Neo4j

参考链接：链接

1 简介

Neo4j使用图相关的概念来描述数据模型，把数据保存为图中的节点以及节点之间的关系。

Neo4j中的数据

数据主要由三部分构成： * 节点。节点表示对象实例，每个节点有唯一的ID区别其它节点，节点带有属性； * 关系。就是图里面的边，连接两个节点，另外这里的关系是有向的并带有属性； * 属性。key-value对，存在于节点和关系中。

Neo4j中的查询

Neo4j使用遍历操作(图遍历)进行查询。为了加速查询，Neo4j会建立索引，并根据索引找到遍历用的起始节点。

用户可以创建任意数量的命名索引。每个索引控制节点或者关系，而每个索引都通过key/value/object三个参数来工作。其中object要么是一个节点，要么是一个关系，取决于索引类型。另外，Neo4j中有关于节点（关系）的索引，系统通过索引实现从属性到节点（关系）的映射。

  • 作用：
    • 查找操作：系统通过设定访问条件比如，遍历的方向，使用深度优先或广度优先算法等条件对图进行遍历，从一个节点沿着关系到其他节点。
    • 删除操作：Neo4j可以快速的插入删除节点和关系，并更新节点和关系中的属性。

Cypher--Neo4j的查询语言

作为Neo4j的查询语言，Cypher是一个描述性的Graph查询语言，不用编写Graph的遍历代码的查询方式。Cypher受SQL等的影响，拥有like,order by等关键字。查询示例：

MATCH (d:Disease)-[:HAS_SYMPTOM]->(s) WHERE d.name='糖尿病' RETURN d.name,s.name

上面的查询语言会返回'糖尿病'的'症状'。

下载和使用

下载链接：Neo4J(快) Neo4J官网(慢...)

可以直接下载Desktop版，比较好直接上手。

关于操作，移步这里

实例之数据导入Neo4j图数据库

参考项目：链接

数据导入的文件：build_graph.py,该文件中的代码详解：

  • a.主体类 MedicalGraph 介绍 
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    class MedicalGraph:
        def __init__(self):
            pass
        
        # 读取文件，获得实体，实体关系
        def read_file(self):
            psss
        # 创建节点
        def create_node(self, label, nodes):
            pass
        # 创建疾病节点的属性
        def create_diseases_nodes(self, disease_info):
            pass
        # 创建知识图谱实体
        def create_graphNodes(self):
            pass
        # 创建实体关系边
        def create_graphRels(self):
            pass
        # 创建实体关系边
        def create_relationship(self, start_node, end_node, edges, rel_type, rel_name):
            pass
  • b.主体类 MedicalGraph 中关键代码

链接 Neo4j 图数据库 

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self.graph = Graph("http://localhost:7474", username="neo4j", password="设定的密码")
读取文件，获得实体，实体关系 
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def read_file(self):
        """
        读取文件，获得实体，实体关系
        :return:
        """
        # cols = ["name", "alias", "part", "age", "infection", "insurance", "department", "checklist", "symptom",
        #         "complication", "treatment", "drug", "period", "rate", "money"]
        # 实体
        diseases = []  # 疾病
        aliases = []  # 别名
        symptoms = []  # 症状
        parts = []  # 部位
        departments = []  # 科室
        complications = []  # 并发症
        drugs = []  # 药品

        # 疾病的属性：age, infection, insurance, checklist, treatment, period, rate, money
        diseases_infos = []
        # 关系
        disease_to_symptom = []  # 疾病与症状关系
        disease_to_alias = []  # 疾病与别名关系
        diseases_to_part = []  # 疾病与部位关系
        disease_to_department = []  # 疾病与科室关系
        disease_to_complication = []  # 疾病与并发症关系
        disease_to_drug = []  # 疾病与药品关系

