Jsonld数据转入neo4j第三种代码案例

以下是将JSON-LD数据转换为Neo4j图形数据库的第三种代码示例：

from py2neo import Graph, Node, Relationship

# 创建Neo4j图形数据库连接
graph = Graph(password="password")

# 将JSON-LD数据转换为Python字典
json_ld_data = {
  "@context": "http://schema.org",
  "@type": "Person",
  "name": "John Smith",
  "jobTitle": "Software Engineer",
  "telephone": "(123) 456-7890",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "123 Main St",
    "addressLocality": "Anytown",
    "addressRegion": "CA",
    "postalCode": "12345",
    "addressCountry": "US"
  }
}

# 创建Neo4j节点
person_node = Node("Person", name=json_ld_data['name'], jobTitle=json_ld_data['jobTitle'], telephone=json_ld_data['telephone'])
address_node = Node("PostalAddress", streetAddress=json_ld_data['address']['streetAddress'], addressLocality=json_ld_data['address']['addressLocality'], addressRegion=json_ld_data['address']['addressRegion'], postalCode=json_ld_data['address']['postalCode'], addressCountry=json_ld_data['address']['addressCountry'])

# 添加节点到Neo4j图形数据库
graph.create(person_node)
graph.create(address_node)

# 创建关系并将其添加到Neo4j图形数据库
person_address_relationship = Relationship(person_node, "HAS_ADDRESS", address_node)
graph.create(person_address_relationship)

这段代码首先建立了与Neo4j图形数据库的连接，然后将JSON-LD数据转换为Python字典。接下来，它创建了两个Neo4j节点，一个表示“Person”类型，另一个表示“PostalAddress”类型。然后，它将这些节点添加到图形数据库中。最后，它创建了一个关系，将“Person”节点与“PostalAddress”节点连接起来，并将该关系添加到图形数据库中。