
1.连接数据库(三种方式相等)
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graph_1 = Graph() graph_2 = Graph(host="localhost") graph_3 = Graph("http://localhost:7474/db/data")
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2.事务操作
a)直接返回结果
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graph.data("MATCH (a:Person) RETURN a.name, a.born LIMIT 4")
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b)以pandas格式返回结果
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DataFrame(graph.data("MATCH (a:Person) RETURN a.name, a.born LIMIT 4"))
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事务操作样例
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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() g.exists(ab)
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3.匹配关系
查找alice的所有朋友
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for rel in graph.match(start_node=alice,rel_type="FRIEND"): print(rel.end_node()['name'])
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4.带参数查询
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from py2neo import Graph g = Graph() # evaluate()返回结果的第一个值
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5.NodeSelector使用,可以使用Cypher语言的where部分
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from py2neo import Graph,NodeSelector graph = Graph() selector = NodeSelector(graph) slected = selector.select("Person",name="Keanu Reeves") list(selected) selected = selector.select("Person").where("_.name =~ 'J.*'","1960 <= _.born < 1970") list(selected)
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6.删除操作
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# 删除所有的 graph.delete_all()
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