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Creates a new node of type 'dbo_Flocks' in a Neo4j graph database with the specified properties and returns the created node.

Purpose

This function is designed to insert a new dbo_Flocks entity into a Neo4j graph database. It dynamically constructs a Cypher CREATE query based on the provided properties dictionary, executes the query using a helper function 'run_query', and returns the newly created node. This is useful for applications that need to programmatically add flock entities to a knowledge graph or database schema where 'dbo_Flocks' represents a specific domain object.

Source Code

def create_dbo_flocks(properties):
    """Create a new dbo_Flocks node"""
    props_list = ', '.join([f"n.{prop} = ${prop}" for prop in properties.keys()])
    query = f"""
    CREATE (n:dbo_Flocks)
    SET {props_list}
    RETURN n
    """
    result = run_query(query, properties)
    return result[0] if result else None

Parameters

Parameter Details

properties: A dictionary containing key-value pairs representing the properties to be set on the new dbo_Flocks node. Keys should be valid property names (strings) and values can be any data type supported by Neo4j (strings, numbers, booleans, lists, etc.). Example: {'name': 'Flock1', 'size': 100, 'location': 'Farm A'}

Return Value

Returns the first element from the query result (the created node object) if the query execution is successful and returns results. Returns None if the query fails or returns an empty result set. The returned node object typically contains all properties set during creation along with Neo4j internal identifiers.

Dependencies

• neo4j

Required Imports

from neo4j import GraphDatabase

Usage Example

from neo4j import GraphDatabase

# Assuming run_query is defined elsewhere
def run_query(query, params):
    driver = GraphDatabase.driver('bolt://localhost:7687', auth=('neo4j', 'password'))
    with driver.session() as session:
        result = session.run(query, params)
        return [record['n'] for record in result]
    driver.close()

# Create a new dbo_Flocks node
flock_properties = {
    'name': 'Northern Flock',
    'size': 150,
    'location': 'Farm B',
    'established_date': '2024-01-15'
}

new_flock = create_dbo_flocks(flock_properties)
if new_flock:
    print(f'Successfully created flock: {new_flock}')
else:
    print('Failed to create flock')

Best Practices

• Ensure the 'run_query' function is properly implemented with error handling and connection management
• Validate the properties dictionary before passing it to avoid injection vulnerabilities or invalid data types
• Consider adding input validation to ensure required properties are present
• Be aware of potential Cypher injection risks when dynamically constructing queries - the parameterized approach used here is good practice
• Handle the None return value appropriately in calling code to detect creation failures
• Consider wrapping this function in a try-except block to handle database connection errors
• Ensure property names in the dictionary match the expected schema for dbo_Flocks nodes
• Consider adding transaction management for consistency in multi-operation scenarios

Tags

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