19.1 Neo4j简介与环境准备 #

• Neo4j：全球最流行的图数据库，适合存储和分析复杂关系数据。
• Python驱动：官方推荐neo4j包，支持Neo4j 4.x/5.x。

19.2 安装Neo4j与Python驱动 #

# 安装Python驱动
pip install neo4j

19.3 Python连接Neo4j数据库 #

详细讲解： 本节演示如何使用Python官方驱动连接本地Neo4j数据库。首先导入驱动包，然后设置连接参数（地址、用户名、密码），最后通过with语句创建连接和会话，执行一条简单的Cypher查询（RETURN 1 AS test），并输出结果。推荐用with语句自动管理资源，避免连接泄漏。

# 导入Neo4j官方驱动包
from neo4j import GraphDatabase

# 设置连接地址，bolt协议，默认端口7687
uri = "bolt://localhost:7687"
# 设置用户名
user = "neo4j"
# 设置密码
password = "12345678"

# 创建驱动对象，推荐用with语句自动关闭连接
with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    # 创建会话对象，同样用with语句自动关闭
    with driver.session() as session:
        # 执行Cypher查询，返回结果对象
        result = session.run("RETURN 1 AS test")
        # 取出结果中的test字段并打印
        print(result.single()["test"])

19.4 节点的创建与批量创建 #

19.4.1 单个节点创建 #

def create_node(tx, label, properties):
    query = f"CREATE (n:{label} $props) RETURN n"
    result = tx.run(query, props=properties)
    return result.single()[0]

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        node = session.execute_write(create_node, "Person", {"name": "Alice", "age": 30, "occupation": "Engineer"})
        print("Created node:", node)

19.4.2 批量创建节点 #

def create_nodes(tx, data):
    query = "UNWIND $data AS item CREATE (n:Person {name: item.name, age: item.age})"
    tx.run(query, data=data)

persons = [
    {"name": "Bob", "age": 25},
    {"name": "Charlie", "age": 35},
    {"name": "Diana", "age": 28}
]

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        session.execute_write(create_nodes, persons)
        print("Created 3 nodes")

19.5 关系的创建 #

def create_relationship(tx, from_name, to_name, rel_type, properties=None):
    query = (
        "MATCH (a:Person {name: $from_name}), (b:Person {name: $to_name}) "
        f"CREATE (a)-[r:{rel_type}]->(b) "
        "SET r += $props "
        "RETURN r"
    )
    props = properties if properties else {}
    result = tx.run(query, from_name=from_name, to_name=to_name, props=props)
    return result.single()[0]

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        relationship = session.execute_write(create_relationship, "Alice", "Bob", "KNOWS", {"since": 2020})
        print("Created relationship:", relationship)

19.6 节点与关系的查询 #

19.6.1 查询所有Person节点 #

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        result = session.run("MATCH (n:Person) RETURN n.name, n.age")
        for record in result:
            print(record["n.name"], record["n.age"])

19.6.2 查询关系 #

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        result = session.run("MATCH (a:Person)-[r:KNOWS]->(b:Person) RETURN a.name, b.name, r.since")
        for record in result:
            print(f"{record['a.name']} knows {record['b.name']} since {record['r.since']}")

19.7 属性操作（增删改查） #

19.7.1 修改属性 #

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        session.run("MATCH (n:Person {name: 'Alice'}) SET n.city = 'Beijing'")

19.7.2 删除属性 #

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        session.run("MATCH (n:Person {name: 'Alice'}) REMOVE n.city")

19.7.3 删除节点和关系 #

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        session.run("MATCH (n:Person {name: 'Diana'}) DETACH DELETE n")

19.8 复杂查询与聚合 #

19.8.1 聚合统计 #

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        result = session.run("MATCH (n:Person) RETURN count(n) AS total")
        print("Total persons:", result.single()["total"])

19.8.2 分组统计 #

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        result = session.run("MATCH (n:Person) RETURN n.age, count(*) AS num")
        for record in result:
            print(f"Age {record['n.age']}: {record['num']}")

19.9 时间类型与APOC扩展用法 #

19.9.1 创建带时间的事件节点 #

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        session.run("CREATE (:Event {name: '会议', time: datetime()})")
        session.run("CREATE (:Event {name: '发布会', time: datetime('2024-06-01T09:00:00')})")

19.9.2 查询并格式化时间（APOC） #

with GraphDatabase.driver(uri, auth=(user, password)) as driver:
    with driver.session() as session:
        result = session.run("""
            MATCH (e:Event)
            RETURN e.name, apoc.temporal.format(e.time, 'yyyy-MM-dd HH:mm') AS time
            LIMIT 5
        """)
        for record in result:
            print(f"{record['e.name']} at {record['time']}")

19.10 最佳实践与常见问题 #

1. 用with语句管理连接，避免资源泄漏
2. 参数化查询，防止注入
3. 批量操作用UNWIND提升效率
4. 注意Neo4j与Python时间格式的差异
5. 遇到连接/认证问题，检查端口、用户名、密码、APOC插件是否启用