DataOps-platform/app/api/data_model/routes.py

from flask import request, jsonify
from app.api.data_model import bp
from app.models.result import success, failed
from app.api.graph.routes import MyEncoder
from app.core.data_model import model as model_functions
import json
import logging

# Configure logger
logger = logging.getLogger(__name__)

# 2024.09.11 数据模型血缘关系(传入数据资源id)
@bp.route('/model/data/relation', methods=['POST'])
def data_model_relation():
    try:
        # 传入请求参数
        receiver = request.get_json()
        resource_ids = receiver['id']  # 给定一个数据资源的id
        response_data = model_functions.handle_model_relation(resource_ids)
        res = success(response_data, "success")
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)
    except Exception as e:
        res = failed(str(e), 500, {})
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)


# 传入一个数据资源的id，返回多个有血缘关系的数据资源
@bp.route('/model/relatives/relation', methods=['POST'])
def data_relatives_relation():
    try:
        # 传入请求参数
        receiver = request.get_json()
        page = int(receiver.get('current', 1))
        page_size = int(receiver.get('size', 10))
        id = receiver['id']

        name_zh_filter = receiver.get('name_zh', None)
        category = receiver.get('category', None)
        time = receiver.get('time', None)

        # 计算跳过的记录的数量
        skip_count = (page - 1) * page_size

        data, total = model_functions.model_resource_list(skip_count, page_size, name_zh_filter, id, category, time)

        response_data = {'records': data, 'total': total, 'size': page_size, 'current': page}
        res = success(response_data, "success")
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)
    except Exception as e:
        res = failed(str(e), 500, {})
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)


# DDL数据模型保存
@bp.route('/data/model/save', methods=['POST'])
def data_model_save():
    # 传入请求参数
    receiver = request.get_json()
    data_model = receiver['name_zh']
    # DDL新增时，id_list（包含resource_id）不是必填项
    id_list = receiver.get('id_list', [])
    data_source = receiver.get('data_source')  # 获取data_source节点ID
    
    # resource_id和meta_id构成json格式
    result = json.dumps(id_list, ensure_ascii=False)
    try:
        # 从DDL中选取保存数据模型（支持data_source参数）
        result_list = [receiver['name_en']]
        id, data_model_node = model_functions.handle_data_model(data_model, result_list, result, receiver)
        
        # 只有在id_list不为空时才处理资源关系
        if id_list:
            model_functions.handle_no_meta_data_model(id_list, receiver, data_model_node)
        
        model_functions.calculate_model_level(id)

        # 创建BusinessDomain节点及其关联关系
        try:
            bd_id, bd_node = model_functions.handle_businessdomain_node(
                data_model, result_list, result, receiver, id_list
            )
            logger.info(f"成功创建BusinessDomain节点，ID: {bd_id}")
        except Exception as bd_error:
            # BusinessDomain创建失败不应该影响主流程
            logger.error(f"创建BusinessDomain节点失败（不中断主流程）: {str(bd_error)}")

        # 查询节点的实际属性（data_model_node 可能只是整数ID）
        from app.services.neo4j_driver import neo4j_driver
        with neo4j_driver.get_session() as session:
            node_query = """
            MATCH (n:DataModel) WHERE id(n) = $node_id
            RETURN n.name_zh as name_zh, n.name_en as name_en, n.description as description,
                   n.category as category, n.create_time as create_time, n.level as level,
                   n.tag as tag, n.leader as leader, n.origin as origin, n.frequency as frequency,
                   n.organization as organization, n.data_sensitivity as data_sensitivity, n.status as status
            """
            node_result = session.run(node_query, node_id=int(id))
            node_record = node_result.single()
        
        # 构建响应数据 - data_model包装格式
        response_data = {
            "data_model": {
                "id": id,
                "name_zh": node_record['name_zh'] if node_record else None,
                "name_en": node_record['name_en'] if node_record else None,
                "description": node_record['description'] if node_record else None,
                "category": node_record['category'] if node_record else None,
                "create_time": node_record['create_time'] if node_record else None,
                "level": node_record['level'] if node_record else None,
                "tag": node_record['tag'] if node_record else None,
                "leader": node_record['leader'] if node_record else None,
                "origin": node_record['origin'] if node_record else None,
                "frequency": node_record['frequency'] if node_record else None,
                "organization": node_record['organization'] if node_record else None,
                "data_sensitivity": node_record['data_sensitivity'] if node_record else None,
                "status": node_record['status'] if node_record else None,
                "data_source": data_source  # 数据源节点ID
            }
        }

        res = success(response_data, "success")
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)

    except Exception as e:
        res = failed(str(e), 500, {})
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)


