Update yfinance_data/fetcher.py

yfinance_data/fetcher.py

@@ -1,59 +1,34 @@
-# yfinance_data/fetcher.py
-
 import yfinance as yf
-import pandas as pd
 
-def fetch_stock_data(symbol, start_date, end_date, interval='1h'):
+def fetch_stock_data(symbol, start_date, end_date, interval='1d'):
     """
-    Fetches historical stock data for a given symbol from Yahoo Finance.
-
+    Fetch 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).
-
+    - symbol (str): Stock symbol to fetch the data for.
+    - start_date (str): Start date in 'YYYY-MM-DD' format.
+    - end_date (str): End date in 'YYYY-MM-DD' format.
+    - interval (str): Data interval. Defaults to '1d'. Options: '1d', '1h', etc.
+    
     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):
+    - DataFrame: Historical stock data including date, open, high, low, close, and volume.
     """
-    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
+    # Fetch the stock data using the yfinance library
+    stock_data = yf.download(symbol, start=start_date, end=end_date, interval=interval)
+    
+    # Check if the DataFrame is empty
+    if stock_data.empty:
+        raise ValueError(f"No data found for {symbol} using interval {interval}.")
+    
+    return stock_data
 
-# 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
+    # Example usage
+    symbol = "AAPL"
+    start_date = "2023-01-01"
+    end_date = "2023-04-01"
+    interval = "1h"  # For hourly data
+    
+    # Fetch and print the data for demonstration
+    data = fetch_stock_data(symbol, start_date, end_date, interval)
+    print(data.head())  # Print the first few rows