"""
工具函数
"""

import os
import shutil
import tempfile
import logging
from pathlib import Path
from typing import Optional, Dict, Any, List, Tuple
import numpy as np
import trimesh

logger = logging.getLogger(__name__)

def validate_file(file_path: str, max_size_mb: int = 50) -> Tuple[bool, str]:
    """
    验证上传的文件
    
    Args:
        file_path: 文件路径
        max_size_mb: 最大文件大小（MB）
    
    Returns:
        (是否有效, 错误信息)
    """
    try:
        if not os.path.exists(file_path):
            return False, "文件不存在"
        
        # 检查文件大小
        file_size_mb = os.path.getsize(file_path) / (1024 * 1024)
        if file_size_mb > max_size_mb:
            return False, f"文件太大: {file_size_mb:.1f}MB > {max_size_mb}MB"
        
        # 检查文件扩展名
        file_ext = Path(file_path).suffix.lower()
        supported_formats = ['.obj', '.glb', '.ply', '.stl']
        if file_ext not in supported_formats:
            return False, f"不支持的文件格式: {file_ext}"
        
        # 尝试加载文件
        try:
            mesh = trimesh.load(file_path, force='mesh')
            if not hasattr(mesh, 'vertices') or len(mesh.vertices) == 0:
                return False, "文件无法解析为有效的3D模型"
        except Exception as e:
            return False, f"文件格式错误: {str(e)}"
        
        return True, "文件有效"
        
    except Exception as e:
        return False, f"文件验证失败: {str(e)}"

def get_model_info(file_path: str) -> Dict[str, Any]:
    """
    获取模型信息
    
    Args:
        file_path: 模型文件路径
    
    Returns:
        模型信息字典
    """
    try:
        mesh = trimesh.load(file_path, force='mesh')
        
        # 计算基本信息
        vertex_count = len(mesh.vertices) if hasattr(mesh, 'vertices') else 0
        face_count = len(mesh.faces) if hasattr(mesh, 'faces') else 0
        
        # 计算包围盒
        if vertex_count > 0:
            bounds = mesh.bounds
            size = bounds[1] - bounds[0]
            center = (bounds[0] + bounds[1]) / 2
        else:
            size = np.array([0, 0, 0])
            center = np.array([0, 0, 0])
        
        # 计算表面积和体积
        surface_area = mesh.area if hasattr(mesh, 'area') else 0
        volume = mesh.volume if hasattr(mesh, 'volume') else 0
        
        return {
            'file_name': os.path.basename(file_path),
            'file_size_mb': os.path.getsize(file_path) / (1024 * 1024),
            'vertex_count': vertex_count,
            'face_count': face_count,
            'bounding_box': {
                'min': bounds[0].tolist() if vertex_count > 0 else [0, 0, 0],
                'max': bounds[1].tolist() if vertex_count > 0 else [0, 0, 0],
                'size': size.tolist(),
                'center': center.tolist()
            },
            'surface_area': float(surface_area),
            'volume': float(volume),
            'is_watertight': mesh.is_watertight if hasattr(mesh, 'is_watertight') else False,
            'is_closed': mesh.is_closed if hasattr(mesh, 'is_closed') else False
        }
        
    except Exception as e:
        logger.error(f"Failed to get model info: {str(e)}")
        return {
            'file_name': os.path.basename(file_path),
            'error': str(e)
        }

def cleanup_temp_files(temp_dir: str, keep_files: Optional[List[str]] = None):
    """
    清理临时文件
    
    Args:
        temp_dir: 临时目录
        keep_files: 需要保留的文件列表
    """
    try:
        if not os.path.exists(temp_dir):
            return
        
        for file_name in os.listdir(temp_dir):
            file_path = os.path.join(temp_dir, file_name)
            
            if keep_files and file_name in keep_files:
                continue
            
            try:
                if os.path.isfile(file_path):
                    os.remove(file_path)
                elif os.path.isdir(file_path):
                    shutil.rmtree(file_path)
            except Exception as e:
                logger.warning(f"Failed to remove {file_path}: {str(e)}")
                
    except Exception as e:
        logger.error(f"Cleanup failed: {str(e)}")

def format_processing_time(seconds: float) -> str:
    """
    格式化处理时间
    
    Args:
        seconds: 秒数
    
    Returns:
        格式化的时间字符串
    """
    if seconds < 60:
        return f"{seconds:.1f}秒"
    elif seconds < 3600:
        minutes = seconds / 60
        return f"{minutes:.1f}分钟"
    else:
        hours = seconds / 3600
        return f"{hours:.1f}小时"

def get_prompt_suggestions(model_info: Dict[str, Any]) -> List[str]:
    """
    根据模型信息获取提示建议
    
