chemavx
4dadd3c2c4
CI/CD / build-and-push (push) Successful in 1m28s
bot/data/news.py (new): - NewsClient with in-memory cache (TTL=4h) to stay within 100 req/day limit - _build_query(): strips dates, punctuation and stopwords from market question - _score_headlines(): keyword-based pos/neg vote per article, averaged ∈ [-1, +1] - Degrades to 0.0 on missing key, 403 quota, or network error bot/strategy/bayesian.py: - BayesianStrategy(news=NewsClient) — optional, backwards compatible - Signal 4: GNews sentiment applied as direct log-odds shift (weight=1.5) so a ±1.0 sentiment score moves a 50% prior to 82%/18% - +0.10 confidence boost when news signal is present - NEWS_LOGODDS_WEIGHT constant documented at module level bot/main.py: - Instantiate NewsClient, pass to BayesianStrategy, close in finally block Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
125 lines
3.9 KiB
Python
125 lines
3.9 KiB
Python
"""
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Polymarket Trading Bot — Main Entry Point
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# ci-test: 2026-04-13
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"""
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import asyncio
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import logging
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import os
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from contextlib import asynccontextmanager
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from bot.data.polymarket import PolymarketClient
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from bot.data.external import ExternalDataClient
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from bot.data.news import NewsClient
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from bot.strategy.bayesian import BayesianStrategy
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from bot.risk.manager import RiskManager
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from bot.executor.paper import PaperExecutor
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from bot.metrics.tracker import MetricsTracker
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from bot.data.db import Database
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
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)
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log = logging.getLogger("bot.main")
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PAPER_MODE = os.getenv("PAPER_MODE", "true").lower() == "true"
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PAPER_BANKROLL = float(os.getenv("PAPER_BANKROLL", "10000"))
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async def run_trading_loop(
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poly: PolymarketClient,
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external: ExternalDataClient,
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strategy: BayesianStrategy,
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risk: RiskManager,
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executor: PaperExecutor,
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metrics: MetricsTracker,
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) -> None:
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"""Main trading loop — runs every 60 seconds."""
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log.info("Trading loop started. PAPER_MODE=%s", PAPER_MODE)
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while True:
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try:
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# 1. Fetch active crypto/finance markets
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markets = await poly.get_active_markets()
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log.info("Found %d active markets", len(markets))
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for _m in markets:
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log.info(" [market] %s | ends: %s | yes_price: %.3f",
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_m.question, _m.end_date, _m.yes_price)
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# 2. Get external signals
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ext_data = await external.get_all_signals()
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for market in markets:
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# 3. Estimate true probability
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signal = await strategy.evaluate(market, ext_data)
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if signal is None:
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continue
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log.info(
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"Signal: market=%s poly_price=%.3f our_estimate=%.3f confidence=%.2f",
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market.question[:50],
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signal.polymarket_price,
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signal.estimated_prob,
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signal.confidence,
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)
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# 4. Risk check + position sizing
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order = risk.size_order(signal, executor.get_portfolio())
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if order is None:
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log.debug("Risk manager rejected order for %s", market.id)
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continue
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# 5. Execute (paper or real)
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trade = await executor.execute(order)
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if trade:
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await metrics.record_trade(trade)
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log.info("Trade executed: %s", trade)
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# 6. Update daily metrics
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await metrics.update_daily_summary()
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except Exception as e:
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log.error("Error in trading loop: %s", e, exc_info=True)
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await asyncio.sleep(60)
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async def main() -> None:
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if PAPER_MODE:
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log.info("=" * 60)
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log.info(" PAPER TRADING MODE — No real money at risk")
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log.info(" Bankroll: $%.2f simulated", PAPER_BANKROLL)
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log.info("=" * 60)
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else:
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log.warning("REAL TRADING MODE ACTIVE — Real money at risk!")
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db = Database()
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await db.connect()
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await db.run_migrations()
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poly = PolymarketClient()
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external = ExternalDataClient()
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news = NewsClient()
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strategy = BayesianStrategy(news=news)
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risk = RiskManager(max_position_pct=0.05, max_exposure_pct=0.30)
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executor = PaperExecutor(db=db, bankroll=PAPER_BANKROLL) if PAPER_MODE else None
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metrics = MetricsTracker(db=db)
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if executor is None:
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# Import real executor only when explicitly needed
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from bot.executor.real import RealExecutor # noqa
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executor = RealExecutor(db=db)
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if PAPER_MODE:
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await executor.initialize()
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try:
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await run_trading_loop(poly, external, strategy, risk, executor, metrics)
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finally:
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await db.disconnect()
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await news.close()
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if __name__ == "__main__":
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asyncio.run(main())
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