def test_load_graph(relationship_nodes):
# Arrange
expected = Graph([
Node("TypeA", given_id="1"),
Node("TypeB", given_id="2")
], [Relationship(relationship_nodes["1"], "Rel", relationship_nodes["2"])])
# Act
result = import_graph_json({
"nodes": [{
"node_type": "TypeA",
"properties": {
"node_id": "1"
}
}, {
"node_type": "TypeB",
"properties": {
"node_id": "2"
}
}],
"relationships": [{
"node_a": "1",
"relationship_type": "Rel",
"node_b": "2"
}]
})
# Assert
assert result == expected
def import_node_json(node_raw: Dict) -> Node:
"""
Loads a node from raw json
:param node_raw: the json to load from
:return: the node object
"""
return Node(node_raw["node_types"], node_raw["properties"])
def test_multi_label_node():
# Arrange
expected = "(n:TestTypeA:TestTypeB {prop1: 'value1', node_id: '1'})"
test_node = Node(["TestTypeA", "TestTypeB"], {"prop1": "value1"}, "1")
# Act
result = node_query(test_node)
# Assert
assert result == expected
def test_node_query_sanity():
# Arrange
expected = "(n:TestType {prop1: 'value1', node_id: '1'})"
test_node = Node("TestType", {"prop1": "value1"}, "1")
# Act
result = node_query(test_node)
# Assert
assert result == expected
def import_node_neo4j(result: neo4j.Record) -> Node:
"""
Takes a neo4j result and converts it to a use able node object
:param result: the neo4j result
:return: the node created from the result
"""
return Node(list(result[0].labels),
{key: value
for key, value in result[0].items()})
def test_load_node():
# Arrange
expected = Node("TestType", given_id="1")
# Act
result = import_node_json({
"node_type": "TestType",
"properties": {
"node_id": "1"
}
})
# Assert
assert result == expected
def create_graph_map(names: List[AnyStr], connection_chance: int) -> Database:
"""
Creates a randomly generated graph in neo4j and saves it to a json representation for use in testing the differ
loads names for generating from a file.
:param connection_chance: the chance for a node to connect to another higher is a bigger change
:param names: the path to save the graph to.
"""
names = names
relationships = []
names_nodes = [
Node(GlobalSettings.TEST_GRAPH_TYPE, properties={"name": name})
for name in names
]
for current_node in names_nodes:
for i in range(random.randint(0, connection_chance)):
selected_node = random.choice(names_nodes)
if selected_node is not current_node:
new_relationship = Relationship(
current_node, GlobalSettings.TEST_GRAPH_RELATIONSHIP,
selected_node)
relationships.append(new_relationship)
return Database(Graph(names_nodes, relationships), "TestDatabase")
def test_node() -> Node:
return Node("TestType", {"prop1": "value1"}, "1")
def test_relationship() -> Relationship:
return Relationship(Node("TestTypeA", {"prop1": "value1"}, "1"),
"Knows",
Node("TestTypeB", {"prop2": "value2"}, "2"), {"rel_prop": "value1"})
def relationship_nodes():
return {"1": Node("TypeA", given_id="1"), "2": Node("TypeB", given_id="2")}
def test_node() -> Node:
return Node("TestType", given_id="1")
def test_relationship() -> Relationship:
return Relationship(Node("TypeA", given_id="1"), "Rel", Node("TypeB", given_id="2"))