"""
Command processor for handling GPU commands including thread management.
"""
from typing import Dict, Any, List
from threading import Lock
import time

class CommandProcessor:
    def __init__(self, hal, memory_manager):
        self.hal = hal
        self.memory_manager = memory_manager
        self.command_queue = []
        self.queue_lock = Lock()
        
    def add_command(self, command_type: str, **kwargs):
        """Add a command to the queue"""
        with self.queue_lock:
            self.command_queue.append({
                "type": command_type,
                "params": kwargs,
                "timestamp": time.time_ns()
            })
            
    def clear_commands(self):
        """Clear all pending commands"""
        with self.queue_lock:
            self.command_queue.clear()
            
    def submit_commands(self, chip_id: int = 0):
        """Submit and execute all queued commands"""
        results = []
        with self.queue_lock:
            for cmd in self.command_queue:
                if cmd["type"] == "execute_kernel":
                    result = self._execute_kernel_command(cmd["params"])
                elif cmd["type"] == "block_barrier":
                    result = self._handle_block_barrier(cmd["params"])
                elif cmd["type"] == "core_barrier":
                    result = self._handle_core_barrier(cmd["params"])
                elif cmd["type"] == "matmul":
                    result = self._handle_matmul(cmd["params"])
                elif cmd["type"] == "global_barrier":
                    result = self._handle_global_barrier(cmd["params"])
                else:
                    result = {"status": "error", "message": f"Unknown command type: {cmd['type']}"}
                    
                results.append(result)
                
            self.command_queue.clear()
        return results
        
    def _execute_kernel_command(self, params: Dict[str, Any]):
        """Execute a kernel across thread blocks"""
        try:
            chip_id = params["chip_id"]
            sm_id = params["sm_id"]
            core_id = params["core_id"]
            thread_config = params["thread_block_config"]
            kernel_func = params["kernel_func"]
            args = params.get("args", [])
            kwargs = params.get("kwargs", {})
            
            # Create thread blocks
            blocks_per_grid = (
                thread_config['grid_dim'][0] * 
                thread_config['grid_dim'][1] * 
                thread_config['grid_dim'][2]
            )
            
            threads_per_block = (
                thread_config['block_dim'][0] * 
                thread_config['block_dim'][1] * 
                thread_config['block_dim'][2]
            )
            
            # Initialize blocks
            blocks = []
            for block_idx in range(blocks_per_grid):
                block = {
                    'id': block_idx,
                    'threads': threads_per_block,
                    'shared_memory_size': thread_config['shared_memory_size'],
                    'results': []
                }
                blocks.append(block)
                
            # Execute kernel across blocks
            for block in blocks:
                # Execute threads in the block
                for thread_idx in range(block['threads']):
                    thread_id = block['id'] * block['threads'] + thread_idx
                    try:
                        result = kernel_func(
                            thread_id=thread_id,
                            block_id=block['id'],
                            *args,
                            **kwargs
                        )
                        block['results'].append({
                            'thread_id': thread_id,
                            'result': result,
                            'status': 'success'
                        })
                    except Exception as e:
                        block['results'].append({
                            'thread_id': thread_id,
                            'error': str(e),
                            'status': 'error'
                        })
                        
            return {
                'status': 'success',
                'blocks_executed': len(blocks),
                'total_threads': blocks_per_grid * threads_per_block,
                'results': [b['results'] for b in blocks]
            }
            
        except Exception as e:
            return {
                'status': 'error',
                'message': f'Kernel execution failed: {str(e)}'
            }
            
    def _handle_block_barrier(self, params: Dict[str, Any]):
        """Handle block-level thread synchronization"""
        try:
            chip_id = params["chip_id"]
            sm_id = params["sm_id"]
            core_id = params["core_id"]
            block_id = params["block_id"]
            
            # Signal barrier in hardware
            self.hal.block_barrier(chip_id, sm_id, core_id, block_id)
            
            return {
                'status': 'success',
                'message': f'Block barrier completed for block {block_id}'
            }
        except Exception as e:
            return {
                'status': 'error',
                'message': f'Block barrier failed: {str(e)}'
            }
            
    def _handle_core_barrier(self, params: Dict[str, Any]):
        """Handle core-level thread synchronization"""
        try:
            chip_id = params["chip_id"]
            sm_id = params["sm_id"]
            core_id = params["core_id"]
            
            # Signal barrier in hardware
            self.hal.core_barrier(chip_id, sm_id, core_id)
            
            return {
                'status': 'success',
                'message': f'Core barrier completed for core {core_id}'
            }
        except Exception as e:
            return {
                'status': 'error',
                'message': f'Core barrier failed: {str(e)}'
            }
            
    def _handle_matmul(self, params: Dict[str, Any]):
        """Handle matrix multiplication command"""
        try:
            return self.hal.matmul(
                params["chip_id"],
                params["sm_id"],
                params["A"],
                params["B"]
            )
        except Exception as e:
            return {
                'status': 'error',
                'message': f'Matrix multiplication failed: {str(e)}'
            }
            
    def _handle_global_barrier(self, params: Dict[str, Any]):
        """Handle global synchronization across all threads"""
        try:
            chip_id = params["chip_id"]
            
            # Signal global barrier in hardware
            self.hal.global_barrier(chip_id)
            
            return {
                'status': 'success',
                'message': f'Global barrier completed for chip {chip_id}'
            }
        except Exception as e:
            return {
                'status': 'error',
                'message': f'Global barrier failed: {str(e)}'
            }