    Args:
        model_info: 模型信息
    
    Returns:
        提示建议列表
    """
    suggestions = []
    
    # 基于文件名的建议
    file_name = model_info.get('file_name', '').lower()
    
    if any(keyword in file_name for keyword in ['human', 'person', 'character', 'boy', 'girl']):
        suggestions.extend([
            "realistic human skeleton for walking animations",
            "character with full body rig for game animation",
            "human bone structure suitable for motion capture"
        ])
    elif any(keyword in file_name for keyword in ['dog', 'cat', 'animal', 'pet']):
        suggestions.extend([
            "four-legged animal with spine and tail bones",
            "quadruped skeleton for natural movement",
            "animal bone structure with flexible spine"
        ])
    elif any(keyword in file_name for keyword in ['bird', 'eagle', 'chicken']):
        suggestions.extend([
            "bird skeleton with wing bones for flight",
            "avian bone structure with hollow bones",
            "bird with articulated wings and tail"
        ])
    elif any(keyword in file_name for keyword in ['robot', 'mech', 'mechanical']):
        suggestions.extend([
            "mechanical robot with joint articulation",
            "industrial robot with precise joint control",
            "mech suit with hydraulic joint system"
        ])
    else:
        suggestions.extend([
            "articulated skeleton suitable for animation",
            "flexible bone structure for general movement",
            "skeleton with natural joint hierarchy"
        ])
    
    # 基于模型复杂度的建议
    vertex_count = model_info.get('vertex_count', 0)
    if vertex_count > 10000:
        suggestions.append("detailed skeleton for high-poly model")
    elif vertex_count < 1000:
        suggestions.append("simple skeleton for low-poly model")
    
    return suggestions[:5]  # 限制建议数量

def create_processing_status(stage: str, progress: float, message: str) -> Dict[str, Any]:
    """
    创建处理状态信息
    
    Args:
        stage: 处理阶段
        progress: 进度 (0-1)
        message: 状态消息
    
    Returns:
        状态信息字典
    """
    return {
        'stage': stage,
        'progress': min(max(progress, 0.0), 1.0),
        'message': message,
        'timestamp': __import__('time').time()
    }

def estimate_processing_time(model_info: Dict[str, Any]) -> float:
    """
    估算处理时间
    
    Args:
        model_info: 模型信息
    
    Returns:
        估算的处理时间（秒）
    """
    try:
        vertex_count = model_info.get('vertex_count', 1000)
        face_count = model_info.get('face_count', 1000)
        
        # 基于模型复杂度的简单估算
        complexity_factor = (vertex_count + face_count) / 10000
        base_time = 30  # 基础处理时间30秒
        
        estimated_time = base_time * (1 + complexity_factor * 0.5)
        return min(estimated_time, 120)  # 最多120秒
        
    except Exception:
        return 60  # 默认60秒

def generate_download_filename(original_name: str, suffix: str) -> str:
    """
    生成下载文件名
    
    Args:
        original_name: 原始文件名
        suffix: 后缀
    
    Returns:
        新文件名
    """
    base_name = os.path.splitext(original_name)[0]
    return f"{base_name}_{suffix}"

def safe_json_serialize(obj: Any) -> Any:
    """
    安全的JSON序列化
    
    Args:
        obj: 要序列化的对象
    
    Returns:
        可序列化的对象
    """
    if isinstance(obj, np.ndarray):
        return obj.tolist()
    elif isinstance(obj, np.floating):
        return float(obj)
    elif isinstance(obj, np.integer):
        return int(obj)
    elif isinstance(obj, dict):
        return {k: safe_json_serialize(v) for k, v in obj.items()}
    elif isinstance(obj, list):
        return [safe_json_serialize(item) for item in obj]
    else:
        return obj