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131 lines
3.9 KiB
Python
131 lines
3.9 KiB
Python
"""
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Alpaca bars → AlpacaPriceData conversion and DB storage
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"""
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import logging
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from datetime import datetime, timezone
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from typing import Dict, List, Optional
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select, and_
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from sqlalchemy.dialects.postgresql import insert as pg_insert
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from app.models.alpaca_price import AlpacaPriceData
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from app.services.alpaca_client import AlpacaClient
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logger = logging.getLogger(__name__)
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class AlpacaPriceService:
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"""Alpaca bars → AlpacaPriceData conversion and DB storage"""
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def __init__(self, client: Optional[AlpacaClient] = None):
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self.client = client or AlpacaClient()
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def is_available(self) -> bool:
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return self.client.is_configured()
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async def fetch_and_store_bars(
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self,
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db: AsyncSession,
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ticker: str,
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start_date: datetime,
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end_date: datetime,
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interval: str = "1d",
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) -> int:
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"""
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Fetch bars from Alpaca and upsert into AlpacaPriceData table.
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Returns:
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Number of newly inserted records.
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"""
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ticker = ticker.upper()
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start_str = start_date.strftime("%Y-%m-%d")
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end_str = end_date.strftime("%Y-%m-%d")
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bars = await self.client.get_bars(
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symbol=ticker,
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timeframe=interval,
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start=start_str,
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end=end_str,
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)
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if not bars:
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logger.warning(f"Alpaca returned 0 bars for {ticker}")
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return 0
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# Build rows for batch insert
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rows = []
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for bar in bars:
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bar_dt = _parse_bar_timestamp(bar["t"])
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rows.append({
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"ticker": ticker,
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"date": bar_dt,
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"open": float(bar.get("o", 0)),
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"high": float(bar.get("h", 0)),
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"low": float(bar.get("l", 0)),
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"close": float(bar.get("c", 0)),
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"volume": float(bar.get("v", 0)),
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"vwap": float(bar["vw"]) if bar.get("vw") else None,
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"trade_count": int(bar["n"]) if bar.get("n") else None,
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"data_source": "ALPACA",
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})
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if not rows:
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return 0
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# Batch insert — skip duplicates via ON CONFLICT DO NOTHING
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stmt = pg_insert(AlpacaPriceData).values(rows)
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stmt = stmt.on_conflict_do_nothing(constraint='uq_alpaca_price_data')
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result = await db.execute(stmt)
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await db.commit()
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inserted = result.rowcount
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if inserted:
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logger.info(f"Alpaca: inserted {inserted} bars for {ticker}")
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return inserted
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async def fetch_bars_raw(
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self,
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ticker: str,
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interval: str = "1d",
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start_date: Optional[datetime] = None,
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end_date: Optional[datetime] = None,
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) -> List[Dict]:
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"""
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Return raw bar dicts without touching the DB (useful for intraday / non-persistent use).
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"""
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start_str = start_date.strftime("%Y-%m-%d") if start_date else None
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end_str = end_date.strftime("%Y-%m-%d") if end_date else None
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bars = await self.client.get_bars(
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symbol=ticker.upper(),
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timeframe=interval,
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start=start_str,
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end=end_str,
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)
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return [
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{
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"timestamp": bar["t"],
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"open": bar.get("o"),
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"high": bar.get("h"),
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"low": bar.get("l"),
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"close": bar.get("c"),
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"volume": bar.get("v"),
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"vwap": bar.get("vw"),
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"trade_count": bar.get("n"),
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}
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for bar in bars
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]
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def _parse_bar_timestamp(ts_str: str) -> datetime:
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"""Parse Alpaca bar timestamp (RFC-3339) into a timezone-aware datetime."""
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# Alpaca returns e.g. "2024-01-02T05:00:00Z"
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dt = datetime.fromisoformat(ts_str.replace("Z", "+00:00"))
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if dt.tzinfo is None:
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dt = dt.replace(tzinfo=timezone.utc)
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return dt
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