"""
数据接口核心业务逻辑模块

本模块包含了数据接口相关的所有核心业务逻辑函数，包括：
- 数据标准(data_standard)相关功能
- 数据标签(DataLabel)相关功能
- 图谱生成
- 动态标签识别等功能
"""

import logging
import re
from app.core.graph.graph_operations import connect_graph
from app.services.neo4j_driver import neo4j_driver

# 配置logger
logger = logging.getLogger(__name__)


def _build_category_filter_conditions(category_filter, params):
    """
    将 category_filter 转换为 Cypher 查询条件列表。
    支持:
    - 字典: {field: value, ...}
    - 列表: [{"field": "...", "value": "..."}, {"category": "xxx"}]
    - 字符串: 兼容旧用法，等同于按 category 字段过滤
    """
    conditions = []
    param_index = 0

    def add_condition(field, value):
        nonlocal param_index
        if value is None:
            return
        if not isinstance(field, str):
            return
        if not re.match(r"^[A-Za-z_][A-Za-z0-9_]*$", field):
            logger.warning(f"忽略非法属性字段: {field}")
            return
        param_key = f"category_filter_{param_index}"
        param_index += 1
        conditions.append(f"n.{field} CONTAINS ${param_key}")
        params[param_key] = value

    if isinstance(category_filter, dict):
        for field, value in category_filter.items():
            add_condition(field, value)
    elif isinstance(category_filter, list):
        for item in category_filter:
            if not isinstance(item, dict):
                continue
            if "field" in item and "value" in item:
                add_condition(item.get("field"), item.get("value"))
            elif len(item) == 1:
                field, value = next(iter(item.items()))
                add_condition(field, value)
    elif category_filter:
        add_condition("category", category_filter)

    return conditions


# 数据标准列表展示
def standard_list(
    skip_count,
    page_size,
    name_en_filter=None,
    name_zh_filter=None,
    category_filter=None,
    create_time_filter=None,
):
    """
    获取数据标准列表

    Args:
        skip_count: 跳过的记录数量
        page_size: 每页记录数量
        name_en_filter: 英文名称过滤条件
        name_zh_filter: 名称过滤条件
        category_filter: 分类过滤条件
        create_time_filter: 时间过滤条件

    Returns:
        tuple: (数据列表, 总记录数)
    """
    data = []

    # 构建查询条件
    where_clause = []
    params = {}
    if name_zh_filter:
        where_clause.append("n.name_zh CONTAINS $name_zh_filter")
        params['name_zh_filter'] = name_zh_filter
    if name_en_filter:
        where_clause.append("n.name_en CONTAINS $name_en_filter")
        params['name_en_filter'] = name_en_filter
    if category_filter:
        where_clause.append("n.category CONTAINS $category_filter")
        params['category_filter'] = category_filter
    if create_time_filter:
        where_clause.append("n.create_time CONTAINS $create_time_filter")
        params['create_time_filter'] = create_time_filter
    else:
        where_clause.append("TRUE")

    where_str = " AND ".join(where_clause)

    # 构建完整的查询语句
    cql = f"""
    MATCH (n:data_standard)
    WHERE {where_str}
    RETURN
        properties(n) as properties,
        n.create_time as create_time,
        id(n) as nodeid,
        size([(n)<-[]-() | 1]) + size([(n)-[]->() | 1]) as relationship_count
    ORDER BY create_time desc
    SKIP $skip_count
    LIMIT $page_size
    """
    params['skip_count'] = skip_count
    params['page_size'] = page_size

    # 修复：使用正确的session方式执行查询
    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(cql, **params)
            for record in result:
                properties = {
                    key: value for key, value in record['properties'].items()
                    if key not in ['input', 'code', 'output']
                }
                properties.setdefault("describe", None)

                new_attr = {
                    'id': record['nodeid'],
                    'number': record['relationship_count']
                }
                properties.update(new_attr)
                data.append(properties)

            # 获取总量
            total_query = (
                f"MATCH (n:data_standard) WHERE {where_str} "
                "RETURN COUNT(n) AS total"
            )
            total_record = session.run(total_query, **params).single()
            total = total_record["total"] if total_record else 0

            return data, total
    except (ConnectionError, ValueError) as e:
        logger.error(f"Neo4j数据库连接失败: {str(e)}")
        return [], 0
    finally:
        if driver:
            driver.close()


