import os
import yfinance as yf
import pandas as pd

def pull():
    # Get the CWD for pathing due to being called from C# now
    SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
    DATA_DIR = os.path.join(SCRIPT_DIR, "data")

    # Import the S&P 500 symbols
    symbols = pd.read_excel(os.path.join(DATA_DIR, "stock_symbols.xlsx"))
    symbols.columns = symbols.columns.str.strip()
    tickers = symbols['Symbol'].tolist()

    # Scrape the data
    all_data = []
    for i, symbol in enumerate(tickers):
        df = yf.download(symbol, period="max", auto_adjust=True)
        if not df.empty:
            # Remove the Horizontal ticker column
            df.columns = df.columns.get_level_values(0)
            # Add in the Vertical ticker column
            df['Ticker'] = symbol
            # add to master list
            all_data.append(df)

    # Concatinate into a combined list and cache
    final_df = pd.concat(all_data)

    # Save to file
    final_df.to_parquet(os.path.join(DATA_DIR, "stocks.parquet"))
    final_df.head(200).to_csv(os.path.join(DATA_DIR, "stocks.preview.csv"))

if __name__ == "__main__":
    pull()