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import pandas as pd
import yfinance as yf
import logging
from typing import List, Tuple
logger = logging.getLogger(__name__)
class DataLoader:
"""
Fetches and preprocesses price (and volume) data for a given universe.
Supports daily and intraday via yfinance.
"""
def __init__(self, tickers: List[str], start_date: str, end_date: str, interval: str = "1d"):
"""
:param tickers: List of ticker strings.
:param start_date: "YYYY-MM-DD"
:param end_date: "YYYY-MM-DD"
:param interval: "1d", "5m", etc.
"""
self.tickers = tickers
self.start_date = start_date
self.end_date = end_date
self.interval = interval
def fetch_data(self) -> Tuple[pd.DataFrame, pd.DataFrame]:
"""
Downloads Adj Close and Volume for all tickers between start_date and end_date.
:return: Tuple (prices_df, volume_df). Both are DataFrames with datetime index.
"""
logger.info(f"Fetching data for {len(self.tickers)} tickers from {self.start_date} to {self.end_date} at interval {self.interval}.")
raw = yf.download(
tickers=self.tickers,
start=self.start_date,
end=self.end_date,
interval=self.interval,
auto_adjust=True,
progress=False
)
if raw.empty:
logger.error("No data fetched. Please check your tickers and date range.")
raise ValueError("Empty pricing data.")
# yfinance returns a MultiIndex with (Attribute, Ticker)
# We extract 'Close' (adjusted) and 'Volume'.
if "Close" in raw and "Volume" in raw:
prices = raw["Close"].copy()
volume = raw["Volume"].copy()
else:
# For some intervals, yfinance may label adjusted close as 'Adj Close'
if "Adj Close" in raw and "Volume" in raw:
prices = raw["Adj Close"].copy()
volume = raw["Volume"].copy()
else:
logger.error("Unexpected data format from yfinance.")
raise ValueError("Unexpected data format.")
# Drop rows where any ticker is missing (to align)
combined = pd.concat([prices, volume], axis=1, keys=["price", "volume"])
combined = combined.dropna()
prices = combined["price"]
volume = combined["volume"]
# Ensure columns are sorted alphabetically for consistency
prices = prices.sort_index(axis=1)
volume = volume[prices.columns]
logger.info(f"Downloaded price data with shape {prices.shape}, volume data with shape {volume.shape}.")
return prices, volume
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