# 新建数据模型请求接口(从数据资源中选取）
# @bp.route('/model/data/search', methods=['POST'])
@bp.route('/data/search', methods=['POST'])
def data_model_search():
    # 传入请求参数
    receiver = request.get_json()
    data_model = receiver['name_zh']
    id_list = receiver['id_list']
    data_source = receiver.get('data_source')  # 获取data_source节点ID
    
    # resource_id和meta_id构成json格式
    result = json.dumps(id_list, ensure_ascii=False)
    try:
        # 从数据资源中选取保存数据模型（支持data_source参数）
        from app.core.meta_data import translate_and_parse
        result_list = translate_and_parse(data_model)
        id, data_model_node = model_functions.handle_data_model(data_model, result_list, result, receiver)
        if id_list:
            model_functions.resource_handle_meta_data_model(id_list, id)
        model_functions.calculate_model_level(id)

        # 查询节点的实际属性（data_model_node 可能只是整数ID）
        from app.services.neo4j_driver import neo4j_driver
        with neo4j_driver.get_session() as session:
            node_query = """
            MATCH (n:DataModel) WHERE id(n) = $node_id
            RETURN n.name_zh as name_zh, n.name_en as name_en, n.description as description,
                   n.category as category, n.create_time as create_time, n.level as level,
                   n.tag as tag, n.leader as leader, n.origin as origin, n.frequency as frequency,
                   n.organization as organization, n.data_sensitivity as data_sensitivity, n.status as status
            """
            node_result = session.run(node_query, node_id=int(id))
            node_record = node_result.single()
        
        # 构建响应数据 - data_model包装格式
        response_data = {
            "data_model": {
                "id": id,
                "name_zh": node_record['name_zh'] if node_record else None,
                "name_en": node_record['name_en'] if node_record else None,
                "description": node_record['description'] if node_record else None,
                "category": node_record['category'] if node_record else None,
                "create_time": node_record['create_time'] if node_record else None,
                "level": node_record['level'] if node_record else None,
                "tag": node_record['tag'] if node_record else None,
                "leader": node_record['leader'] if node_record else None,
                "origin": node_record['origin'] if node_record else None,
                "frequency": node_record['frequency'] if node_record else None,
                "organization": node_record['organization'] if node_record else None,
                "data_sensitivity": node_record['data_sensitivity'] if node_record else None,
                "status": node_record['status'] if node_record else None,
                "data_source": data_source  # 数据源节点ID
            }
        }

        res = success(response_data, "success")
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)

    except Exception as e:
        res = failed(str(e), 500, {})
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)


# 新建数据模型请求接口(从数据模型中选取）
@bp.route('/model/data/model/add', methods=['POST'])
def data_model_model_add():
    # 传入请求参数 
    receiver = request.get_json()
    data_model = receiver['name_zh']
    id_list = receiver['id_list']
    data_source = receiver.get('data_source')  # 获取data_source节点ID
    
    # model_id和meta_id构成json格式
    result = json.dumps(id_list, ensure_ascii=False)
    try:
        # 从数据模型中选取保存数据模型
        # handle_data_model 已经处理了 data_source 关系创建（支持 int/dict/string 格式）
        from app.core.meta_data import translate_and_parse
        result_list = translate_and_parse(data_model)
        node_id, data_model_node = model_functions.handle_data_model(data_model, result_list, result, receiver)
        model_functions.model_handle_meta_data_model(id_list, node_id)
        model_functions.calculate_model_level(node_id)

        # 查询节点的实际属性（data_model_node 可能只是整数ID）
        from app.services.neo4j_driver import neo4j_driver
        with neo4j_driver.get_session() as session:
            node_query = """
            MATCH (n:DataModel) WHERE id(n) = $node_id
            RETURN n.name_zh as name_zh, n.name_en as name_en, n.description as description,
                   n.category as category, n.create_time as create_time, n.level as level,
                   n.tag as tag, n.leader as leader, n.origin as origin, n.frequency as frequency,
                   n.organization as organization, n.data_sensitivity as data_sensitivity, n.status as status
            """
            node_result = session.run(node_query, node_id=int(node_id))
            node_record = node_result.single()
        
        # 构建响应数据 - data_model包装格式
        response_data = {
            "data_model": {
                "id": node_id,
                "name_zh": node_record['name_zh'] if node_record else None,
                "name_en": node_record['name_en'] if node_record else None,
                "description": node_record['description'] if node_record else None,
                "category": node_record['category'] if node_record else None,
                "create_time": node_record['create_time'] if node_record else None,
                "level": node_record['level'] if node_record else None,
                "tag": node_record['tag'] if node_record else None,
                "leader": node_record['leader'] if node_record else None,
                "origin": node_record['origin'] if node_record else None,
                "frequency": node_record['frequency'] if node_record else None,
                "organization": node_record['organization'] if node_record else None,
                "data_sensitivity": node_record['data_sensitivity'] if node_record else None,
                "status": node_record['status'] if node_record else None,
                "data_source": data_source  # 数据源节点ID，与name_zh在同一级别
            }
        }

        res = success(response_data, "success")
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)

    except Exception as e:
        res = failed(str(e), 500, {})
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)


