"""
映射图模型
定义映射图的数据结构和业务逻辑
"""
from dataclasses import dataclass, field
from typing import Dict, List, Optional, Tuple
from models.field import Field
from models.mapping import Mapping, OperatorMapping, CodeMapping


@dataclass
class GraphNode:
    """
    图节点

    Attributes:
        field: 关联的字段
        x: X坐标
        y: Y坐标
    """

    field: Field
    x: float = 0.0
    y: float = 0.0

    def __hash__(self):
        """使节点可哈希"""
        return hash(self.field.id)

    def __eq__(self, other):
        """节点相等性比较"""
        if isinstance(other, GraphNode):
            return self.field.id == other.field.id
        return False


@dataclass
class GraphEdge:
    """
    图边

    Attributes:
        id: 边ID
        source_field_id: 源字段ID
        target_field_id: 目标字段ID
        mapping: 映射关系
        weight: 权重（用于最短路径计算）
    """

    source_field_id: int
    target_field_id: int
    mapping: Mapping
    id: Optional[int] = None
    weight: float = 1.0

    def to_dict(self) -> dict:
        """转换为字典"""
        return {
            'id': self.id,
            'source_field_id': self.source_field_id,
            'target_field_id': self.target_field_id,
            'mapping': self.mapping.to_dict() if self.mapping else None,
            'weight': self.weight,
        }


@dataclass
class MappingGraph:
    """
    映射图

    Attributes:
        nodes: 节点字典（字段ID -> 节点）
        edges: 边列表
    """

    nodes: Dict[int, GraphNode] = field(default_factory=dict)
    edges: List[GraphEdge] = field(default_factory=list)

    def add_node(self, node: GraphNode):
        """添加节点"""
        if node.field.id:
            self.nodes[node.field.id] = node

    def remove_node(self, field_id: int):
        """移除节点及相关的边"""
        if field_id in self.nodes:
            del self.nodes[field_id]
            # 移除相关的边
            self.edges = [e for e in self.edges
                          if e.source_field_id != field_id and e.target_field_id != field_id]

    def get_node(self, field_id: int) -> Optional[GraphNode]:
        """获取节点"""
        return self.nodes.get(field_id)

    def add_edge(self, edge: GraphEdge):
        """添加边"""
        # 确保源节点和目标节点存在
        if edge.source_field_id in self.nodes and edge.target_field_id in self.nodes:
            self.edges.append(edge)

    def remove_edge(self, edge_id: int):
        """移除边"""
        self.edges = [e for e in self.edges if e.id != edge_id]

    def get_edges_from(self, field_id: int) -> List[GraphEdge]:
        """获取从指定节点出发的所有边"""
        return [e for e in self.edges if e.source_field_id == field_id]

    def get_edges_to(self, field_id: int) -> List[GraphEdge]:
        """获取指向指定节点的所有边"""
        return [e for e in self.edges if e.target_field_id == field_id]

    def get_neighbors(self, field_id: int) -> List[int]:
        """获取节点的所有邻居节点ID"""
        return [e.target_field_id for e in self.edges if e.source_field_id == field_id]

    def has_path(self, source_id: int, target_id: int) -> bool:
        """检查两个节点之间是否存在路径"""
        if source_id not in self.nodes or target_id not in self.nodes:
            return False

        visited = set()
        queue = [source_id]

        while queue:
            current = queue.pop(0)
            if current == target_id:
                return True

            if current in visited:
                continue

            visited.add(current)
            neighbors = self.get_neighbors(current)
            queue.extend([n for n in neighbors if n not in visited])

        return False

    def get_all_paths(self, source_id: int, target_id: int,
                      max_depth: int = 10) -> List[List[int]]:
        """
        获取两个节点之间的所有路径

        Args:
            source_id: 源节点ID
            target_id: 目标节点ID
            max_depth: 最大搜索深度

        Returns:
            路径列表，每个路径是节点ID列表
        """
        if source_id not in self.nodes or target_id not in self.nodes:
            return []

        all_paths = []

        def dfs(current: int, target: int, path: List[int], visited: set, depth: int):
            if depth > max_depth:
                return

            if current == target:
                all_paths.append(path.copy())
                return

            visited.add(current)
            neighbors = self.get_neighbors(current)

            for neighbor in neighbors:
                if neighbor not in visited:
                    path.append(neighbor)
                    dfs(neighbor, target, path, visited, depth + 1)
                    path.pop()

            visited.remove(current)

        dfs(source_id, target_id, [source_id], set(), 0)
        return all_paths

    def to_dict(self) -> dict:
        """转换为字典"""
        return {
            'nodes': {fid: {'field': node.field.to_dict(), 'x': node.x, 'y': node.y}
                      for fid, node in self.nodes.items()},
            'edges': [e.to_dict() for e in self.edges],
        }

    def get_statistics(self) -> dict:
        """获取图的统计信息"""
        return {
            'node_count': len(self.nodes),
            'edge_count': len(self.edges),
            'avg_degree': len(self.edges) / len(self.nodes) if self.nodes else 0,
        }