$14,$15,$16,$17,$18,$19,$20
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)
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ON CONFLICT (id) DO NOTHING
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""",
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trade.id, trade.market_id, trade.question, trade.direction,
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trade.size_usdc, trade.entry_price, trade.shares, trade.fee_usdc,
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trade.net_cost, trade.timestamp, trade.reasoning, trade.paper,
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# Phase 1 fields
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trade.edge_gross, trade.edge_net, trade.prior_prob, trade.final_prob,
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trade.mid_price, trade.spread_estimate, trade.commission, trade.family_key,
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)
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async def save_daily_metrics(self, metrics: dict) -> None:
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async with self._pool.acquire() as conn:
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await conn.execute("""
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INSERT INTO metrics_daily (
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timestamp, total_trades, total_deployed, total_fees,
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total_pnl, win_rate, avg_edge, sharpe_ratio, calibration_score, paper_mode
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) VALUES ($1,$2,$3,$4,$5,$6,$7,$8,$9,$10)
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""",
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metrics["timestamp"], metrics["total_trades"], metrics["total_deployed"],
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metrics["total_fees"], metrics["total_pnl"], metrics["win_rate"],
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metrics["avg_edge"], metrics["sharpe_ratio"], metrics["calibration_score"],
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metrics["paper_mode"],
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)
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async def get_open_positions(self) -> dict[str, float]:
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"""Return {market_id: total_net_cost} for all trades in DB.
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Since there is no closed flag, every trade in the DB is treated as an
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open position. After a TRUNCATE the query returns nothing, so the
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portfolio correctly resets to a full bankroll.
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"""
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async with self._pool.acquire() as conn:
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rows = await conn.fetch(
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"SELECT market_id, SUM(net_cost) AS total FROM trades GROUP BY market_id"
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)
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return {r["market_id"]: float(r["total"]) for r in rows}
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async def get_open_families(self) -> set[str]:
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"""Return the set of family_key values from all open positions.
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Used at startup to rebuild occupied_families from DB state so the
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family-deduplication logic survives pod restarts.
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"""
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async with self._pool.acquire() as conn:
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rows = await conn.fetch(
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"SELECT DISTINCT family_key FROM trades WHERE family_key IS NOT NULL"
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)
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return {r["family_key"] for r in rows if r["family_key"]}
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async def get_open_position_details(self) -> list[dict]:
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"""Return one row per open position with family_key and direction.
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Used at startup to detect positions that share a family_key (same
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underlying event), which indicates a contradictory paper trade entered
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before the general-election family fix was deployed.
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"""
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async with self._pool.acquire() as conn:
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rows = await conn.fetch("""
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SELECT DISTINCT ON (market_id)
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market_id, question, direction, edge_net, family_key, timestamp
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FROM trades
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WHERE paper = TRUE
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ORDER BY market_id, timestamp DESC
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""")
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return [dict(r) for r in rows]
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async def get_recent_trades(self, limit: int = 100) -> list[dict]:
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async with self._pool.acquire() as conn:
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rows = await conn.fetch(
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"SELECT * FROM trades ORDER BY timestamp DESC LIMIT $1", limit
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)
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return [dict(r) for r in rows]
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async def get_metrics_history(self, days: int = 42) -> list[dict]:
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async with self._pool.acquire() as conn:
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rows = await conn.fetch(
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"SELECT * FROM metrics_daily ORDER BY timestamp DESC LIMIT $1", days
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)
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return [dict(r) for r in rows]
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