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Retrieves a limited set of nodes labeled as 'dbo_Concepts' from a Neo4j graph database.

Purpose

This function queries a Neo4j database to fetch nodes with the label 'dbo_Concepts', which likely represent concepts from the DBpedia ontology. It's designed for exploring or retrieving concept data from a knowledge graph, with a configurable limit to control the number of results returned. The function is useful for data exploration, testing database connectivity, or retrieving a sample of concept nodes for further processing.

Source Code

def get_all_dbo_concepts(limit=100):
    """Return dbo_Concepts nodes (limited to 25)"""
    query = """
    MATCH (n:dbo_Concepts)
    RETURN n
    LIMIT $limit
    """
    return run_query(query, {"limit": limit})

Parameters

Parameter Details

limit: An integer specifying the maximum number of dbo_Concepts nodes to return. Default value is 100. Note: The docstring incorrectly states the limit is 25, but the actual default is 100. This parameter allows users to control query performance and result set size.

Return Value

Returns the result of the run_query function, which typically returns a list of Neo4j Record objects or a processed result set containing the matched dbo_Concepts nodes. The exact return type depends on the implementation of run_query, but it should contain up to 'limit' number of nodes with their properties. If no nodes are found, it likely returns an empty list or None.

Dependencies

• neo4j

Required Imports

from neo4j import GraphDatabase

Usage Example

# Assuming run_query is defined and Neo4j connection is configured
# Example 1: Get default 100 concepts
results = get_all_dbo_concepts()
for record in results:
    print(record['n'])

# Example 2: Get only 10 concepts
results = get_all_dbo_concepts(limit=10)
for record in results:
    concept_node = record['n']
    print(f"Concept: {concept_node}")

# Example 3: Get maximum 500 concepts
results = get_all_dbo_concepts(limit=500)

Best Practices

• The docstring is inconsistent with the actual default limit value (states 25 but default is 100) - this should be corrected
• Be cautious with large limit values as they may impact database performance and memory usage
• Ensure the run_query function properly handles database connections and error cases
• Consider adding error handling for cases where the database is unavailable or the query fails
• The function assumes run_query is available in scope - ensure proper import or definition
• Consider adding type hints for better code documentation (e.g., limit: int -> List[Record])
• For production use, consider adding pagination support for very large datasets instead of relying solely on LIMIT

Tags

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