"""
Strategy execution module integrating Openfund-maker and Openfund-taker
"""

import logging
import threading
import time
import traceback
from typing import Dict, Any, List, Optional

from openfund_agent.models.trading import (
    TradingSignal,
    Position,
    OrderAction,
    ExecutionResult,
)
from openfund_agent.strategy.context import StrategyContext, StrategyContextManager

logger = logging.getLogger(__name__)


class StrategyExecutionTool:
    """
    Strategy execution tool that integrates Openfund-maker and Openfund-taker

    This class provides the core functionality for executing trading strategies,
    including signal generation (Maker) and position management (Taker).
    """

    def __init__(
        self,
        maker_config: Dict[str, Any],
        taker_config: Dict[str, Any],
        exchange_client: Any,
    ):
        """
        Initialize strategy execution tool

        Args:
            maker_config: Configuration for Openfund-maker
            taker_config: Configuration for Openfund-taker
            exchange_client: Exchange client instance
        """
        self.maker_config = maker_config
        self.taker_config = taker_config
        self.exchange_client = exchange_client
        self.lock = threading.Lock()
        self.context_manager = StrategyContextManager()
        self.execution_history: List[Dict[str, Any]] = []

        logger.info("StrategyExecutionTool initialized")

    def generate_signals(
        self, strategy_name: str, market_data: Dict[str, Any]
    ) -> List[TradingSignal]:
        """
        Generate trading signals using Maker functionality

        This method analyzes market data and generates trading signals based on
        the specified strategy.

        Args:
            strategy_name: Name of the strategy to use
            market_data: Market data including klines and indicators

        Returns:
            List of generated trading signals

        Raises:
            ValueError: If strategy_name is invalid or market_data is incomplete
        """
        if not strategy_name:
            raise ValueError("strategy_name cannot be empty")

        if not market_data:
            raise ValueError("market_data cannot be empty")

        logger.info(f"Generating signals for strategy: {strategy_name}")

        try:
            # TODO: Integrate with Openfund-maker
            # For now, return empty list as placeholder
            signals = []

            # Example signal generation logic (to be replaced with actual Maker integration)
            # This is a placeholder that would be replaced with actual strategy logic
            if "kline" in market_data and "indicators" in market_data:
                # Placeholder for actual signal generation
                logger.debug(f"Market data available for signal generation")

            logger.info(f"Generated {len(signals)} signals")
            return signals

        except Exception as e:
            logger.error(f"Error generating signals: {str(e)}")
            raise

    def manage_positions(
        self, positions: List[Position], strategy_config: Dict[str, Any]
    ) -> List[OrderAction]:
        """
        Manage positions using Taker functionality

        This method manages existing positions, including stop-loss and take-profit
        updates, position closing, etc.

        Args:
            positions: List of current positions
            strategy_config: Strategy configuration parameters

        Returns:
            List of order actions to execute

        Raises:
            ValueError: If positions list is None or strategy_config is invalid
        """
        if positions is None:
            raise ValueError("positions cannot be None")

        if not strategy_config:
            raise ValueError("strategy_config cannot be empty")

        logger.info(f"Managing {len(positions)} positions")

        try:
            # TODO: Integrate with Openfund-taker
            # For now, return empty list as placeholder
            order_actions = []

            # Example position management logic (to be replaced with actual Taker integration)
            for position in positions:
                logger.debug(
                    f"Processing position: {position.symbol} "
                    f"{position.side} @ {position.entry_price}"
                )
                # Placeholder for actual position management logic

            logger.info(f"Generated {len(order_actions)} order actions")
            return order_actions

        except Exception as e:
            logger.error(f"Error managing positions: {str(e)}")
            raise

    def execute_strategy(
        self, strategy_name: str, symbol: str, parameters: Dict[str, Any]
    ) -> ExecutionResult:
        """
        Execute complete trading strategy

        This method coordinates signal generation and order management to execute
        a complete trading strategy.