# 数据标准图谱展示（血缘关系）父节点
def standard_kinship_graph(nodeid):
    """
    生成数据标准的血缘关系图谱

    Args:
        nodeid: 节点ID

    Returns:
        图谱数据
    """
    # 查询语句
    cql = """
    MATCH(da:data_standard)
    WHERE id(da)=$nodeId
    OPTIONAL MATCH(a:DataResource)-[:clean_resource]-(da)
    OPTIONAL MATCH(b:DataModel)-[:clean_model]-(da)
    WITH
        collect({
            id:toString(id(a)),
            text:a.name,
            type:split(labels(a)[0],'_')[1]
        })+
        collect({
            id:toString(id(b)),
            text:b.name,
            type:split(labels(b)[0],'_')[1]
        })+
        collect({
            id:toString(id(da)),
            text:da.name,
            type:split(labels(da)[0],'_')[1]
        }) as nodes,
        da,
        collect({from:toString(id(a)),to:toString(id(da)),text:'标准'})+
        collect({from:toString(id(b)),to:toString(id(da)),text:'标准'}) as lines
    WITH
        toString(id(da)) as rootId,
        apoc.coll.toSet(lines) as lines,
        apoc.coll.toSet(nodes) as nodes
    RETURN nodes,lines,rootId
    """

    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(cql, nodeId=nodeid)
            res = {}
            for item in result:
                res = {
                    "nodes": [
                        record for record in item['nodes'] if record['id']
                    ],
                    "lines": [
                        record
                        for record in item['lines']
                        if record['from'] and record['to']
                    ],
                    "rootId": item['rootId']
                }
            return res
    except (ConnectionError, ValueError) as e:
        logger.error(f"Neo4j数据库连接失败: {str(e)}")
        return {}
    finally:
        if driver:
            driver.close()


# 数据标准图谱展示（影响关系）下游
def standard_impact_graph(nodeid):
    """
    生成数据标准的影响关系图谱

    Args:
        nodeid: 节点ID

    Returns:
        图谱数据
    """
    # 查询语句
    cql = """
        MATCH(da:data_standard)
        WHERE id(da)=$nodeId
        OPTIONAL MATCH(da)-[:clean_model]-(m1:DataMeta)-[:clean_model]-(da)
        OPTIONAL MATCH(da)-[:clean_model]-(m2:DataMeta)-[:clean_model]-(da)
        WITH
            collect({
                id:toString(id(da)),
                text:da.name,
                type:split(labels(da)[0],'_')[1]
            })+
            collect({id:toString(id(m1)),text:m1.name})+
            collect({id:toString(id(m2)),text:m2.name}) as nodes,
            da,
            collect({
                from:toString(id(da)),
                to:toString(id(m1)),
                text:'标准清洗'
            })+
            collect({
                from:toString(id(da)),
                to:toString(id(m2)),
                text:'标准清洗'
            }) as lines
        WITH
            toString(id(da)) as rootId,
            apoc.coll.toSet(lines) as lines,
            apoc.coll.toSet(nodes) as nodes
        RETURN nodes,lines,rootId
        """

    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(cql, nodeId=nodeid)
            res = {}
            for item in result:
                res = {
                    "nodes": [
                        record for record in item['nodes'] if record['id']
                    ],
                    "lines": [
                        record
                        for record in item['lines']
                        if record['from'] and record['to']
                    ],
                    "rootId": item['rootId']
                }
            return res
    except (ConnectionError, ValueError) as e:
        logger.error(f"Neo4j数据库连接失败: {str(e)}")
        return {}
    finally:
        if driver:
            driver.close()


