622a74724b
period=1d interval=1m returns empty after NSE closes at 3:30 PM IST. Fall back to period=5d interval=1d to get last available close price. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
132 lines
3.8 KiB
Python
132 lines
3.8 KiB
Python
# engine/data.py
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from datetime import datetime, timezone
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from pathlib import Path
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import os
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import threading
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import pandas as pd
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import yfinance as yf
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ENGINE_ROOT = Path(__file__).resolve().parents[1]
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HISTORY_DIR = ENGINE_ROOT / "storage" / "history"
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ALLOW_PRICE_CACHE = os.getenv("ALLOW_PRICE_CACHE", "0").strip().lower() in {"1", "true", "yes"}
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_LAST_PRICE: dict[str, dict[str, object]] = {}
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_LAST_PRICE_LOCK = threading.Lock()
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def _history_cache_file(ticker: str, provider: str = "yfinance") -> Path:
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safe_ticker = (ticker or "").replace(":", "_").replace("/", "_")
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return HISTORY_DIR / f"{safe_ticker}.csv"
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def _set_last_price(
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ticker: str,
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price: float,
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source: str,
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*,
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provider: str | None = None,
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instrument_token: int | None = None,
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):
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now = datetime.now(timezone.utc)
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with _LAST_PRICE_LOCK:
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payload = {"price": float(price), "source": source, "ts": now}
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if provider:
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payload["provider"] = provider
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if instrument_token is not None:
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payload["instrument_token"] = int(instrument_token)
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_LAST_PRICE[ticker] = payload
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def get_price_snapshot(ticker: str) -> dict[str, object] | None:
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with _LAST_PRICE_LOCK:
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data = _LAST_PRICE.get(ticker)
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if not data:
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return None
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return dict(data)
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def _get_last_live_price(ticker: str, provider: str | None = None) -> float | None:
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with _LAST_PRICE_LOCK:
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data = _LAST_PRICE.get(ticker)
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if not data:
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return None
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if data.get("source") == "live":
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if provider and data.get("provider") not in {None, provider}:
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return None
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return float(data.get("price", 0))
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return None
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def _cached_last_close(ticker: str, provider: str = "yfinance") -> float | None:
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file = _history_cache_file(ticker, provider=provider)
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if not file.exists():
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return None
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df = pd.read_csv(file)
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if df.empty or "Close" not in df.columns:
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return None
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return float(df["Close"].iloc[-1])
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def fetch_live_price(
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ticker,
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allow_cache: bool | None = None,
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*,
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provider: str = "yfinance",
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user_id: str | None = None,
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run_id: str | None = None,
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):
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if allow_cache is None:
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allow_cache = ALLOW_PRICE_CACHE
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# Try intraday (works during market hours)
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try:
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df = yf.download(
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ticker,
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period="1d",
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interval="1m",
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auto_adjust=True,
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progress=False,
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timeout=5,
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)
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if df is not None and not df.empty:
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close_value = df["Close"].iloc[-1]
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if hasattr(close_value, "iloc"):
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close_value = close_value.iloc[-1]
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price = float(close_value)
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_set_last_price(ticker, price, "live", provider="yfinance")
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return price
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except Exception:
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pass
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# Fallback: last close from past 5 days (works after market hours)
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try:
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df = yf.download(
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ticker,
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period="5d",
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interval="1d",
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auto_adjust=True,
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progress=False,
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timeout=5,
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)
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if df is not None and not df.empty:
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close_value = df["Close"].iloc[-1]
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if hasattr(close_value, "iloc"):
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close_value = close_value.iloc[-1]
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price = float(close_value)
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_set_last_price(ticker, price, "live", provider="yfinance")
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return price
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except Exception:
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pass
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if allow_cache:
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last_live = _get_last_live_price(ticker, provider="yfinance")
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if last_live is not None:
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return last_live
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cached = _cached_last_close(ticker, provider="yfinance")
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if cached is not None:
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_set_last_price(ticker, cached, "cache", provider="yfinance")
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return cached
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raise RuntimeError(f"No live data for {ticker}")
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