import os
from typing import Dict, Any, List, Optional
from datetime import datetime, timedelta
import pandas as pd
import yfinance as yf
from crewai.tools import BaseTool
import time
import logging
import requests

# Set up logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger("yahoo_tools")

class YahooBitcoinDataTool(BaseTool):
    name: str = "Yahoo Finance Bitcoin Data Tool"
    description: str = "Fetches Bitcoin price data from Yahoo Finance as an alternative data source"
    max_retries: int = 3
    backoff_factor: float = 2.0
    timeout: int = 30
    cache_duration_minutes: int = 15
    cached_data: Dict[str, Dict[str, Any]] = {}
    last_cache_time: Dict[str, datetime] = {}
    
    def __init__(self, max_retries: int = 3, backoff_factor: float = 2.0, timeout: int = 30, cache_duration_minutes: int = 15):
        """
        Initialize the tool with retry parameters
        
        Args:
            max_retries: Maximum number of retry attempts (default: 3)
            backoff_factor: Exponential backoff factor between retries (default: 2.0)
            timeout: Request timeout in seconds (default: 30)
            cache_duration_minutes: How long to cache results (default: 15 minutes)
        """
        super().__init__()
        self.max_retries = max_retries
        self.backoff_factor = backoff_factor
        self.timeout = timeout
        self.cache_duration_minutes = cache_duration_minutes
        self.cached_data = {}  # Cache by period and interval
        self.last_cache_time = {}  # Cache timestamps by period and interval
    
    def _check_cache_valid(self, period: str, interval: str) -> bool:
        """
        Check if the cached data is still valid
        
        Args:
            period: The time period key
            interval: The interval key
            
        Returns:
            True if cache is valid, False otherwise
        """
        cache_key = f"{period}_{interval}"
        
        if cache_key not in self.cached_data or cache_key not in self.last_cache_time:
            return False
            
        cache_age = datetime.now() - self.last_cache_time[cache_key]
        return cache_age.total_seconds() < (self.cache_duration_minutes * 60)
        
    def _run(self, period: str = "1mo", interval: str = "1d") -> Dict[str, Any]:
        """
        Fetch Bitcoin price data from Yahoo Finance
        
        Args:
            period: Time period to fetch data for (1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max)
            interval: Time interval between data points (1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo)
            
        Returns:
            Dictionary with OHLCV data and metadata
        """
        # Use cached data if available and valid
        cache_key = f"{period}_{interval}"
        if self._check_cache_valid(period, interval):
            logger.info(f"Using cached Bitcoin data for period={period}, interval={interval}")
            return self.cached_data[cache_key]
        
        logger.info(f"Fetching Bitcoin data for period={period}, interval={interval}")
        
        # BTC-USD ticker from Yahoo Finance
        ticker = "BTC-USD"
        
        # Alternative tickers to try if primary fails
        alternative_tickers = ["BTC-USD", "BTCUSD=X", "BTC=F"]
        
        data_dict = None
        
        # Try the primary ticker with retry logic
        for attempt in range(self.max_retries):
            try:
                logger.info(f"Fetching {ticker} data (attempt {attempt + 1}/{self.max_retries})")
                
                # Get the data
                data = yf.Ticker(ticker)
                df = data.history(period=period, interval=interval, timeout=self.timeout)
                
                # Check if we have valid data
                if df.empty:
                    error_msg = f"{ticker}: possibly delisted; no price data found (period={period})"
                    logger.warning(error_msg)
                    # Don't retry with the same ticker, break to try alternatives
                    break
                
                # Process the data
                df = df.reset_index()
                
                # Ensure proper column names
                if 'Date' in df.columns:
                    df = df.rename(columns={'Date': 'time'})
                elif 'Datetime' in df.columns:
                    df = df.rename(columns={'Datetime': 'time'})
                
                # Standardize column names to lowercase
                df.columns = [col.lower() for col in df.columns]
                
                # Convert numpy types to Python native types for JSON serialization
                for col in df.columns:
                    if col != 'time':
                        df[col] = df[col].apply(lambda x: x.item() if hasattr(x, 'item') else x)
                