# 数据标准图谱展示（所有关系）
def standard_all_graph(nodeid):
    """
    生成数据标准的所有关系图谱

    Args:
        nodeid: 节点ID

    Returns:
        图谱数据
    """
    # 查询语句
    cql = """
    MATCH(da:data_standard)
    WHERE id(da)=$nodeId
    OPTIONAL MATCH(a:DataResource)-[:clean_resource]-(da)
    OPTIONAL MATCH(b:DataModel)-[:clean_model]-(da)
    OPTIONAL MATCH(da)-[:clean_model]-(m1:DataMeta)-[:clean_model]-(da)
    OPTIONAL MATCH(da)-[:clean_model]-(m2:DataMeta)-[:clean_model]-(da)
    WITH
        collect({
            id:toString(id(a)),
            text:a.name,
            type:split(labels(a)[0],'_')[1]
        })+
        collect({
            id:toString(id(b)),
            text:b.name,
            type:split(labels(b)[0],'_')[1]
        })+
        collect({
            id:toString(id(da)),
            text:da.name,
            type:split(labels(da)[0],'_')[1]
        })+
        collect({id:toString(id(m1)),text:m1.name})+
        collect({id:toString(id(m2)),text:m2.name}) as nodes,
        da,
        collect({from:toString(id(a)),to:toString(id(da)),text:'标准'})+
        collect({from:toString(id(b)),to:toString(id(da)),text:'标准'})+
        collect({
            from:toString(id(da)),
            to:toString(id(m1)),
            text:'标准清洗'
        })+
        collect({
            from:toString(id(da)),
            to:toString(id(m2)),
            text:'标准清洗'
        }) as lines
    WITH
        toString(id(da)) as rootId,
        apoc.coll.toSet(lines) as lines,
        apoc.coll.toSet(nodes) as nodes
    RETURN nodes,lines,rootId
    """
    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(cql, nodeId=nodeid)
            res = {}
            for item in result:
                res = {
                    "nodes": [
                        record for record in item['nodes'] if record['id']
                    ],
                    "lines": [
                        record
                        for record in item['lines']
                        if record['from'] and record['to']
                    ],
                    "rootId": item['rootId']
                }
            return res
    except (ConnectionError, ValueError) as e:
        logger.error(f"Neo4j数据库连接失败: {str(e)}")
        return {}
    finally:
        if driver:
            driver.close()


# 数据标签列表展示
def label_list(
    skip_count,
    page_size,
    name_en_filter=None,
    name_zh_filter=None,
    category_filter=None,
    group_filter=None,
):
    """
    获取数据标签列表

    Args:
        skip_count: 跳过的记录数量
        page_size: 每页记录数量
        name_en_filter: 英文名称过滤条件
        name_zh_filter: 名称过滤条件
        category_filter: 分类过滤条件
        group_filter: 分组过滤条件

    Returns:
        tuple: (数据列表, 总记录数)
    """
    data = []

    # 构建查询条件
    where_clause = []
    params = {}
    if name_zh_filter:
        where_clause.append("n.name_zh CONTAINS $name_zh_filter")
        params['name_zh_filter'] = name_zh_filter
    if name_en_filter:
        where_clause.append("n.name_en CONTAINS $name_en_filter")
        params['name_en_filter'] = name_en_filter
    where_clause.extend(
        _build_category_filter_conditions(category_filter, params)
    )
    if group_filter:
        where_clause.append("n.group CONTAINS $group_filter")
        params['group_filter'] = group_filter

    if not where_clause:
        where_clause.append("TRUE")

    where_str = " AND ".join(where_clause)

    # 构建完整的查询语句
    cql = f"""
    MATCH (n:DataLabel)
    WHERE {where_str}
    WITH
        n,
        properties(n) as properties,
        n.create_time as create_time,
        id(n) as nodeid
    OPTIONAL MATCH (n)<-[r]-()
    WITH
        n,
        properties,
        create_time,
        nodeid,
        count(r) as incoming
    OPTIONAL MATCH (n)-[r]->()
    WITH
        n,
        properties,
        create_time,
        nodeid,
        incoming,
        count(r) as outgoing
    RETURN
        properties,
        create_time,
        nodeid,
        incoming + outgoing as relationship_count
    ORDER BY create_time desc
    SKIP $skip_count
    LIMIT $page_size
    """
    params['skip_count'] = skip_count
    params['page_size'] = page_size

    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(cql, **params)
            for record in result:
                properties = record['properties']
                new_attr = {
                    'id': record['nodeid'],
                    'number': record['relationship_count']
                }
                if "describe" not in properties:
                    properties["describe"] = None
                if "scope" not in properties:
                    properties["scope"] = None
                properties.update(new_attr)
                data.append(properties)

            # 获取总量
            total_query = (
                f"MATCH (n:DataLabel) WHERE {where_str} "
                "RETURN COUNT(n) AS total"
            )
            total_record = session.run(total_query, **params).single()
            total = total_record["total"] if total_record else 0

            return data, total
    except (ConnectionError, ValueError) as e:
        logger.error(f"Neo4j数据库连接失败: {str(e)}")
        return [], 0
    finally:
        if driver:
            driver.close()


