上一篇文章主要介绍python中适配Neo4j的库py2neo的关于节点、关系、子图基本内容，本文继续介绍py2neo中Graph、事务、嵌入Cypher语句以及NodeSelector等。
1.Graph
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class py2neo.database.Graph(*uris, **settings)
Graph指的就是图数据库，需要传入连接的 URI，初始化参数有bolt、secure、host、http_port、https_port、bolt_port、user、password。
from py2neo import Graph
graph_1 = Graph()
graph_2 = Graph(host="localhost")
graph_3 = Graph("http://localhost:7474/db/data/")
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begin(autocommit=False) 开始一个事务
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create(subgraph) 事务操作创建一个子图
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exists(subgraph) 是否存在节点、关系或子图
from py2neo import Graph, Node, Relationship
g = Graph()
tx = g.begin()
a = Node("Person", name="Alice")
tx.create(a)
b = Node("Person", name="Bob")
ab = Relationship(a, "KNOWS", b)
tx.create(ab)
tx.commit()
print(g.exists(ab))
返回结果：True
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data(statement, parameters=None, **kwparameters)
利用data()获得查询结果，返回含有字典元素的列表
from py2neo import Graph
graph = Graph()
data=graph.data("MATCH (a:Person) RETURN a.name, a.born LIMIT 4")
print(data)
运行结果：
[{'a.born': 1964, 'a.name': 'Keanu Reeves'},
{'a.born': 1967, 'a.name': 'Carrie-Anne Moss'},
{'a.born': 1961, 'a.name': 'Laurence Fishburne'},
{'a.born': 1960, 'a.name': 'Hugo Weaving'}]
还可以通过pandas.DataFrame使结果转化为表格的形式
from py2neo import Graph
from pandas import DataFrame
graph = Graph()
data=DataFrame(graph.data("MATCH (a:Person) RETURN a.name, a.born LIMIT 4"))
print(data)
运行结果：
a.born a.name
0 1964 Keanu Reeves
1 1967 Carrie-Anne Moss
2 1961 Laurence Fishburne
3 1960 Hugo Weaving
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degree(subgraph) 返回度数（度就是指一个节点相关联边的数目）
from py2neo import Graph
graph = Graph()
node=graph.find_one(label='Resource',property_key='name',property_value='β-羟丁酸')
data=graph.degree(node)
print(data)
运行结果：
2
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delete(subgraph) 删除节点、关系或子图
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delete_all() 删除数据库所有的节点和关系
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evaluate(statement, parameters=None, **kwparameters) 返回第一条查询结果
from py2neo import Graph
graph = Graph()
data=graph.evaluate("MATCH (a:Person) RETURN a.name")
print(data)
运行结果：
Keanu Reeves
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find(*args, **kwargs) 需要传入的不定参数label、property_key、property_value、limit，返回符合筛选条件节点的生成器
from py2neo import Graph, Node
graph = Graph()
nodes=graph.find(label='Resource')
for node in nodes:
print(node)
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find_one(*args, **kwargs)需要传入的不定参数label、property_key、property_value，返回符合筛选条件一个节点，即使多个都满足，也会返回唯一节点。
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match(start_node=None, rel_type=None, end_node=None, bidirectional=False, limit=None) 匹配并返回所有满足条件的关系
for rel in graph.match(start_node=alice, rel_type="FRIEND"):
print(rel.end_node()["name"])
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match_one(start_node=None, rel_type=None, end_node=None, bidirectional=False)匹配并返回所有满足条件的一条关系
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push(subgraph) 更新节点、关系或子图
from py2neo import Graph, Node
graph = Graph()
a = Node('Person', name='xiaoming')
node = graph.find_one(label='Person')
node['age'] = 18
graph.push(node)
print(graph.find_one(label='Person'))
运行结果：
(a80d634:Person {age:18,name:"xiaoming"})
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run(statement, parameters=None, **kwparameters)运行一个cypher查询,返回cursors
from py2neo import Graph, Node
graph = Graph()
data=graph.run('MATCH (n:Person) RETURN n.name')
print(list(data))
运行结果：
[('n.name': 'xiaoming'),('n.name': 'xiaohong'),('n.name': 'xiaoliang')]
2.NodeSelector
NodeSelector是为更好的查询节点，支持更多的查询条件，比graph更友好
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select(*labels, **properties)返回NodeSelection类
from py2neo import Graph, NodeSelector
graph = Graph()
selector = NodeSelector(graph)
selected = selector.select("Person", name="Keanu Reeves")
list(selected)
运行结果：
[(f9726ea:Person {born:1964,name:"Keanu Reeves"})]
NodeSelection还有以下方法
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first()返回单个节点
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limit(amount)返回底部节点的限值条数
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skip(amount)返回顶部节点的限值条数
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order_by(*fields)排序
selection.order_by("_.name", "max(_.a, _.b)")
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where(*conditions, **properties)筛选条件
from py2neo import Graph, Node
graph = Graph()
selected = selector.select("Person").where("_.name =~ 'J.*'", "1960 <= _.born < 1970")
list(selected)
运行结果：
[(a03f6eb:Person {born:1967,name:"James Marshall"}),
(e59993d:Person {born:1966,name:"John Cusack"}),
(c44901e:Person {born:1960,name:"John Goodman"}),
(b141775:Person {born:1965,name:"John C. Reilly"}),
(e40244b:Person {born:1967,name:"Julia Roberts"})]
参考：http://py2neo.org/v3/index.html
注意：本文归作者所有，未经作者允许，不得转载