        Args:
            strategy_name: Name of the strategy to execute
            symbol: Trading pair symbol (e.g., "BTC/USDT:USDT")
            parameters: Strategy parameters

        Returns:
            ExecutionResult containing signals, orders, and execution status

        Raises:
            ValueError: If required parameters are missing or invalid
        """
        if not strategy_name:
            raise ValueError("strategy_name cannot be empty")

        if not symbol:
            raise ValueError("symbol cannot be empty")

        logger.info(f"Executing strategy '{strategy_name}' for {symbol}")

        start_time = time.time()
        errors = []
        signals = []
        orders = []

        try:
            with self.lock:
                # Step 1: Fetch market data (placeholder - would integrate with data collection)
                market_data = self._fetch_market_data(symbol, parameters)

                # Step 2: Generate trading signals
                try:
                    signals = self.generate_signals(strategy_name, market_data)
                except Exception as e:
                    error_msg = f"Signal generation failed: {str(e)}"
                    logger.error(error_msg)
                    errors.append(error_msg)

                # Step 3: Get current positions
                try:
                    positions = self._get_current_positions(symbol)
                except Exception as e:
                    error_msg = f"Failed to get positions: {str(e)}"
                    logger.error(error_msg)
                    errors.append(error_msg)
                    positions = []

                # Step 4: Manage positions
                try:
                    orders = self.manage_positions(positions, parameters)
                except Exception as e:
                    error_msg = f"Position management failed: {str(e)}"
                    logger.error(error_msg)
                    errors.append(error_msg)

                execution_time = time.time() - start_time
                success = len(errors) == 0

                result = ExecutionResult(
                    success=success,
                    signals=signals,
                    orders=orders,
                    errors=errors,
                    execution_time=execution_time,
                    metadata={
                        "strategy_name": strategy_name,
                        "symbol": symbol,
                        "parameters": parameters,
                        "timestamp": int(time.time()),
                    },
                )

                # Record execution details
                self._record_execution(strategy_name, symbol, result)

                # Record individual orders
                for order in orders:
                    self._record_order(order, strategy_name, "pending")

                logger.info(
                    f"Strategy execution completed in {execution_time:.2f}s. "
                    f"Success: {success}, Signals: {len(signals)}, Orders: {len(orders)}"
                )

                return result

        except Exception as e:
            execution_time = time.time() - start_time
            error_msg = f"Strategy execution failed: {str(e)}"
            logger.error(error_msg)
            logger.error(f"Traceback: {traceback.format_exc()}")
            errors.append(error_msg)

            result = ExecutionResult(
                success=False,
                signals=signals,
                orders=orders,
                errors=errors,
                execution_time=execution_time,
                metadata={
                    "strategy_name": strategy_name,
                    "symbol": symbol,
                    "error": str(e),
                    "traceback": traceback.format_exc(),
                },
            )

            # Record failed execution
            self._record_execution(strategy_name, symbol, result, exception=e)

            return result

    def _fetch_market_data(self, symbol: str, parameters: Dict[str, Any]) -> Dict[str, Any]:
        """
        Fetch market data for strategy execution

        This is a placeholder method that would integrate with the data collection module.

        Args:
            symbol: Trading pair symbol
            parameters: Strategy parameters that may include timeframe, etc.

        Returns:
            Dictionary containing market data
        """
        # TODO: Integrate with DataCollectionTool
        # For now, return placeholder data
        logger.debug(f"Fetching market data for {symbol}")

        return {
            "kline": {},
            "indicators": {},
            "symbol": symbol,
            "timestamp": int(time.time()),
        }

    def _get_current_positions(self, symbol: str) -> List[Position]:
        """
        Get current positions for the symbol

        This is a placeholder method that would query the exchange for current positions.