# 数据标签图谱展示
def id_label_graph(id):
    """
    根据ID生成数据标签图谱

    Args:
        id: 节点ID

    Returns:
        图谱数据
    """
    query = """
    MATCH (n:DataLabel)
    WHERE id(n) = $nodeId
    OPTIONAL MATCH (a)-[:LABEL]-(n)
    WITH
       collect({
           from: toString(id(a)),
           to: toString(id(n)),
           text: "标签"
       }) AS line1,
       collect({
           id: toString(id(n)),
           text: n.name_zh,
           type:"label"
       }) AS node1,
       collect({
           id: toString(id(a)),
           text: a.name_zh,
           type: split(labels(a)[0], '_')[1]
       }) AS node2,
       n
    WITH
        apoc.coll.toSet(line1) AS lines,
        apoc.coll.toSet(node1 + node2) AS nodes,
        toString(id(n)) AS res
    RETURN lines, nodes, res
    """
    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(query, nodeId=id)
            res = {}
            for item in result:
                res = {
                    "nodes": [
                        record for record in item['nodes'] if record['id']
                    ],
                    "lines": [
                        record
                        for record in item['lines']
                        if record['from'] and record['to']
                    ],
                    "rootId": item['res'],
                }
            return res
    except (ConnectionError, ValueError) as e:
        logger.error(f"Neo4j数据库连接失败: {str(e)}")
        return {}
    finally:
        if driver:
            driver.close()


# 数据标签图谱展示（血缘关系）父节点/（所有关系）
def label_kinship_graph(nodeid):
    """
    生成数据标签的血缘关系图谱

    Args:
        nodeid: 节点ID

    Returns:
        图谱数据
    """
    # 查询语句
    cql = """
    MATCH(la:DataLabel)
    WHERE id(la)=$nodeId
    OPTIONAL MATCH(a:DataResource)-[:LABEL]-(la)
    OPTIONAL MATCH(b:DataModel)-[:LABEL]-(la)
    OPTIONAL MATCH(meta:DataMeta)-[:LABEL]-(la)
    OPTIONAL MATCH(d:data_standard)-[:LABEL]-(la)
    OPTIONAL MATCH(e:DataMetric)-[:LABEL]-(la)
    WITH
        collect({
            id:toString(id(a)),
            text:a.name_zh,
            type:split(labels(a)[0],'_')[1]
        })+
        collect({
            id:toString(id(b)),
            text:b.name_zh,
            type:split(labels(b)[0],'_')[1]
        })+
        collect({
            id:toString(id(d)),
            text:d.name_zh,
            type:split(labels(d)[0],'_')[1]
        })+
        collect({
            id:toString(id(e)),
            text:e.name_zh,
            type:split(labels(e)[0],'_')[1]
        })+
        collect({
            id:toString(id(la)),
            text:la.name_zh,
            type:split(labels(la)[0],'_')[1]
        })+
        collect({id:toString(id(meta)),text:meta.name_zh}) as nodes,
        la,
        collect({from:toString(id(a)),to:toString(id(la)),text:'标签'})+
        collect({from:toString(id(b)),to:toString(id(la)),text:'标签'})+
        collect({from:toString(id(meta)),to:toString(id(la)),text:'标签'})+
        collect({from:toString(id(d)),to:toString(id(la)),text:'标签'})+
        collect({from:toString(id(e)),to:toString(id(la)),text:'标签'}) as lines
    WITH
        toString(id(la)) as rootId,
        apoc.coll.toSet(lines) as lines,
        apoc.coll.toSet(nodes) as nodes
    RETURN nodes,lines,rootId
    """
    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(cql, nodeId=nodeid)
            res = {}
            for item in result:
                res = {
                    "nodes": [
                        record for record in item['nodes'] if record['id']
                    ],
                    "lines": [
                        record
                        for record in item['lines']
                        if record['from'] and record['to']
                    ],
                    "rootId": item['rootId']
                }
            return res
    except (ConnectionError, ValueError) as e:
        logger.error(f"Neo4j数据库连接失败: {str(e)}")
        return {}
    finally:
        if driver:
            driver.close()


# 数据标签图谱展示（影响关系）下游
def label_impact_graph(nodeid):
    """
    生成数据标签的影响关系图谱

    Args:
        nodeid: 节点ID

    Returns:
        图谱数据
    """
    # 查询语句
    cql = """
        MATCH(n:DataLabel)
        WHERE id(n)=$nodeId
        RETURN {
            id:toString(id(n)),
            text:(n.name_zh),
            type:"label"
        } AS nodes,
        toString(id(n)) as rootId
        """
    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(cql, nodeId=nodeid)
            res = {}
            for item in result:
                res = {
                    "nodes": item['nodes'],
                    "rootId": item['rootId'],
                    "lines": []
                }
            return res
    except (ConnectionError, ValueError) as e:
        logger.error(f"Neo4j数据库连接失败: {str(e)}")
        return {}
    finally:
        if driver:
            driver.close()