        all_data = pd.read_csv(self.data_path, encoding='gb18030').loc[:, :].values
        for data in all_data:
            disease_dict = {}  # 疾病信息
            # 疾病
            disease = str(data[0]).replace("...", " ").strip()
            disease_dict["name"] = disease
            # 别名
            line = re.sub("[，、；,.;]", " ", str(data[1])) if str(data[1]) else "未知"
            for alias in line.strip().split():
                aliases.append(alias)
                disease_to_alias.append([disease, alias])
            # 部位
            part_list = str(data[2]).strip().split() if str(data[2]) else "未知"
            for part in part_list:
                parts.append(part)
                diseases_to_part.append([disease, part])
            # 年龄
            age = str(data[3]).strip()
            disease_dict["age"] = age
            # 传染性
            infect = str(data[4]).strip()
            disease_dict["infection"] = infect
            # 医保
            insurance = str(data[5]).strip()
            disease_dict["insurance"] = insurance
            # 科室
            department_list = str(data[6]).strip().split()
            for department in department_list:
                departments.append(department)
                disease_to_department.append([disease, department])
            # 检查项
            check = str(data[7]).strip()
            disease_dict["checklist"] = check
            # 症状
            symptom_list = str(data[8]).replace("...", " ").strip().split()[:-1]
            for symptom in symptom_list:
                symptoms.append(symptom)
                disease_to_symptom.append([disease, symptom])
            # 并发症
            complication_list = str(data[9]).strip().split()[:-1] if str(data[9]) else "未知"
            for complication in complication_list:
                complications.append(complication)
                disease_to_complication.append([disease, complication])
            # 治疗方法
            treat = str(data[10]).strip()[:-4]
            disease_dict["treatment"] = treat
            # 药品
            drug_string = str(data[11]).replace("...", " ").strip()
            for drug in drug_string.split()[:-1]:
                drugs.append(drug)
                disease_to_drug.append([disease, drug])
            # 治愈周期
            period = str(data[12]).strip()
            disease_dict["period"] = period
            # 治愈率
            rate = str(data[13]).strip()
            disease_dict["rate"] = rate
            # 费用
            money = str(data[14]).strip() if str(data[14]) else "未知"
            disease_dict["money"] = money

            diseases_infos.append(disease_dict)

        return set(diseases), set(symptoms), set(aliases), set(parts), set(departments), set(complications), \
                set(drugs), disease_to_alias, disease_to_symptom, diseases_to_part, disease_to_department, \
                disease_to_complication, disease_to_drug, diseases_infos
创建节点:

不包含属性的节点: 

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def create_node(self, label, nodes):
    """
    创建节点
    :param label: 标签
    :param nodes: 节点
    :return:
    """
    count = 0
    for node_name in nodes:
        node = Node(label, name=node_name)
        self.graph.create(node)
        count += 1
        print(count, len(nodes))
    return
带有属性节点: 
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def create_diseases_nodes(self, disease_info):
    """
    创建疾病节点的属性
    :param disease_info: list(Dict)
    :return:
    """
    count = 0
    for disease_dict in disease_info:
        node = Node("Disease", name=disease_dict['name'], age=disease_dict['age'],
                    infection=disease_dict['infection'], insurance=disease_dict['insurance'],
                    treatment=disease_dict['treatment'], checklist=disease_dict['checklist'],
                    period=disease_dict['period'], rate=disease_dict['rate'],
                    money=disease_dict['money'])
        self.graph.create(node)
        count += 1
        print(count)
    return
创建知识图谱实体: 
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def create_graphNodes(self):
    """
    创建知识图谱实体
    :return:
    """
    disease, symptom, alias, part, department, complication, drug, rel_alias, rel_symptom, rel_part, \
    rel_department, rel_complication, rel_drug, rel_infos = self.read_file()
    self.create_diseases_nodes(rel_infos)
    self.create_node("Symptom", symptom)
    self.create_node("Alias", alias)
    self.create_node("Part", part)
    self.create_node("Department", department)
    self.create_node("Complication", complication)
    self.create_node("Drug", drug)

    return
创建知识图谱关系: 
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def create_graphRels(self):
    disease, symptom, alias, part, department, complication, drug, rel_alias, rel_symptom, rel_part, \
    rel_department, rel_complication, rel_drug, rel_infos = self.read_file()

    self.create_relationship("Disease", "Alias", rel_alias, "ALIAS_IS", "别名")
    self.create_relationship("Disease", "Symptom", rel_symptom, "HAS_SYMPTOM", "症状")
    self.create_relationship("Disease", "Part", rel_part, "PART_IS", "发病部位")
    self.create_relationship("Disease", "Department", rel_department, "DEPARTMENT_IS", "所属科室")
    self.create_relationship("Disease", "Complication", rel_complication, "HAS_COMPLICATION", "并发症")
    self.create_relationship("Disease", "Drug", rel_drug, "HAS_DRUG", "药品")
创建实体关系边: 
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def create_relationship(self, start_node, end_node, edges, rel_type, rel_name):
    """
    创建实体关系边
    :param start_node:
    :param end_node:
    :param edges:
    :param rel_type:
    :param rel_name:
    :return:
    """
    count = 0
    # 去重处理
    set_edges = []
    for edge in edges:
        set_edges.append('###'.join(edge))
    all = len(set(set_edges))
    for edge in set(set_edges):
        edge = edge.split('###')
        p = edge[0]
        q = edge[1]
        query = "match(p:%s),(q:%s) where p.name='%s'and q.name='%s' create (p)-[rel:%s{name:'%s'}]->(q)" % (
            start_node, end_node, p, q, rel_type, rel_name)
        try:
            self.graph.run(query)
            count += 1
            print(rel_type, count, all)
        except Exception as e:
            print(e)
    return