                # Metadata about Bitcoin from Yahoo Finance
                info = data.info
                
                # Extract key information
                market_cap = info.get('marketCap', None)
                volume_24h = info.get('volume24Hr', None)
                circulating_supply = info.get('circulatingSupply', None)
                
                # Convert to dictionary for JSON serialization
                data_dict = {
                    "dataframe": df.to_dict(orient='records'),
                    "last_price": float(df['close'].iloc[-1]) if not df.empty else None,
                    "time_period": period,
                    "interval": interval,
                    "ticker": ticker,
                    "metadata": {
                        "market_cap": market_cap,
                        "volume_24h": volume_24h,
                        "circulating_supply": circulating_supply,
                        "last_updated": datetime.now().isoformat()
                    }
                }
                
                # Cache the data
                self.cached_data[cache_key] = data_dict
                self.last_cache_time[cache_key] = datetime.now()
                logger.info(f"Cached Bitcoin data for period={period}, interval={interval}")
                
                return data_dict
                
            except requests.exceptions.Timeout as e:
                wait_time = self.backoff_factor ** attempt
                logger.warning(f"Timeout error for {ticker}: {str(e)}. Retrying in {wait_time:.1f} seconds...")
                if attempt < self.max_retries - 1:
                    time.sleep(wait_time)
                else:
                    logger.error(f"Max retries reached for {ticker}")
                    # Don't return error yet, try alternative tickers
                    break
                    
            except Exception as e:
                logger.error(f"Error fetching data for {ticker}: {str(e)}")
                # Don't return error yet, try alternative tickers
                break
        
        # If we get here, the primary ticker failed - try alternatives
        if data_dict is None:
            for alt_ticker in alternative_tickers:
                # Skip the one we already tried
                if alt_ticker == ticker:
                    continue
                    
                logger.info(f"Trying alternative ticker: {alt_ticker}")
                
                try:
                    # Get the data with the alternative ticker
                    data = yf.Ticker(alt_ticker)
                    df = data.history(period=period, interval=interval, timeout=self.timeout)
                    
                    # Check if we have valid data
                    if df.empty:
                        logger.warning(f"{alt_ticker}: possibly delisted; no price data found (period={period})")
                        continue
                    
                    # Process the data
                    df = df.reset_index()
                    
                    # Ensure proper column names
                    if 'Date' in df.columns:
                        df = df.rename(columns={'Date': 'time'})
                    elif 'Datetime' in df.columns:
                        df = df.rename(columns={'Datetime': 'time'})
                    
                    # Standardize column names to lowercase
                    df.columns = [col.lower() for col in df.columns]
                    
                    # Convert numpy types to Python native types for JSON serialization
                    for col in df.columns:
                        if col != 'time':
                            df[col] = df[col].apply(lambda x: x.item() if hasattr(x, 'item') else x)
                    
                    # Metadata about Bitcoin from Yahoo Finance
                    info = data.info
                    
                    # Extract key information
                    market_cap = info.get('marketCap', None)
                    volume_24h = info.get('volume24Hr', None)
                    circulating_supply = info.get('circulatingSupply', None)
                    
                    # Convert to dictionary for JSON serialization
                    data_dict = {
                        "dataframe": df.to_dict(orient='records'),
                        "last_price": float(df['close'].iloc[-1]) if not df.empty else None,
                        "time_period": period,
                        "interval": interval,
                        "ticker": alt_ticker,
                        "metadata": {
                            "market_cap": market_cap,
                            "volume_24h": volume_24h,
                            "circulating_supply": circulating_supply,
                            "last_updated": datetime.now().isoformat()
                        },
                        "note": f"Used alternative ticker {alt_ticker} because primary ticker failed"
                    }
                    
                    # Cache the data
                    self.cached_data[cache_key] = data_dict
                    self.last_cache_time[cache_key] = datetime.now()
                    logger.info(f"Cached Bitcoin data for period={period}, interval={interval} using alternate ticker {alt_ticker}")
                    
                    return data_dict
                    
                except Exception as e:
                    logger.error(f"Error fetching data for alternative ticker {alt_ticker}: {str(e)}")
                    continue
        
