import os from typing import Annotated import pandas as pd import yfinance as yf from stockstats import wrap from tradingagents.config import DEFAULT_CONFIG class StockstatsUtils: @staticmethod def get_stock_stats( symbol: Annotated[str, "ticker symbol for the company"], indicator: Annotated[ str, "quantitative indicators based off of the stock data for the company" ], curr_date_str: Annotated[ str, "curr date for retrieving stock price data, YYYY-mm-dd" ], data_dir: Annotated[ str, "directory where the stock data is stored.", ], online: Annotated[ bool, "whether to use online tools to fetch data or offline tools. If True, will use online tools.", ] = False, ): df = None data = None if not online: try: data = pd.read_csv( os.path.join( data_dir, f"{symbol}-YFin-data-2015-01-01-2025-03-25.csv", ) ) df = wrap(data) except FileNotFoundError as err: raise Exception( "Stockstats fail: Yahoo Finance data not fetched yet!" ) from err else: # Get today's date as YYYY-mm-dd to add to cache today_date = pd.Timestamp.today() curr_date = pd.to_datetime(curr_date_str) end_date = today_date start_date = today_date - pd.DateOffset(years=15) start_date = start_date.strftime("%Y-%m-%d") end_date = end_date.strftime("%Y-%m-%d") # Get config and ensure cache directory exists os.makedirs(DEFAULT_CONFIG.data_cache_dir, exist_ok=True) data_file = os.path.join( DEFAULT_CONFIG.data_cache_dir, f"{symbol}-YFin-data-{start_date}-{end_date}.csv", ) if os.path.exists(data_file): data = pd.read_csv(data_file) data["Date"] = pd.to_datetime(data["Date"]) else: data = yf.download( symbol, start=start_date, end=end_date, multi_level_index=False, progress=False, auto_adjust=True, ) if data is None: raise ValueError(f"Failed to download data for {symbol}") data = data.reset_index() data.to_csv(data_file, index=False) df = wrap(data) df["Date"] = df["Date"].dt.strftime("%Y-%m-%d") curr_date = curr_date.strftime("%Y-%m-%d") df[indicator] # trigger stockstats to calculate the indicator matching_rows = df[df["Date"].str.startswith(curr_date_str)] if not matching_rows.empty: indicator_value = matching_rows[indicator].values[0] return indicator_value else: return "N/A: Not a trading day (weekend or holiday)"