"""Helper functions to fetch macro data and global markets."""
import logging
from datetime import datetime, timedelta
from typing import Dict, Optional, Any

import pandas as pd
import yfinance as yf

from ..common.logging import logger


def fetch_global_market_data(tickers: Optional[list] = None) -> Dict[str, Any]:
    if tickers is None:
        tickers = [
            "^GSPC",   # S&P 500
            "^DJI",    # Dow Jones
            "^IXIC",   # Nasdaq
            "GC=F",    # Gold
            "SI=F",    # Silver
            "CL=F",    # WTI Crude
            "BTC-USD", # Bitcoin
        ]
    result = {}
    for ticker in tickers:
        try:
            data = yf.download(ticker, period="1mo", interval="1d", progress=False)
            if data.empty:
                continue
            current = data['Close'].iloc[-1]
            month_ago = data['Close'].iloc[0] if len(data) > 0 else current
            # Ensure scalar values
            current_val = float(current.iloc[0]) if hasattr(current, 'iloc') else float(current)
            month_val = float(month_ago.iloc[0]) if hasattr(month_ago, 'iloc') else float(month_ago)
            month_change = (current_val - month_val) / month_val * 100
            result[ticker] = {
                "current": current_val,
                "month_change_pct": month_change
            }
        except Exception as e:
            logger.error(f"Error fetching {ticker}: {e}")
    return result


def prepare_macro_data(scraper) -> Dict[str, Any]:
    logger.info("Fetching macro data...")
    inflation = scraper.fetch_inflation()
    interest_rates = scraper.fetch_interest_rates()
    nrb = scraper.fetch_nrb_data()
    forex = scraper.fetch_forex_rates()
    gdp = scraper.fetch_gdp_vs_nepse()
    global_data = fetch_global_market_data()
    return {
        "inflation_data": inflation,
        "interest_rates_data": interest_rates,
        "nrb_data": nrb,
        "forex_data": forex,
        "gdp_data": gdp,
        "global_data": global_data,
    }