重新选择neo-4j官方的与python交互包，尝试了py2neo包后发现对neo4j了解还不够，很多操作只是浅尝辄止，所以，决定阅读neo4j的官方开发驱动包，并尝试学习Cypher语言，这对以后对人物关系的挖掘是有帮助的．
1.概念
neo-4j由两部分组成:relationship,label和property,label或者relationship中包含property,label与label之间形成关系.
2.语法
2.1 Node语法 Cypher语言用()代表一个节点
1234 | ()(matrix)(matrix:Movie)(matrix:Movie{title:"The Matrix",released:1997}) |
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2.2 Relationship语法
1234567 | -->-[role]->-[:ACTED_IN]-># 关系的类型-[role:ACTED_IN]-># 关系的属性值,属性值可以是数组-[role:ACTED_IN {role:["Neo"]}]-> |
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2.3 Pattern语法 语法中有Node和Relationship
123 | (keanu:Person:Actor {name:"Keanu Reeves"})-[role:ACTED_IN {roles:["Neo"]}]->(matrix:Movie {title:"The matrix"}) |
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保存结点关系path
12 | # acted_in中保存的就是path,有很多函数可以对path操作:nodes(path),rels(paht),len(path)acted_in = (:Person)-[:ACTED_IN]->(:Movie) |
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创建数据及及结点关系
12345678 | CREATE (:MOVIE {title:"The Matrix",released:1997})CREATE (p:Person { name:"Keanu Reeves", born:1964 })RETURN p# 创建关系CREATE (a:Person { name:"Tom Hanks", born:1956 })-[r:ACTED_IN { roles: ["Forrest"]}]->(m:Movie { title:"Forrest Gump",released:1994 })CREATE (d:Person { name:"Robert Zemeckis", born:1951 })-[:DIRECTED]->(m)RETURN a,d,r,m |
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匹配pattern
1234567 | MATCH(m:Movie)RETURN mMATCH(p:Person {name:"duncan"})RETURN p# 匹配关系MATCH (p:Person { name:"Tom Hanks" })-[r:ACTED_IN]->(m:Movie)RETURN m.title, r.roles |
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添加节点并添加关系
1234 | MATCH (p:Person { name:"Tom Hanks" })CREATE (m:Movie { title:"Cloud Atlas",released:2012 })CREATE (p)-[r:ACTED_IN { roles: ['Zachry']}]->(m)RETURN p,r,m |
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更新结点属性,但不确定图中是否存在一个结点时(这样做的代价是开销很大),总之,使用MERGE,它没有找到就会创建.
123 | MERGE (m:Movie { title:"Cloud Atlas" })ON CREATE SET m.released = 2012RETURN m |
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2.4 where语法 以下两种写法相同
123 | MATCH (m:Movie)WHERE m.title = "The Matrix"RETURN m |
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12 | MATCH (m:Movie { title: "The Matrix" })RETURN m |
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123 | MATCH (p:Person)-[r:ACTED_IN]->(m:Movie)WHERE p.name =~ "K. " OR m.released > 2000 OR "Neo" IN r.rolesRETURN p,r,m |
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where子句可以用关系来判断
123 | MATCH (p:Person)-[:ACTED_IN]->(m)WHERE NOT (p)-[:DIRECTED]->()RETURN p,m |
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使用别名返回值
123 | MATCH (p:Person)RETURN p, p.name AS name, upper(p.name), coalesce(p.nickname,"n/a") AS nickname, { name: p.name, label:head(labels(p))} AS person |
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聚合函数
12 | MATCH (:Person)RETURN count(*) AS people |
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排序和分页
123 | MATCH (a:Person)-[:ACTED_IN]->(m:Movie)RETURN a,count(*) AS appearancesORDER BY appearances DESC LIMIT 10; |
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聚集
12 | MATCH (m:Movie)<-[:ACTED_IN]-(a:Person)RETURN m.title AS movie, collect(a.name) AS cast, count(*) AS actors |
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合并两个结果
12345 | MATCH (actor:Person)-[r:ACTED_IN]->(movie:Movie)RETURN actor.name AS name, type(r) AS acted_in, movie.title AS titleUNIONMATCH (director:Person)-[r:DIRECTED]->(movie:Movie)RETURN director.name AS name, type(r) AS acted_in, movie.title AS title |
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with语法保留中间结果
1234 | MATCH (person:Person)-[:ACTED_IN]->(m:Movie)WITH person, count(*) AS appearances, collect(m.title) AS moviesWHERE appearances > 1RETURN person.name, appearances, movies |
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增加约束
1 | CREATE CONSTRAINT ON (movie:Movie) ASSERT movie.title IS UNIQUE |
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创建索引
1 | CREATE INDEX ON :Actor(name) |
