import logging
from collections.abc import Callable
from functools import wraps
from typing import Annotated, Any, Optional

import pandas as pd
import yfinance as yf
from pandas import DataFrame

from .utils import SavePathType, decorate_all_methods

logger = logging.getLogger(__name__)


def init_ticker(func: Callable) -> Callable:
    @wraps(func)
    def wrapper(symbol: Annotated[str, "ticker symbol"], *args, **kwargs) -> Any:
        ticker = yf.Ticker(symbol)
        return func(ticker, *args, **kwargs)

    return wrapper


@decorate_all_methods(init_ticker)
class YFinanceUtils:
    def get_stock_data(
        symbol: Annotated[str, "ticker symbol"],
        start_date: Annotated[
            str, "start date for retrieving stock price data, YYYY-mm-dd"
        ],
        end_date: Annotated[
            str, "end date for retrieving stock price data, YYYY-mm-dd"
        ],
        save_path: SavePathType = None,
    ) -> DataFrame:
        ticker = symbol
        end_date = pd.to_datetime(end_date) + pd.DateOffset(days=1)
        end_date = end_date.strftime("%Y-%m-%d")
        stock_data = ticker.history(start=start_date, end=end_date)
        return stock_data

    def get_stock_info(
        symbol: Annotated[str, "ticker symbol"],
    ) -> dict:
        ticker = symbol
        stock_info = ticker.info
        return stock_info

    def get_company_info(
        symbol: Annotated[str, "ticker symbol"],
        save_path: str | None = None,
    ) -> DataFrame:
        ticker = symbol
        info = ticker.info
        company_info = {
            "Company Name": info.get("shortName", "N/A"),
            "Industry": info.get("industry", "N/A"),
            "Sector": info.get("sector", "N/A"),
            "Country": info.get("country", "N/A"),
            "Website": info.get("website", "N/A"),
        }
        company_info_df = DataFrame([company_info])
        if save_path:
            company_info_df.to_csv(save_path)
            logger.info("Company info for %s saved to %s", ticker.ticker, save_path)
        return company_info_df

    def get_stock_dividends(
        symbol: Annotated[str, "ticker symbol"],
        save_path: str | None = None,
    ) -> DataFrame:
        ticker = symbol
        dividends = ticker.dividends
        if save_path:
            dividends.to_csv(save_path)
            logger.info("Dividends for %s saved to %s", ticker.ticker, save_path)
        return dividends

    def get_income_stmt(symbol: Annotated[str, "ticker symbol"]) -> DataFrame:
        ticker = symbol
        income_stmt = ticker.financials
        return income_stmt

    def get_balance_sheet(symbol: Annotated[str, "ticker symbol"]) -> DataFrame:
        ticker = symbol
        balance_sheet = ticker.balance_sheet
        return balance_sheet

    def get_cash_flow(symbol: Annotated[str, "ticker symbol"]) -> DataFrame:
        ticker = symbol
        cash_flow = ticker.cashflow
        return cash_flow

    def get_analyst_recommendations(symbol: Annotated[str, "ticker symbol"]) -> tuple:
        ticker = symbol
        recommendations = ticker.recommendations
        if recommendations.empty:
            return None, 0

        row_0 = recommendations.iloc[0, 1:]

        max_votes = row_0.max()
        majority_voting_result = row_0[row_0 == max_votes].index.tolist()

        return majority_voting_result[0], max_votes