# 数据标签按照提交内容查询相似分组，并且返回
def dynamic_label_list(name_filter=None):
    """
    根据内容查询相似的数据标签分组

    Args:
        name_filter: 内容过滤条件

    Returns:
        标签分组列表
    """
    # 构建完整的查询语句
    cql = """
    MATCH (n:DataLabel)
    WITH
        n,
        apoc.text.levenshteinSimilarity(n.group, $name_filter) AS similarity
    WHERE similarity > 0.1 // 设置相似度阈值
    RETURN DISTINCT n.group as name_zh, id(n) as nodeid
    """

    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(cql, name_filter=name_filter or "")
            data = []
            for record in result:
                data.append(
                    {
                        "name_zh": record['name_zh'],
                        "id": record['nodeid'],
                    }
                )

            return data
    except (ConnectionError, ValueError) as e:
        logger.error(f"Neo4j数据库连接失败: {str(e)}")
        return []
    finally:
        if driver:
            driver.close()


def search_info(key, value):
    """
    搜索指定属性的节点信息

    Args:
        key: 搜索属性键
        value: 搜索属性值

    Returns:
        搜索结果列表
    """
    field_pattern = r"^[A-Za-z_][A-Za-z0-9_]*$"
    if not re.match(field_pattern, str(key)):
        logger.warning("非法属性键: %s", key)
        return []

    query = """
    MATCH (n)
    WHERE n[$field] =~ $pattern
    WITH
        n,
        properties(n) as properties,
        n.create_time as create_time,
        id(n) as nodeid
    RETURN properties, nodeid, create_time, labels(n) as labels
    LIMIT 30
    """

    driver = None
    try:
        driver = connect_graph()
    except (ConnectionError, ValueError) as e:
        logger.error(f"无法连接到Neo4j数据库: {str(e)}")
        return []

    try:
        with driver.session() as session:
            result = session.run(
                query,
                field=key,
                pattern=f"(?i).*{value}.*",
            )

            results = []
            for record in result:
                results.append(
                    {
                        "properties": record["properties"],
                        "id": record["nodeid"],
                        "create_time": record["create_time"],
                        "labels": record["labels"],
                    }
                )

            return results
    except Exception as e:
        logger.error(f"搜索节点信息失败: {str(e)}")
        return []
    finally:
        if driver:
            driver.close()


def label_info(id):
    """
    获取标签节点的信息

    Args:
        id: 节点ID

    Returns:
        标签节点信息
    """
    query = """
    MATCH (n)
    WHERE id(n) = $nodeId
    RETURN {
        id:toString(id(n)),
        text:(n.name_zh),
        type:"label"
    } AS nodes,
    toString(id(n)) as rootId
    """

    driver = None
    try:
        driver = connect_graph()
        with driver.session() as session:
            result = session.run(query, nodeId=id).data()
            return result[0] if result else {}
    except (ConnectionError, ValueError) as e:
        logger.error(f"无法连接到Neo4j数据库: {str(e)}")
        return {}
    finally:
        if driver:
            driver.close()


def graph_all(domain_id, include_meta=True):
    """
    获取完整关系图谱

    Args:
        domain_id: 节点ID
        include_meta: 是否包含元数据节点

    Returns:
        dict: 包含 nodes 与 lines 的图谱数据
    """
    try:
        domain_id_int = int(domain_id)
    except (ValueError, TypeError):
        logger.error(f"节点ID不是有效的整数: {domain_id}")
        return {"nodes": [], "lines": []}

    try:
        with neo4j_driver.get_session() as session:
            nodes = {}
            lines = {}

            # 使用路径查询同时获取节点和关系
            if include_meta:
                cypher = """
                MATCH (n)
                WHERE id(n) = $domain_id
                OPTIONAL MATCH path = (n)-[r]-(m)
                RETURN n,
                       collect(DISTINCT m) as related_nodes,
                       collect(DISTINCT r) as relationships
                """
            else:
                cypher = """
                MATCH (n)
                WHERE id(n) = $domain_id
                OPTIONAL MATCH path = (n)-[r]-(m)
                WHERE NOT (m:DataMeta)
                RETURN n,
                       collect(DISTINCT m) as related_nodes,
                       collect(DISTINCT r) as relationships
                """

            result = session.run(cypher, domain_id=domain_id_int)
            record = result.single()

            if not record:
                logger.warning(f"未找到节点: {domain_id_int}")
                return {"nodes": [], "lines": []}