# 数据模型-详情接口
@bp.route('/data/model/detail', methods=['POST'])
def data_model_detail():
    try:
        # 传入请求参数
        receiver = request.get_json()
        # 直接使用字符串ID，不做类型转换
        id = receiver.get('id')
        print(f"Received id from frontend: {id}")

        result_data = model_functions.handle_id_model(id)
        
        # handle_id_model 返回的数据格式是 {"data_model": {...}}
        # 提取内部的 data_model 数据
        model_data = result_data.get("data_model", {})
        
        # 查询关联的数据源信息
        from app.services.neo4j_driver import neo4j_driver
        data_source_id = None
        try:
            model_id = int(id)
            with neo4j_driver.get_session() as session:
                # 查询数据模型关联的数据源节点
                ds_cypher = """
                MATCH (m:DataModel)-[:COME_FROM]->(ds:DataSource)
                WHERE id(m) = $model_id
                RETURN id(ds) as ds_id
                """
                ds_result = session.run(ds_cypher, model_id=model_id)
                ds_record = ds_result.single()
                
                if ds_record:
                    # 如果存在数据源关联，只返回ID
                    data_source_id = ds_record['ds_id']
                    logger.info(f"找到数据模型关联的数据源: model_id={model_id}, data_source_id={data_source_id}")
                else:
                    logger.info(f"数据模型未关联数据源: model_id={model_id}")
        except Exception as e:
            # 数据源查询失败不应该影响主流程
            logger.error(f"查询数据源关联失败（不中断主流程）: {str(e)}")
        
        # 删除 childrenId 字段（如果存在）
        if 'childrenId' in model_data:
            del model_data['childrenId']
        
        # 添加 data_source 字段
        model_data['data_source'] = data_source_id
        
        # 构建响应数据 - data_model包装格式
        response_data = {
            "data_model": model_data
        }
        
        res = success(response_data, "success")
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)

    except Exception as e:
        import traceback
        traceback.print_exc()
        res = failed(str(e), 500, {})
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)


# 删除数据模型
@bp.route('/data/model/delete', methods=['POST'])
def data_model_delete():
    try:
        # 传入请求参数
        receiver = request.get_json()
        id = receiver.get('id')
        print(f"Deleting data model with id: {id}")

        # 首先删除数据模型节点
        from app.services.neo4j_driver import neo4j_driver
        query = """
        MATCH (n:DataModel) where id(n) = $nodeId
        detach delete n
        """
        with neo4j_driver.get_session() as session:
            session.run(query, nodeId=id)

        res = success({}, "success")
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)

    except Exception as e:
        import traceback
        traceback.print_exc()
        res = failed(str(e), 500, {})
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)


# 列表 数据模型查询
@bp.route('/data/model/list', methods=['POST'])
def data_model_list():
    try:
        # 传入请求参数
        receiver = request.get_json()
        page = int(receiver.get('current', 1))
        page_size = int(receiver.get('size', 10))
        name_zh_filter = receiver.get('name_zh', None)
        name_en_filter = receiver.get('name_en', None)
        category = receiver.get('category', None)
        tag = receiver.get('tag', None)
        level = receiver.get('level', None)

        # 计算跳过的记录的数量
        skip_count = (page - 1) * page_size

        data, total = model_functions.model_list(skip_count, page_size, name_en_filter,
                                 name_zh_filter, category, tag, level)

        response_data = {'records': data, 'total': total, 'size': page_size, 'current': page}
        res = success(response_data, "success")
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)
    except Exception as e:
        res = failed(str(e), 500, {})
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)


# 数据模型的图谱（血缘关系Kinship+影响关系Impact+所有关系all+社区关系community）
@bp.route('/data/model/graph/all', methods=['POST'])
def data_model_graph_all():
    try:
        # 传入请求参数
        receiver = request.get_json()
        type = receiver['type'] # kinship/impact/all/community

        if type == 'community':
            # 社区图谱查询，提取tag参数
            tag = receiver.get('tag', None)
            result = model_functions.model_community(tag)
        else:
            # 非社区查询时才提取nodeid和meta参数
            nodeid = receiver.get('id')
            meta = receiver.get('meta', False) # true/false 是否返回元数据
            
            if type == 'kinship':
                result = model_functions.model_kinship_graph(nodeid, meta)
            elif type == 'impact':
                result = model_functions.model_impact_graph(nodeid, meta)
            else:
                result = model_functions.model_all_graph(nodeid, meta)
        return json.dumps(success(result, "success"), ensure_ascii=False, cls=MyEncoder)
    except Exception as e:
        return json.dumps(failed(str(e), 500, {}), ensure_ascii=False, cls=MyEncoder)


