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# yfinance_data/fetcher.py
import yfinance as yf
import pandas as pd
def fetch_stock_data(symbol, start_date, end_date, interval='1h'):
"""
Fetches historical stock data for a given symbol from Yahoo Finance.
Parameters:
- symbol: The ticker symbol for the stock (str).
- start_date: The start date for the data fetching in 'YYYY-MM-DD' format (str).
- end_date: The end date for the data fetching in 'YYYY-MM-DD' format (str).
- interval: The data interval. Valid intervals: '1m', '2m', '5m', '15m', '30m', '1h', '1d', '5d', '1wk', '1mo', '3mo' (str).
Returns:
- DataFrame: Historical stock data including date, open, high, low, close, volume.
"""
# Fetch the data
data = yf.download(symbol, start=start_date, end=end_date, interval=interval)
# Drop any NaNs (usually in case of missing data)
data.dropna(inplace=True)
return data
def fetch_data_for_indicators(symbol, days=30):
"""
Fetches historical stock data for the past 30 days for both 4-hour and 1-hour intervals.
Parameters:
- symbol: The ticker symbol for the stock (str).
- days: Number of days in the past to fetch data for (int).
Returns:
- Tuple of DataFrames: (data_4h, data_1h)
"""
# Calculate start and end dates
end_date = pd.Timestamp.now()
start_date = end_date - pd.Timedelta(days=days)
# Convert dates to string format for the API call
start_date_str = start_date.strftime('%Y-%m-%d')
end_date_str = end_date.strftime('%Y-%m-%d')
# Fetch data for both intervals
data_4h = fetch_stock_data(symbol, start_date_str, end_date_str, interval='4h')
data_1h = fetch_stock_data(symbol, start_date_str, end_date_str, interval='1h')
return data_4h, data_1h
# Example usage
if __name__ == "__main__":
symbol = "AAPL" # Example stock symbol
data_4h, data_1h = fetch_data_for_indicators(symbol)
print("4-Hour Data:")
print(data_4h.head()) # Display the first few rows
print("\n1-Hour Data:")
print(data_1h.head()) # Display the first few rows
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