At this point, we should take a look at the Cypher type system. As Neo4j is written in Java (the j in Neo4j stands for Java after all), there are some discrepancies between the types stored in the Neo4j database and native Python types.
Some values like strings, floats, booleans, and nulls map directly to Python types, but more complex types need special handling.
Python Types to Neo4j Types
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For more information about Temporal Data Types, see Temporal Data Types.
Let’s take a look at some of these types in more detail.
Nodes & Relationships
Nodes and Relationships are both returned as similar classes.
As an example, let’s take the following code snippet:
Unresolved directive in lesson.adoc - include::https://raw.githubusercontent.com/neo4j-graphacademy/llm-chatbot-typescript/main/example/results.py[tag=run]The query will return one record for each :Person and :Movie node with an :ACTED_IN relationship between them.
Nodes
We can retrieve the movie value from a record using the [] brackets method, providing a string that refers to the alias for the :Movie node in the Cypher statement.
Unresolved directive in lesson.adoc - include::https://raw.githubusercontent.com/neo4j-graphacademy/llm-chatbot-typescript/main/example/results.py[tag=node]The value assigned to the node variable will be the instance of a Node.
Node is a type provided by the Neo4j Python Driver to hold the information held in Neo4j for the node.
Unresolved directive in lesson.adoc - include::https://raw.githubusercontent.com/neo4j-graphacademy/llm-chatbot-typescript/main/example/results.py[tag=node_info]-
The
idproperty provides access to the node’s Internal ID
eg.1234 -
The
labelsproperty is a frozenset containing an array of labels attributed to the Node
eg.['Person', 'Actor'] -
The
items()method provides access to the node’s properties as an iterable of all name-value pairs.
eg.{name: 'Tom Hanks', tmdbId: '31' } -
A single property can be retrieved by either using
[]brackets or using theget()method. Theget()method also allows you to define a default property if none exists.
Internal IDs
Internal IDs refer to the position in the Neo4j store files where the record is held. These numbers can be re-used, a best practice is to always look up a node by an indexed property rather than relying on an internal ID.Relationships
Relationship objects are similar to a Node in that they provide the same method for accessing the internal ID and properties.
Unresolved directive in lesson.adoc - include::https://raw.githubusercontent.com/neo4j-graphacademy/llm-chatbot-typescript/main/example/results.py[tag=rel]-
The
idproperty holds the internal ID of the relationship.
eg.9876 -
The
typeproperty holds the relationship type
eg.ACTED_IN -
The
items()method provides access to the relationships’s properties as an iterable of all name-value pairs.
eg.{role: 'Woody'} -
As with Nodes, you can access a single relationship property using brackets or the
get()method. -
start_node- an integer representing the internal ID for the node at the start of the relationship -
end_node- an integer representing the internal ID for the node at the end of the relationship
Paths
If you return a path of nodes and relationships, they will be returned as an instance of a Path.
Unresolved directive in lesson.adoc - include::https://raw.githubusercontent.com/neo4j-graphacademy/llm-chatbot-typescript/main/example/results.py[tag=path]-
start_node- a Neo4jIntegerrepresenting the internal ID for the node at the start of the path -
end_node- a Neo4jIntegerrepresenting the internal ID for the node at the end of the path -
len(path)- A count of the number of relationships within the path -
relationships- An array ofRelationshipobjects within the path.
Path Segments
A path is split into segments representing each relationship in the path.
For example, say we have a path of (p:Person)-[:ACTED_IN]→(m:Movie)-[:IN_GENRE]→(g:Genre), there would be two relationships.
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(p:Person)-[:ACTED_IN]→(m:Movie) -
(m:Movie)-[:IN_GENRE]→(g:Genre)
The relationships within a path can be iterated over using the iter() function.
Unresolved directive in lesson.adoc - include::https://raw.githubusercontent.com/neo4j-graphacademy/llm-chatbot-typescript/main/example/results.py[tag=segments]Temporal Data Types
Temporal data types are implemented by the neo4j.time module.
It provides a set of types compliant with ISO-8601 and Cypher, which are similar to those found in the built-in datetime module. Sub-second values are measured to nanosecond precision and the types are compatible with pytz.
The table below shows the general mappings between Cypher and the temporal types provided by the driver.
In addition, the built-in temporal types can be passed as parameters and will be mapped appropriately.
| Neo4j Cypher Type | Python driver type | Python built-in type | tzinfo |
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Date |
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Time |
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LocalTime |
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DateTime |
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LocalDateTime |
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Duration |
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Unresolved directive in lesson.adoc - include::https://raw.githubusercontent.com/neo4j-graphacademy/llm-chatbot-typescript/main/example/results.py[tag=temporal]Each of the above types has a number of attributes for accessing the different, for example year, month, day, and in the case of the types that include a time, hour, minute and second.
For more information, see Temporal Data Types&.
Spatial Data Types
Cypher has built-in support for handling spatial values (points), and the underlying database supports storing these point values as properties on nodes and relationships.
Points
| Cypher Type | Python Type |
|---|---|
Point |
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Point (Cartesian) |
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Point (WGS-84) |
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CartesianPoint
A Cartesian Point can be created in Cypher by supplying x and y values to the point() function.
The optional z value represents the height.
To create a Cartesian Point in Python, you can import the neo4j.spatial.CartesianPoint class.
# Using X and Y values
twoD=CartesianPoint((1.23, 4.56))
print(twoD.x, twoD.y)
# Using X, Y and Z
threeD=CartesianPoint((1.23, 4.56, 7.89))
print(threeD.x, threeD.y, threeD.z)For more information, see the Python reference.
WGS84Point
A WGS84 Point can be created in Cypher by supplying latitude and longitude values to the point() function.
To create a Cartesian Point in Python, you can import the neo4j.spatial.WGS84Point class.
london=WGS84Point((-0.118092, 51.509865))
print(london.longitude, london.latitude)
the_shard=WGS84Point((-0.086500, 51.504501, 310))
print(the_shard.longitude, the_shard.latitude, the_shard.height)For more information, see the Python reference.
Distance
When using the point.distance function in Cypher, the distance calculated between two points is returned as a float.
WITH point({x: 1, y:1}) AS one,
point({x: 10, y: 10}) AS two
RETURN point.distance(one, two) // 12.727922061357855For more information on Spatial types, see the Cypher Manual.
Check Your Understanding
1. Accessing Node Properties
Which of the following options are valid methods for accessing the name property on the node object node?
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✓
node["name"] -
❏
node["properties"]["name"] -
❏
node.properties.name -
✓
node.get("name") -
❏
property(node, "name")
Hint
You can get a property of a node using two of the methods above.
Solution
The valid options to get a property from a node or relationship are using square brackets (node["name"]) or using the .get() method (node.get("name")).
2. Relationship Types
What method would you use to access the type of the relationship acted_in?
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❏
acted_in["type"] -
❏
acted_in.labels -
✓
acted_in.type -
❏
neo4j.getType(acted_in)
Hint
You are looking for the type of the relationship.
Solution
The answer is acted_in.type.
Lesson Summary
In this lesson you have learned how to handle some of the more complex objects returned by a Cypher statement.
As we progress through this module, you will use the knowledge gained so far to read data from, and write data back to the database. In the next Challenge, you will modify the repository to read from the database.