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Queries a Neo4j graph database to retrieve LIMS_Tests nodes that are connected to a specific LIMS_Testparameters node through a REFERENCES_TESTS relationship.

Purpose

This function is designed to traverse a graph database structure representing a Laboratory Information Management System (LIMS). It finds all test definitions (LIMS_Tests) that are referenced by a specific test parameter configuration (LIMS_Testparameters). This is useful for understanding which tests utilize particular test parameters, enabling analysis of test configurations and their relationships in a laboratory data management context.

Source Code

def get_lims_testparameters_with_references_tests_lims_tests(source_id, limit=100):
    """Get LIMS_Tests nodes connected to a LIMS_Testparameters via REFERENCES_TESTS"""
    query = """
    MATCH (source:LIMS_Testparameters {id: $source_id})-[r:REFERENCES_TESTS]->(target:LIMS_Tests)
    RETURN target
    LIMIT $limit
    """
    return run_query(query, {"source_id": source_id, "limit": limit})

Parameters

Parameter Details

source_id: The unique identifier (id property) of the LIMS_Testparameters node from which to start the traversal. This should be a string or value that matches the 'id' property of a LIMS_Testparameters node in the Neo4j database.

limit: Maximum number of LIMS_Tests nodes to return. Defaults to 100. This parameter controls query performance and result set size. Should be a positive integer.

Return Value

Returns the result of the run_query function, which typically contains a list or collection of LIMS_Tests nodes that match the query criteria. The exact return type depends on the implementation of run_query, but it likely returns a list of dictionaries or Neo4j Record objects containing the properties of the target LIMS_Tests nodes. Returns an empty collection if no matching relationships are found.

Dependencies

• neo4j

Required Imports

from neo4j import GraphDatabase

Usage Example

# Assuming run_query is defined and Neo4j connection is configured
# Example run_query implementation:
# 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['target'] for record in result]

# Get LIMS_Tests referenced by a specific test parameter
test_param_id = 'TP-12345'
results = get_lims_testparameters_with_references_tests_lims_tests(test_param_id, limit=50)

# Process results
for test_node in results:
    print(f"Test ID: {test_node['id']}, Name: {test_node.get('name', 'N/A')}")

Best Practices

• Ensure the source_id parameter matches an existing LIMS_Testparameters node in the database to avoid empty results
• Adjust the limit parameter based on expected result set size and performance requirements
• Handle cases where run_query might return empty results or raise exceptions
• Consider implementing connection pooling and proper session management in the run_query function
• Use parameterized queries (as shown) to prevent Cypher injection attacks
• Close Neo4j driver connections properly after use to avoid resource leaks
• Consider adding error handling for database connection failures
• For large result sets, consider implementing pagination instead of relying solely on the limit parameter

Tags

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