"""
Parallel Agent Executor
========================
Provides parallel execution of multiple agents using asyncio.
"""

import asyncio
from typing import Any, Callable, Awaitable
from dataclasses import dataclass, field
from datetime import datetime, timezone
import logging

from agents.base import BaseAgent
from ledger.merkle import hash_leaf

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("ParallelExecutor")


@dataclass
class AgentTask:
    """Represents a task to be executed by an agent."""
    agent: BaseAgent
    input_data: dict[str, Any]
    task_id: str = ""
    
    def __post_init__(self):
        if not self.task_id:
            self.task_id = f"task_{hash_leaf(str(self.input_data))[:8]}"


@dataclass
class AgentResult:
    """Represents the result of an agent execution."""
    task_id: str
    agent_role: str
    input_data: dict[str, Any]
    output_data: dict[str, Any]
    success: bool
    error: str = ""
    execution_time_ms: float = 0
    timestamp: str = ""
    
    def __post_init__(self):
        if not self.timestamp:
            self.timestamp = datetime.now(timezone.utc).isoformat()


class ParallelExecutor:
    """
    Executes multiple agents in parallel using asyncio.gather.
    
    Features:
    - Concurrent agent execution
    - Error handling per agent
    - Result aggregation
    - Execution timing
    """
    
    def __init__(self, max_concurrency: int = 10):
        """
        Initialize the parallel executor.
        
        Args:
            max_concurrency: Maximum number of concurrent agent executions
        """
        self.max_concurrency = max_concurrency
        self.semaphore = asyncio.Semaphore(max_concurrency)
    
    async def execute_single(self, task: AgentTask) -> AgentResult:
        """
        Execute a single agent task with semaphore control.
        
        Args:
            task: The agent task to execute
            
        Returns:
            AgentResult with execution details
        """
        async with self.semaphore:
            start_time = asyncio.get_event_loop().time()
            
            try:
                output = await task.agent.run(task.input_data)
                execution_time = (asyncio.get_event_loop().time() - start_time) * 1000
                
                return AgentResult(
                    task_id=task.task_id,
                    agent_role=task.agent.role,
                    input_data=task.input_data,
                    output_data=output,
                    success=True,
                    execution_time_ms=execution_time
                )
            except Exception as e:
                execution_time = (asyncio.get_event_loop().time() - start_time) * 1000
                logger.error(f"Agent {task.agent.role} failed: {e}")
                
                return AgentResult(
                    task_id=task.task_id,
                    agent_role=task.agent.role,
                    input_data=task.input_data,
                    output_data={},
                    success=False,
                    error=str(e),
                    execution_time_ms=execution_time
                )
    
    async def execute_parallel(
        self, 
        tasks: list[AgentTask],
        return_exceptions: bool = False
    ) -> list[AgentResult]:
        """
        Execute multiple agent tasks in parallel.
        
        Args:
            tasks: List of AgentTask objects to execute
            return_exceptions: If True, exceptions are returned as results
            
        Returns:
            List of AgentResult objects
        """
        logger.info(f"Executing {len(tasks)} tasks in parallel (max concurrency: {self.max_concurrency})")
        
        # Create coroutines for all tasks
        coroutines = [self.execute_single(task) for task in tasks]
        
        # Execute all in parallel
        results = await asyncio.gather(*coroutines, return_exceptions=return_exceptions)
        
        # Handle any unexpected exceptions
        processed_results = []
        for i, result in enumerate(results):
            if isinstance(result, Exception):
                processed_results.append(AgentResult(
                    task_id=tasks[i].task_id,
                    agent_role=tasks[i].agent.role,
                    input_data=tasks[i].input_data,
                    output_data={},
                    success=False,
                    error=str(result)
                ))
            else:
                processed_results.append(result)
        
        successful = sum(1 for r in processed_results if r.success)
        logger.info(f"Parallel execution complete: {successful}/{len(tasks)} successful")
        
        return processed_results
    
    async def execute_with_dependencies(
        self,
        task_groups: list[list[AgentTask]]
    ) -> list[list[AgentResult]]:
        """
        Execute task groups sequentially, with tasks within each group running in parallel.
        
        Args:
            task_groups: List of task groups. Each group runs after the previous completes.
            
        Returns:
            List of result groups corresponding to task groups
        """
        all_results = []
        
        for i, group in enumerate(task_groups):
            logger.info(f"Executing task group {i + 1}/{len(task_groups)}")
            group_results = await self.execute_parallel(group)
            all_results.append(group_results)
        
        return all_results


def merge_results(results: list[AgentResult]) -> dict[str, Any]:
    """
    Merge multiple agent results into a combined output.
    
    Args:
        results: List of AgentResult objects
        
    Returns:
        Merged result dictionary
    """
    merged = {
        "total_agents": len(results),
        "successful": sum(1 for r in results if r.success),
        "failed": sum(1 for r in results if not r.success),
        "total_execution_time_ms": sum(r.execution_time_ms for r in results),
        "results": [],
        "errors": []
    }
    
    for result in results:
        if result.success:
            merged["results"].append({
                "agent": result.agent_role,
                "task_id": result.task_id,
                "output": result.output_data,
                "execution_time_ms": result.execution_time_ms
            })
        else:
            merged["errors"].append({
                "agent": result.agent_role,
                "task_id": result.task_id,
                "error": result.error
            })
    
    return merged