import pandas as pd
import yfinance as yf
from stockstats import wrap
from typing import Annotated
import os
from .config import get_config, DATA_DIR


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: Annotated[
            str, "curr date for retrieving stock price data, YYYY-mm-dd"
        ],
    ):
        # Get config and set up data directory path
        config = get_config()
        online = config["data_vendors"]["technical_indicators"] != "local"

        df = None
        data = None

        # CRITICAL: Use curr_date as end date to prevent future data leakage
        # This ensures backtest doesn't see data beyond the analysis date
        curr_date_dt = pd.to_datetime(curr_date)
        end_date_dt = curr_date_dt
        start_date_dt = curr_date_dt - pd.DateOffset(years=2)  # Reduced from 15 years for faster fetching

        if not online:
            try:
                data = pd.read_csv(
                    os.path.join(
                        DATA_DIR,
                        f"{symbol}-YFin-data-2015-01-01-2025-03-25.csv",
                    )
                )
                # CRITICAL: Filter local data to prevent future data leakage
                data["Date"] = pd.to_datetime(data["Date"])
                data = data[data["Date"] <= curr_date_dt]
                df = wrap(data)
            except FileNotFoundError:
                raise Exception("Stockstats fail: Yahoo Finance data not fetched yet!")
        else:
            start_date = start_date_dt.strftime("%Y-%m-%d")
            end_date = end_date_dt.strftime("%Y-%m-%d")

            # Get config and ensure cache directory exists
            os.makedirs(config["data_cache_dir"], exist_ok=True)

            # Cache file now uses curr_date (end_date), not today's date
            data_file = os.path.join(
                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,
                )
                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_dt.strftime("%Y-%m-%d")

        df[indicator]  # trigger stockstats to calculate the indicator
        matching_rows = df[df["Date"].str.startswith(curr_date)]

        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)"