        Args:
            symbol: Trading pair symbol

        Returns:
            List of current positions
        """
        # TODO: Integrate with exchange client to get actual positions
        # For now, return empty list
        logger.debug(f"Getting current positions for {symbol}")

        return []

    def _record_execution(
        self,
        strategy_name: str,
        symbol: str,
        result: ExecutionResult,
        exception: Optional[Exception] = None,
    ) -> None:
        """
        Record strategy execution details

        This method maintains a detailed log of all strategy executions including
        signals, orders, errors, and exceptions.

        Args:
            strategy_name: Name of the executed strategy
            symbol: Trading pair symbol
            result: Execution result
            exception: Exception if execution failed
        """
        try:
            record = {
                "timestamp": int(time.time()),
                "strategy_name": strategy_name,
                "symbol": symbol,
                "success": result.success,
                "signals_count": len(result.signals),
                "orders_count": len(result.orders),
                "execution_time": result.execution_time,
                "errors": result.errors,
            }

            # Record signal details
            if result.signals:
                record["signals"] = [
                    {
                        "symbol": sig.symbol,
                        "side": sig.side,
                        "entry_price": sig.entry_price,
                        "stop_loss": sig.stop_loss,
                        "take_profit": sig.take_profit,
                        "confidence": sig.confidence,
                        "timestamp": sig.timestamp,
                    }
                    for sig in result.signals
                ]

            # Record order details
            if result.orders:
                record["orders"] = [
                    {
                        "action_type": order.action_type,
                        "symbol": order.symbol,
                        "side": order.side,
                        "quantity": order.quantity,
                        "price": order.price,
                        "stop_loss": order.stop_loss,
                        "take_profit": order.take_profit,
                        "reason": order.reason,
                    }
                    for order in result.orders
                ]

            # Record exception details if present
            if exception:
                record["exception"] = {
                    "type": type(exception).__name__,
                    "message": str(exception),
                    "traceback": traceback.format_exc(),
                }

            self.execution_history.append(record)

            logger.info(
                f"Recorded execution: {strategy_name} on {symbol} - "
                f"Success: {result.success}, Signals: {len(result.signals)}, "
                f"Orders: {len(result.orders)}"
            )

        except Exception as e:
            logger.error(f"Failed to record execution: {str(e)}")

    def _record_order(
        self,
        order: OrderAction,
        strategy_name: str,
        execution_status: str = "pending",
    ) -> None:
        """
        Record individual order action with complete details

        Args:
            order: Order action to record
            strategy_name: Name of the strategy
            execution_status: Status of order execution ('pending' | 'executed' | 'failed')
        """
        try:
            order_record = {
                "timestamp": int(time.time()),
                "strategy_name": strategy_name,
                "action_type": order.action_type,
                "symbol": order.symbol,
                "side": order.side,
                "quantity": order.quantity,
                "price": order.price,
                "stop_loss": order.stop_loss,
                "take_profit": order.take_profit,
                "reason": order.reason,
                "execution_status": execution_status,
            }

            logger.info(
                f"Order recorded: {order.action_type} {order.symbol} {order.side} "
                f"qty={order.quantity} price={order.price} status={execution_status}"
            )

            # Store in context if available
            context = self.context_manager.get_context(strategy_name)
            context.add_order(order)

        except Exception as e:
            logger.error(f"Failed to record order: {str(e)}")

    def get_execution_history(
        self, strategy_name: Optional[str] = None, limit: Optional[int] = None
    ) -> List[Dict[str, Any]]:
        """
        Get execution history

        Args:
            strategy_name: Filter by strategy name (optional)
            limit: Limit number of records returned (optional)

        Returns:
            List of execution records
        """
        history = self.execution_history

        if strategy_name:
            history = [record for record in history if record.get("strategy_name") == strategy_name]

        if limit:
            history = history[-limit:]

        return history

    def clear_execution_history(self) -> None:
        """Clear all execution history"""
        count = len(self.execution_history)
        self.execution_history.clear()
        logger.info(f"Cleared {count} execution records")
