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| import yfinance as yf | |
| import pandas as pd | |
| from pytickersymbols import PyTickerSymbols | |
| from config import ticker_dict | |
| def get_stocks_from_index(idx): | |
| stock_data = PyTickerSymbols() | |
| index = ticker_dict[idx] | |
| stocks = list(stock_data.get_stocks_by_index(index)) | |
| stock_names = [f"{stock['name']}:{stock['symbol']}" for stock in stocks] | |
| return stock_names | |
| def get_stock_data(ticker_name, interval, start_date, end_date): | |
| series = yf.download(tickers=ticker_name, start=start_date, end=end_date, interval=interval) | |
| return series.reset_index() | |
| def get_company_info(ticker): | |
| stock = yf.Ticker(ticker) | |
| info = stock.info | |
| fundamentals = { | |
| "Company Name": info.get("longName", "N/A"), | |
| "Sector": info.get("sector", "N/A"), | |
| "Industry": info.get("industry", "N/A"), | |
| "Market Cap": f"${info.get('marketCap', 'N/A'):,}", | |
| "P/E Ratio": round(info.get("trailingPE", 0), 2), | |
| "EPS": round(info.get("trailingEps", 0), 2), | |
| "52 Week High": f"${info.get('fiftyTwoWeekHigh', 'N/A'):,}", | |
| "52 Week Low": f"${info.get('fiftyTwoWeekLow', 'N/A'):,}", | |
| "Dividend Yield": f"{info.get('dividendYield', 0) * 100:.2f}%", | |
| "Beta": round(info.get("beta", 0), 2), | |
| } | |
| return pd.DataFrame(list(fundamentals.items()), columns=['Metric', 'Value']) |