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2.4 Cypher操作
更新操作
1234 | MATCH (n {name: 'John'})-[:FRIEND]-(friend)WITH n, count(friend) AS friendsCountSET n.friendCount = friendsCountRETURN n.friendsCount |
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2.5 Cypher语法
2.5.1 CASE语法
12345678 | MATCH (n)RETURNCASE n.eyesWHEN 'blue'THEN 1WHEN 'brown'THEN 2ELSE 3 END AS result |
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12345678 | MATCH (n)RETURNCASEWHEN n.eyes = 'blue'THEN 1WHEN n.age < 40THEN 2ELSE 3 END AS result |
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2.5.2 带参数查询
12 | MATCH (n:Person { name: $name })RETURN n |
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2.5.3 定义正则表达式
1234 | MATCH (n:Person)# regex在之前定义WHERE n.name =~ $regexRETURN n.name |
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2.5.4 用json数据创建结点
12345678910 | { "props" : { "name" : "Andres", "position" : "Developer" }}CREATE ($props) |
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用json数据批量创建结点
12345678910111213141516171819202122 | { "props" : [ { "awesome" : true, "name" : "Andres", "position" : "Developer" }, { "children" : 3, "name" : "Michael", "position" : "Developer" } ]}UNWIND $props AS propertiesCREATE (n:Person)SET n = propertiesRETURN n |
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2.5.5 查询关系(限定跳数) a到b的跳数少于7跳
1 | (a)-[*..7]->(b) |
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2.5.6 Match 匹配关系
12345678 | # 不分方向--# 带有具体关系-[r]-# 指向关系--># 带有具体关系-[r]-> |
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两点之间最短长度的路径
123 | MATCH (martin:Person { name: 'Martin Sheen' }),(oliver:Person { name: 'Oliver Stone' }), p =shortestPath((martin)-[*..15]-(oliver))RETURN p |
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2.5.7 直接从CSV文件中批量插入结点数据
123456789 | # CSV文件内容:"1","ABBA","1992""2","Roxette","1986""3","Europe","1979""4","The Cardigans","1992"# queryLOAD CSV FROM '{csv-dir}/artists.csv' AS lineCREATE (:Artist { name: line[1], year: toInt(line[2])}) |
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当CSV文件包含大量数据时,使用USING PERIODIC COMMIT
123 | USING PERIODIC COMMITLOAD CSV FROM '{csv-dir}/artists.csv' AS lineCREATE (:Artist { name: line[1], year: toInt(line[2])}) |
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2.5.7 Set
123 | # 更新属性MATCH (peter { name: 'Peter' })SET peter = { hungry: TRUE , position: 'Entrepreneur' } |
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1234 | # 给结点增加标签MATCH (n { name: 'Stefan' })SET n :GermanRETURN n |
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2.5.8 Delete
1234567 | # 删除单节点MATCH (n:Useless)DELETE n# 删除一个结点及其所有关系MATCH (n { name: 'Andres' })DETACH DELETE n |
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2.5.9 Remove Remove和Delete不同之处在于,Delete用来删除结点,而Remove用来移除结点的属性和标签.
1234 | # 移除结点的age属性MATCH (n { name: 'Peter' })REMOVE n:GermanRETURN n |
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2.5.10 FOREACH
123 | MATCH p =(begin)-[*]->(END )WHERE begin.name = 'A' AND END .name = 'D'FOREACH (n IN nodes(p)| SET n.marked = TRUE ) |
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3.neo4j-python
安装驱动
1 | pip install neo4j-driver==1.1.0 |
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带参更新数据
1 | tx.run( "CREATE (person:Person {name: {name}, title: {title}})",parameters( "name", "Arthur", "title", "king" ) ); |
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123 | result = session.run("MATCH (weapon:Weapon) WHERE weapon.name CONTAINS {term} " "RETURN weapon.name", {"term": search_term}) |
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保存结果
12345678 | session = driver.session()result = session.run("MATCH (knight:Person:Knight) WHERE knight.castle = {castle} " "RETURN knight.name AS name", {"castle": "Camelot"})retained_result = list(result)session.close()for record in retained_result: print("%s is a knight of Camelot" % record["name"]) |
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