数据类型和 Cypher 类型映射

from neo4j.time import Date

d = Date(year=2021, month=11, day=2)
print(d)  # '2021-11-02'

from neo4j.time import Time
import pytz

t = Time(hour=7, minute=47, nanosecond=4123, tzinfo=pytz.FixedOffset(-240))
print(t)  # '07:47:00.000004123-04:00'

from neo4j.time import Time

t = Time(hour=7, minute=47, nanosecond=4123)
print(t)  # '07:47:00.000004123'

from neo4j.time import DateTime
import pytz

dt = DateTime(year=2021, month=11, day=2, hour=7, minute=47, nanosecond=4123)
dt = pytz.timezone("US/Eastern").localize(dt)  # time zone localization (optional)
print(dt)  # '2021-11-02T07:47:00.000004123-04:00'

from neo4j.time import DateTime

dt = DateTime(year=2021, month=11, day=2, hour=7, minute=47, nanosecond=4123)
print(dt)  # '2021-11-02T07:47:00.000004123'

from neo4j.time import Duration

duration = Duration(years=1, days=2, seconds=3, nanoseconds=4)
print(duration)  # 'P1Y2DT3.000000004S'

from neo4j.spatial import CartesianPoint

# A 2D CartesianPoint
point = CartesianPoint((1.23, 4.56))
print(point.x, point.y, point.srid)
# 1.23 4.56 7203

# A 3D CartesianPoint
point = CartesianPoint((1.23, 4.56, 7.89))
print(point.x, point.y, point.z, point.srid)
# 1.23 4.56 7.8 9157

from neo4j.spatial import WGS84Point

# A 2D WGS84Point
point = WGS84Point((1.23, 4.56))
print(point.longitude, point.latitude, point.srid)
# or print(point.x, point.y, point.srid)
# 1.23 4.56 4326

# A 3D WGS84Point
point = WGS84Point((1.23, 4.56, 7.89))
print(point.longitude, point.latitude, point.height, point.srid)
# or print(point.x, point.y, point.z, point.srid)
# 1.23 4.56 7.89 4979

from neo4j import GraphDatabase


URI = "<URI for Neo4j database>"
AUTH = ("<Username>", "<Password>")

with GraphDatabase.driver(URI, auth=AUTH) as driver:
    records, _, _ = driver.execute_query(
        "MERGE (p:Person {name: $name}) RETURN p AS person",
        name="Alice",
        database_="neo4j",
    )
    for record in records:
        node = record["person"]
        print(f"Node ID: {node.element_id}\n"
              f"Labels: {node.labels}\n"
              f"Properties: {node.items()}\n"
        )

# Node ID: 4:73e9a61b-b501-476d-ad6f-8d7edf459251:0
# Labels: frozenset({'Person'})
# Properties: dict_items([('name', 'Alice')])

from neo4j import GraphDatabase


URI = "<URI for Neo4j database>"
AUTH = ("<Username>", "<Password>")

with GraphDatabase.driver(URI, auth=AUTH) as driver:
    records, _, _ = driver.execute_query("""
        MERGE (p:Person {name: $name})
        MERGE (p)-[r:KNOWS {status: $status, since: date()}]->(friend:Person {name: $friend_name})
        RETURN r AS friendship
        """, name="Alice", status="BFF", friend_name="Bob",
    )
    for record in records:
        relationship = record["friendship"]
        print(f"Relationship ID: {relationship.element_id}\n"
              f"Start node: {relationship.start_node}\n"
              f"End node: {relationship.end_node}\n"
              f"Type: {relationship.type}\n"
              f"Friends since: {relationship.get('since')}\n"
              f"All properties: {relationship.items()}\n"
        )

# Relationship ID: 5:73e9a61b-b501-476d-ad6f-8d7edf459251:1
# Start node: <Node element_id='4:73e9a61b-b501-476d-ad6f-8d7edf459251:0' labels=frozenset({'Person'}) properties={'name': 'Alice'}>
# End node: <Node element_id='4:73e9a61b-b501-476d-ad6f-8d7edf459251:2' labels=frozenset({'Person'}) properties={'name': 'Bob'}>
# Type: KNOWS
# Friends since: 2022-11-07
# All properties: dict_items([('since', neo4j.time.Date(2022, 11, 7)), ('status', 'BFF')])

from neo4j import GraphDatabase
from neo4j.time import Date


URI = "<URI for Neo4j database>"
AUTH = ("<Username>", "<Password>")

def add_friend(driver, name, status, date, friend_name):
    driver.execute_query("""
        MERGE (p:Person {name: $name})
        MERGE (p)-[r:KNOWS {status: $status, since: $date}]->(friend:Person {name: $friend_name})
        """, name=name, status=status, date=date, friend_name=friend_name,
        database_="neo4j",
    )

with GraphDatabase.driver(URI, auth=AUTH) as driver:
    # Create some :Person nodes linked by :KNOWS relationships
    add_friend(driver, name="Alice", status="BFF", date=Date.today(), friend_name="Bob")
    add_friend(driver, name="Bob", status="Fiends", date=Date.today(), friend_name="Sofia")
    add_friend(driver, name="Sofia", status="Acquaintances", date=Date.today(), friend_name="Sofia")

    # Follow :KNOWS relationships outgoing from Alice three times, return as path
    records, _, _ = driver.execute_query("""
        MATCH path=(:Person {name: $name})-[:KNOWS*3]->(:Person)
        RETURN path AS friendship_chain
        """, name="Alice",
        database_="neo4j",
    )
    path = records[0]["friendship_chain"]

    print("-- Path breakdown --")
    for friendship in path:
        print("{name} is friends with {friend} ({status})".format(
            name=friendship.start_node.get("name"),
            friend=friendship.end_node.get("name"),
            status=friendship.get("status"),
        ))