分别使用Cypher与python构建neo4j图谱
Cypher /ˈsaɪ.fər/ 赛佛儿语言
Cypher 是 Neo4j 图数据库的 声明式查询语言。
用来 创建节点、关系、查询图、更新或删除数据。
语法上有点类似 SQL,但面向 图模型(节点、边、属性)。
Neo4j 增删改查:增:增加一个节点create (n:Person {name:'我',age:31})带有关系属性create (p:Person{name:" 我 ",age:"31"})-[: 包 工 程 { 金 额 :10000}]->(n:Person{name:" 好 大 哥",age:"35"})删create (n:Person {name:'TYD',age:31})match (n:Person{name:"TYD"}) delete n删除关系match (p:Person{name:"我",age:"31"})-[f:包工程]->(n:Person{name:"好大哥",age:"35"})delete f改:加上标签match (t:Person) where id(t)=789 set t:好人 return t加上属性match (a:好人) where id(a)=789 set a.战斗力=200 return a修改属性match (a:好人) where id(a)=789 set a.战斗力=500 return a查:(查操作太多啦,直接参考 neo4j 例子就好)match (p:Person) - [:包工程] -> (n:Person) return p,n快速清空数据库:MATCH (n)DETACH DELETE n
上一篇博客中的demo
python与neo4j结合处理excel中的数据创建图谱
# -*- coding: utf-8 -*-
from py2neo import Node, Graph, Relationship,NodeMatcherclass DataToNeo4j(object):"""将excel中数据存入neo4j"""def __init__(self):
一、连接图谱,定义标签"""建立连接"""link = Graph("bolt://localhost:7687", auth=("neo4j", "weixuanlv0304"))self 指向 刚才连接好的图self.graph = link#self.graph = NodeMatcher(link)# 定义labelself.buy = 'buy'self.sell = 'sell'self.graph.delete_all()self.matcher = NodeMatcher(link)"""
二、简单创建结点已经边关系1、创建结点node3 = Node('animal' , name = 'cat')node4 = Node('animal' , name = 'dog') node2 = Node('Person' , name = 'Alice')node1 = Node('Person' , name = 'Bob') 2、创建边 结点2 关系 结点1r1 = Relationship(node2 , 'know' , node1) r2 = Relationship(node1 , 'know' , node3) r3 = Relationship(node2 , 'has' , node3) r4 = Relationship(node4 , 'has' , node2) 3、create 将结点和边添加到这个图中self.graph.create(node1)self.graph.create(node2)self.graph.create(node3)self.graph.create(node4)self.graph.create(r1)self.graph.create(r2)self.graph.create(r3)self.graph.create(r4)"""三、利用函数在图中创建实体结点def create_node(self, node_buy_key,node_sell_key):"""建立节点"""创建购买方结点for name in node_buy_key:buy_node = Node(self.buy, name=name)self.graph.create(buy_node)创建售卖方结点for name in node_sell_key:sell_node = Node(self.sell, name=name)self.graph.create(sell_node)def create_relation(self, df_data):"""建立联系""" m = 0for m in range(0, len(df_data)):try: print(list(self.matcher.match(self.buy).where("_.name=" + "'" + df_data['buy'][m] + "'")))print(list(self.matcher.match(self.sell).where("_.name=" + "'" + df_data['sell'][m] + "'")))rel = Relationship(self.matcher.match(self.buy).where("_.name=" + "'" + df_data['buy'][m] + "'").first(),df_data['money'][m], self.matcher.match(self.sell).where("_.name=" + "'" + df_data['sell'][m] + "'").first())self.graph.create(rel)except AttributeError as e:print(e, m)