Neo4j图数据库导入数据

一.Neo4j简介

1.数据构成

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。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，如图1所示。

2.索引

Neo4j使用遍历操作进行查询。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

3.特点

查询的高性能

利用图结构进行查询，因此效率较高

设计的灵活性

开发的敏捷性

二.导入数据

#账号密码设置
    class MedicalGraph:
        def __init__(self):
            ...
            self.graph = Graph("http://localhost:7474", username="neo4j", password="自己的")
#获取数据路径
    cur_dir = '/'.join(os.path.abspath(__file__).split('/')[:-1])
    self.data_path = os.path.join(cur_dir, 'DATA/disease.csv')

#读取文件
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