        # If we get here, all tickers failed
        error_msg = f"Failed to fetch Bitcoin data for period={period}, interval={interval} with all available tickers"
        logger.error(error_msg)
        return {
            "error": error_msg,
            "time_period": period,
            "interval": interval,
            "tickers_tried": alternative_tickers
        }


class YahooCryptoMarketTool(BaseTool):
    name: str = "Yahoo Finance Crypto Market Tool"
    description: str = "Fetches data about the broader cryptocurrency market for contextual analysis"
    max_retries: int = 3
    backoff_factor: float = 2.0
    timeout: int = 30
    cache_duration_minutes: int = 30
    cached_data: Dict[str, Any] = None
    last_cache_time: datetime = None
    
    def __init__(self, max_retries: int = 3, backoff_factor: float = 2.0, timeout: int = 30, cache_duration_minutes: int = 30):
        """
        Initialize the tool with retry parameters
        
        Args:
            max_retries: Maximum number of retry attempts (default: 3)
            backoff_factor: Exponential backoff factor between retries (default: 2.0)
            timeout: Request timeout in seconds (default: 30)
            cache_duration_minutes: How long to cache results (default: 30 minutes)
        """
        super().__init__()
        self.max_retries = max_retries
        self.backoff_factor = backoff_factor
        self.timeout = timeout
        self.cache_duration_minutes = cache_duration_minutes
        self.cached_data = None
        self.last_cache_time = None

    def _check_cache_valid(self) -> bool:
        """
        Check if the cached data is still valid
        
        Returns:
            True if cache is valid, False otherwise
        """
        if self.cached_data is None or self.last_cache_time is None:
            return False
            
        cache_age = datetime.now() - self.last_cache_time
        return cache_age.total_seconds() < (self.cache_duration_minutes * 60)

    def _get_ticker_data_with_retries(self, ticker: str) -> Dict[str, Any]:
        """
        Get ticker data with retry logic
        
        Args:
            ticker: The ticker symbol to fetch
            
        Returns:
            Dictionary with ticker data or error
        """
        for attempt in range(self.max_retries):
            try:
                logger.info(f"Fetching data for {ticker} (attempt {attempt + 1}/{self.max_retries})")
                data = yf.Ticker(ticker)
                
                # Set a timeout for the history call
                hist = data.history(period="5d", timeout=self.timeout)
                info = data.info
                
                # Verify we have data
                if hist.empty:
                    logger.warning(f"{ticker}: possibly delisted; no price data found (period=5d)")
                    return {
                        "ticker": ticker,
                        "error": f"{ticker}: possibly delisted; no price data found (period=5d)"
                    }
                
                # Successfully got data, return it
                return {
                    "data": data,
                    "hist": hist,
                    "info": info
                }
                
            except requests.exceptions.Timeout as e:
                wait_time = self.backoff_factor ** attempt
                logger.warning(f"Timeout error for {ticker}: {str(e)}. Retrying in {wait_time:.1f} seconds...")
                if attempt < self.max_retries - 1:
                    time.sleep(wait_time)
                else:
                    logger.error(f"Max retries reached for {ticker}")
                    return {
                        "ticker": ticker,
                        "error": f"Timeout error after {self.max_retries} attempts: {str(e)}"
                    }
                    
            except Exception as e:
                logger.error(f"Error fetching data for {ticker}: {str(e)}")
                return {
                    "ticker": ticker,
                    "error": str(e)
                }
                
        return {
            "ticker": ticker,
            "error": "Unknown error during retry attempts"
        }
    
    def _run(self, top_n: int = 10) -> Dict[str, Any]:
        """
        Fetch data about the top cryptocurrencies in the market
        
