一、说在前面
1、使用工具：py2neo ，官方操作文档 ：https://py2neo.org/v4/index.html
2、还包括一些neo4j的命令操作
二、案例说明
1、数据展示
2、这个案例主要是读取Excel中的结构化数据购买方、销售方（节点）和金额（边），并实现在图中创建实体
三、相关代码
1、DataToNeo4jClass.py（连接neo4j，创建节点和关系的工具）
#
-*- coding: utf-8 -*-
from py2neo import Node, Graph, Relationship,NodeMatcher
class DataToNeo4j(object):
"""将excel中数据存入neo4j"""def__init__(self):
"""建立连接"""
link = Graph("http://localhost:7474", username="neo4j", password="wzs208751")
self.graph = link
#self.graph = NodeMatcher(link)# 定义label
self.buy = ‘buy‘
self.sell = ‘sell‘
self.graph.delete_all()
self.matcher = NodeMatcher(link)
"""
node3 = Node(‘animal‘ , name = ‘cat‘)
node4 = Node(‘animal‘ , name = ‘dog‘)
node2 = Node(‘Person‘ , name = ‘Alice‘)
node1 = Node(‘Person‘ , name = ‘Bob‘)
r1 = Relationship(node2 , ‘know‘ , node1)
r2 = Relationship(node1 , ‘know‘ , node3)
r3 = Relationship(node2 , ‘has‘ , node3)
r4 = Relationship(node4 , ‘has‘ , node2)
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)
"""def create_node(self, node_buy_key,node_sell_key):
"""建立节点"""for name in node_buy_key:
buy_node = Node(self.buy, name=name)
self.graph.create(buy_node)
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 = 0
for 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)
2、invoice_neo4j.py
#
-*- coding: utf-8 -*-
from utils.DataToNeo4jClass import DataToNeo4j
import os
import pandas as pd
#pip install py2neo==5.0b1 注意版本，要不对应不了
invoice_data = pd.read_excel(‘./Invoice_data_Demo.xls‘, header=0)
#print(invoice_data)#可以先阅读下文档：https://py2neo.org/v4/index.htmldef data_extraction():
"""节点数据抽取"""# 取出购买方名称到list
node_buy_key = []
for i in range(0, len(invoice_data)):
node_buy_key.append(invoice_data[‘购买方名称‘][i])
node_sell_key = []
for i in range(0, len(invoice_data)):
node_sell_key.append(invoice_data[‘销售方名称‘][i])
# 去除重复的发票名称
node_buy_key = list(set(node_buy_key))
node_sell_key = list(set(node_sell_key))
# value抽出作node
node_list_value = []
for i in range(0, len(invoice_data)):
for n in range(1, len(invoice_data.columns)):
# 取出表头名称invoice_data.columns[i] node_list_value.append(invoice_data[invoice_data.columns[n]][i])
# 去重
node_list_value = list(set(node_list_value))
# 将list中浮点及整数类型全部转成string类型
node_list_value = [str(i) for i in node_list_value]
return node_buy_key, node_sell_key,node_list_value
def relation_extraction():
"""联系数据抽取"""
links_dict = {}
sell_list = []
money_list = []
buy_list = []
for i in range(0, len(invoice_data)):
money_list.append(invoice_data[invoice_data.columns[19]][i])#金额
sell_list.append(invoice_data[invoice_data.columns[10]][i])#销售方方名称
buy_list.append(invoice_data[invoice_data.columns[6]][i])#购买方名称# 将数据中int类型全部转成string
sell_list = [str(i) for i in sell_list]
buy_list = [str(i) for i in buy_list]
money_list = [str(i) for i in money_list]
# 整合数据，将三个list整合成一个dict
links_dict[‘buy‘] = buy_list
links_dict[‘money‘] = money_list
links_dict[‘sell‘] = sell_list
# 将数据转成DataFrame
df_data = pd.DataFrame(links_dict)
print(df_data)
return df_data
relation_extraction()
create_data = DataToNeo4j()
create_data.create_node(data_extraction()[0], data_extraction()[1])
create_data.create_relation(relation_extraction())
四、Neo4j增删改查命令
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
原文：https://www.cnblogs.com/20183544-wangzhengshuai/p/14876534.html
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