            # 处理起始节点
            n_node = record["n"]
            if n_node:
                n_props = dict(n_node)
                n_labels = list(n_node.labels)
                n_props["id"] = domain_id_int
                n_props["node_type"] = n_labels[0] if n_labels else ""
                nodes[domain_id_int] = n_props

            # 处理关联节点
            related_nodes = record["related_nodes"] or []
            for m_node in related_nodes:
                if m_node is None:
                    continue
                m_elem_id = m_node.element_id
                m_id = int(m_elem_id.split(":")[-1])
                if m_id not in nodes:
                    m_props = dict(m_node)
                    m_labels = list(m_node.labels)
                    m_props["id"] = m_id
                    m_props["node_type"] = m_labels[0] if m_labels else ""
                    nodes[m_id] = m_props

            # 处理关系
            relationships = record["relationships"] or []
            for rel in relationships:
                if rel is None:
                    continue
                rel_elem_id = rel.element_id
                rel_id = rel_elem_id.split(":")[-1]
                if rel_id not in lines:
                    # 获取关系的起始和结束节点 ID
                    start_elem_id = rel.start_node.element_id
                    end_elem_id = rel.end_node.element_id
                    start_id = start_elem_id.split(":")[-1]
                    end_id = end_elem_id.split(":")[-1]
                    # 获取关系类型
                    rel_type = type(rel).__name__
                    lines[rel_id] = {
                        "id": rel_id,
                        "from": start_id,
                        "to": end_id,
                        "text": rel_type,
                    }

            logger.info(
                f"graph_all 结果: node_id={domain_id_int}, "
                f"nodes={len(nodes)}, lines={len(lines)}"
            )

            return {
                "nodes": list(nodes.values()),
                "lines": list(lines.values()),
            }
    except Exception as e:
        logger.error(f"获取图谱失败: {str(e)}")
        import traceback
        logger.error(traceback.format_exc())
        return {"nodes": [], "lines": []}


def node_delete(node_id):
    """
    删除 DataLabel 节点及其所有关联关系

    Args:
        node_id: 节点ID（整数）

    Returns:
        dict: 删除结果，包含 success 状态和 message 信息
    """
    driver = None
    try:
        driver = connect_graph()
    except (ConnectionError, ValueError) as e:
        logger.error(f"无法连接到Neo4j数据库: {str(e)}")
        return {"success": False, "message": "无法连接到数据库"}

    try:
        with driver.session() as session:
            # 首先检查节点是否存在且为 DataLabel 类型
            check_query = """
            MATCH (n:DataLabel)
            WHERE id(n) = $nodeId
            RETURN n
            """
            check_result = session.run(
                check_query,
                nodeId=node_id,
            ).single()

            if not check_result:
                logger.warning(f"DataLabel 节点不存在: ID={node_id}")
                return {
                    "success": False,
                    "message": f"DataLabel 节点不存在 (ID: {node_id})",
                }

            # 删除节点及其所有关系
            delete_query = """
            MATCH (n:DataLabel)
            WHERE id(n) = $nodeId
            DETACH DELETE n
            RETURN count(n) as deleted_count
            """
            delete_result = session.run(
                delete_query,
                nodeId=node_id,
            ).single()
            if not delete_result:
                logger.warning(f"删除结果为空: ID={node_id}")
                return {
                    "success": False,
                    "message": "删除失败，未获取到删除结果",
                }
            deleted_count = delete_result["deleted_count"]

            if deleted_count > 0:
                logger.info(f"成功删除 DataLabel 节点: ID={node_id}")
                return {
                    "success": True,
                    "message": (
                        f"成功删除 DataLabel 节点 (ID: {node_id})"
                    ),
                }
            else:
                logger.warning(f"删除失败，节点可能已被删除: ID={node_id}")
                return {"success": False, "message": "删除失败，节点可能已被删除"}
    except Exception as e:
        logger.error(f"删除 DataLabel 节点失败: {str(e)}")
        return {"success": False, "message": f"删除失败: {str(e)}"}
    finally:
        if driver:
            driver.close()