        Args:
            top_n: Number of top cryptocurrencies to fetch data for
            
        Returns:
            Dictionary with market data and trends
        """
        # Check if we have valid cached data
        if self._check_cache_valid():
            logger.info("Using cached cryptocurrency market data")
            return self.cached_data
            
        logger.info(f"Fetching data for top {top_n} cryptocurrencies")
        
        try:
            # Common crypto tickers to check
            tickers = [
                "BTC-USD",  # Bitcoin
                "ETH-USD",  # Ethereum
                "XRP-USD",  # Ripple
                "SOL-USD",  # Solana
                "ADA-USD",  # Cardano
                "AVAX-USD", # Avalanche
                "DOT-USD",  # Polkadot
                "DOGE-USD", # Dogecoin
                "LINK-USD", # Chainlink
                "MATIC-USD" # Polygon
            ]
            
            # Limit to requested number
            tickers = tickers[:min(top_n, len(tickers))]
            
            results = []
            market_cap_sum = 0
            btc_dominance = 0
            btc_market_cap = 0
            success_count = 0
            error_count = 0
            
            # Fetch data for each ticker
            for ticker in tickers:
                ticker_data = self._get_ticker_data_with_retries(ticker)
                
                if "error" in ticker_data:
                    # Handle error case - add basic info with error message
                    error_count += 1
                    results.append({
                        "ticker": ticker,
                        "name": ticker.split('-')[0],
                        "error": ticker_data["error"],
                        "data_available": False
                    })
                    continue
                
                # Extract data
                data = ticker_data["data"]
                hist = ticker_data["hist"]
                info = ticker_data["info"]
                
                success_count += 1
                
                if not hist.empty:
                    current_price = hist['Close'].iloc[-1]
                    day_change = ((current_price / hist['Close'].iloc[-2]) - 1) * 100 if len(hist) > 1 else 0
                    week_change = ((current_price / hist['Close'].iloc[0]) - 1) * 100 if len(hist) > 4 else day_change
                    
                    market_cap = info.get('marketCap', 0)
                    market_cap_sum += market_cap if market_cap else 0
                    
                    # Store BTC market cap for dominance calculation
                    if ticker == "BTC-USD":
                        btc_market_cap = market_cap if market_cap else 0
                    
                    # Convert numpy types to Python native types for JSON serialization
                    if hasattr(current_price, 'item'):
                        current_price = current_price.item()
                    if hasattr(day_change, 'item'):
                        day_change = day_change.item()
                    if hasattr(week_change, 'item'):
                        week_change = week_change.item()
                    
                    results.append({
                        "ticker": ticker,
                        "name": info.get('shortName', ticker.split('-')[0]),
                        "current_price": current_price,
                        "market_cap": market_cap,
                        "volume_24h": info.get('volume24Hr', None),
                        "day_change_percent": day_change,
                        "week_change_percent": week_change,
                        "data_available": True
                    })
            
            # Calculate BTC dominance
            if market_cap_sum > 0 and btc_market_cap > 0:
                btc_dominance = (btc_market_cap / market_cap_sum) * 100
            
            # Overall market trends - only count assets with data
            valid_results = [r for r in results if r.get("data_available", False)]
            market_trend = "bullish" if sum(r.get('day_change_percent', 0) for r in valid_results) > 0 else "bearish"
            
            # Create response
            response = {
                "cryptocurrencies": results,
                "market_summary": {
                    "total_market_cap": market_cap_sum,
                    "btc_dominance": btc_dominance,
                    "market_trend": market_trend,
                    "timestamp": datetime.now().isoformat(),
                    "success_count": success_count,
                    "error_count": error_count,
                    "total_count": len(tickers)
                }
            }
            
            # Cache the result if we got at least some data
            if success_count > 0:
                self.cached_data = response
                self.last_cache_time = datetime.now()
                logger.info(f"Cached cryptocurrency market data (success: {success_count}, errors: {error_count})")
            
            return response
            
        except Exception as e:
            logger.error(f"Error in YahooCryptoMarketTool: {str(e)}")
            return {
                "error": str(e),
                "market_summary": {
                    "market_trend": "unknown",
                    "timestamp": datetime.now().isoformat(),
                    "error": str(e)
                },
                "cryptocurrencies": []
            }