dennisthiessen
437ceacfc1
Behavior-preserving cleanup (345 tests pass, ruff clean):
- scheduler: replace 62 inline logger.x(json.dumps({...})) calls with a
_log_event helper, and collapse 11 identical _job_runtime dicts into an
_idle_runtime() factory over _JOB_NAMES.
- settings: add app/services/settings_store.py (get_setting/get_value/get_map/
upsert_setting) and route ~13 hand-rolled SystemSetting queries + two
identical _settings_map helpers through it.
- scoring.get_rankings: collapse the per-ticker N+1 (3-4 queries + a commit each)
into 2 bulk reads + a single conditional commit; drop the redundant re-fetch.
Lazy recompute-on-read is preserved. Adds first tests for get_rankings.
Net ~ -245 lines across the touched modules.
114 lines
3.8 KiB
Python
114 lines
3.8 KiB
Python
"""Market-regime guard.
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Computes a simple, robust trend regime for a benchmark (SPY by default) from its
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own moving averages, so the UI can warn against fighting the broad market — e.g.
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going long while SPY is below its 200-day average. Result is cached in a
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SystemSetting (JSON) and refreshed by a daily job; reads are cheap.
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Regime is informational: it warns, it doesn't suppress setups.
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"""
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from __future__ import annotations
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import json
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import logging
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from datetime import date, datetime, timedelta, timezone
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.config import settings
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from app.providers.alpaca import AlpacaOHLCVProvider
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from app.services import settings_store
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from app.services.admin_service import update_setting
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logger = logging.getLogger(__name__)
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KEY_REGIME = "market_regime"
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BENCHMARK = "SPY"
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_SMA_SHORT = 50
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_SMA_LONG = 200
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def _sma(values: list[float], window: int) -> float | None:
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if len(values) < window:
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return None
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return sum(values[-window:]) / window
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def compute_regime(closes: list[float]) -> dict:
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"""Derive a regime label from a benchmark's close series.
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bullish = price above the 200-day and the 50-day confirms (50 ≥ 200)
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bearish = price below the 200-day and the 50-day confirms (50 ≤ 200)
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neutral = mixed / chop
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unknown = not enough history
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"""
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if not closes:
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return {"label": "unknown", "reason": "no benchmark data"}
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price = closes[-1]
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sma50 = _sma(closes, _SMA_SHORT)
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sma200 = _sma(closes, _SMA_LONG)
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if sma200 is None:
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# Fall back to the 50-day alone when we lack a full year of history.
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if sma50 is None:
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return {"label": "unknown", "reason": "insufficient history"}
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label = "bullish" if price > sma50 else "bearish"
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return {
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"label": label,
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"price": round(price, 2),
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"sma50": round(sma50, 2),
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"sma200": None,
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"pct_above_200": None,
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"reason": "based on 50-day only (under 200 bars)",
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}
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above_200 = price > sma200
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if above_200 and sma50 >= sma200:
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label = "bullish"
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elif not above_200 and sma50 <= sma200:
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label = "bearish"
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else:
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label = "neutral"
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return {
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"label": label,
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"price": round(price, 2),
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"sma50": round(sma50, 2),
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"sma200": round(sma200, 2),
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"pct_above_200": round((price / sma200 - 1.0) * 100, 2),
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"reason": None,
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}
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async def update_market_regime(db: AsyncSession) -> dict:
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"""Fetch the benchmark, compute the regime, and cache it. Job entrypoint."""
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if not settings.alpaca_api_key or not settings.alpaca_api_secret:
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return {"label": "unknown", "reason": "Alpaca keys not configured"}
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provider = AlpacaOHLCVProvider(settings.alpaca_api_key, settings.alpaca_api_secret)
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end = date.today()
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start = end - timedelta(days=400) # ~280 trading days → covers the 200-day SMA
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bars = await provider.fetch_ohlcv(BENCHMARK, start, end)
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closes = [b.close for b in sorted(bars, key=lambda b: b.date)]
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regime = compute_regime(closes)
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regime["benchmark"] = BENCHMARK
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regime["computed_at"] = datetime.now(timezone.utc).isoformat()
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await update_setting(db, KEY_REGIME, json.dumps(regime))
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logger.info(json.dumps({"event": "market_regime_updated", "regime": regime["label"]}))
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return regime
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async def get_market_regime(db: AsyncSession) -> dict:
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"""Return the cached regime (computed by the daily job)."""
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setting = await settings_store.get_setting(db, KEY_REGIME)
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if setting is None:
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return {"label": "unknown", "benchmark": BENCHMARK, "reason": "not computed yet"}
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try:
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return json.loads(setting.value)
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except (TypeError, ValueError):
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return {"label": "unknown", "benchmark": BENCHMARK, "reason": "corrupt cache"}
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