# 数据模型的列表图谱
@bp.route('/data/model/list/graph', methods=['POST'])
def data_model_list_graph():
    try:
        # 传入请求参数
        receiver = request.get_json()

        if not receiver or 'tag' not in receiver:
            raise ValueError("Missing 'tag' parameter in request body")

        nodeid = receiver['tag']

        # 构建查询条件
        params = {}
        where_clause = ""

        if nodeid is not None:
            where_clause = "MATCH (n)-[:LABEL]->(la) WHERE id(la) = $nodeId"
            params['nodeId'] = nodeid

        from app.services.neo4j_driver import neo4j_driver
        query = f"""
        MATCH (n:DataModel)
        OPTIONAL MATCH (n)-[:child]->(child)
        {where_clause}
        WITH 
            collect(DISTINCT {{id: toString(id(n)), text: n.name_zh, type: split(labels(n)[0], '_')[1]}}) AS nodes,
            collect(DISTINCT {{id: toString(id(child)), text: child.name_zh, type: split(labels(child)[0], '_')[1]}}) AS nodes2,
            collect(DISTINCT {{from: toString(id(n)), to: toString(id(child)), text: '下级'}}) AS lines
        RETURN nodes + nodes2 AS nodes, lines AS lines
        """

        with neo4j_driver.get_session() as session:
            result = session.run(query, **params)
            data = result.data()
            
            if len(data) > 0:
                # 过滤掉空节点（即 id 为 null 的节点）
                nodes = []
                for node in data[0]['nodes']:
                    if node['id'] != 'null':
                        nodes.append(node)
                
                lines = data[0]['lines']
                
                response_data = {
                    'nodes': nodes,
                    'edges': lines
                }
                
                return json.dumps(success(response_data, "success"), ensure_ascii=False, cls=MyEncoder)
            else:
                return json.dumps(success({'nodes': [], 'edges': []}, "No data found"), ensure_ascii=False, cls=MyEncoder)
    
    except Exception as e:
        return json.dumps(failed(str(e), 500, {}), ensure_ascii=False, cls=MyEncoder)


# 更新数据模型
@bp.route('/data/model/update', methods=['POST'])
def data_model_update():
    try:
        # 传入请求参数
        receiver = request.get_json()
        
        result = model_functions.data_model_edit(receiver)
        
        return json.dumps(success(result, "success"), ensure_ascii=False, cls=MyEncoder)
    except Exception as e:
        return json.dumps(failed(str(e), 500, {}), ensure_ascii=False, cls=MyEncoder)


# 数据模型关联元数据搜索
@bp.route('/search', methods=['POST'])
def data_model_metadata_search():
    """数据模型关联元数据搜索"""
    try:
        # 获取分页和筛选参数
        receiver = request.get_json()
        page = int(receiver.get('current', 1))
        page_size = int(receiver.get('size', 10))
        model_id = receiver.get('id')
        
        name_en_filter = receiver.get('name_en')
        name_zh_filter = receiver.get('name_zh')
        category_filter = receiver.get('category')
        tag_filter = receiver.get('tag')
        
        if model_id is None:
            return json.dumps(failed("模型ID不能为空", 400, {}), ensure_ascii=False, cls=MyEncoder)
            
        # 确保传入的ID为整数
        try:
            model_id = int(model_id)
        except (ValueError, TypeError):
            return json.dumps(failed(f"模型ID必须为整数, 收到的是: {model_id}", 400, {}), ensure_ascii=False, cls=MyEncoder)
            
        # 记录请求信息
        logger.info(f"获取数据模型关联元数据请求，ID: {model_id}")
            
        # 调用业务逻辑查询关联元数据
        metadata_list, total_count = model_functions.model_search_list(
            model_id, 
            page, 
            page_size, 
            name_en_filter, 
            name_zh_filter, 
            category_filter, 
            tag_filter
        )
        
        # 返回结果
        response_data = {
            "records": metadata_list,
            "total": total_count,
            "size": page_size,
            "current": page
        }
        res = success(response_data, "success")
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)
    except Exception as e:
        logger.error(f"数据模型关联元数据搜索失败: {str(e)}")
        res = failed(str(e), 500, {})
        return json.dumps(res, ensure_ascii=False, cls=MyEncoder)