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function get_lims_sampletestresults_with_references_testparameters_lims_testparameters

Maturity: 42

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

File:
/tf/active/vicechatdev/neo4j_schema/neo4j_python_snippets.py
Lines:
1321 - 1328
Complexity:
simple

Purpose

This function is designed to traverse a Laboratory Information Management System (LIMS) graph database to find test parameters associated with a specific sample test result. It's useful for retrieving configuration or metadata about tests that were performed on a sample, enabling analysis of test specifications, parameters, and settings used during sample testing.

Source Code

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

Parameters

Name Type Default Kind
source_id - - positional_or_keyword
limit - 100 positional_or_keyword

Parameter Details

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

limit: Maximum number of LIMS_Testparameters nodes to return. Defaults to 100. This parameter controls query performance and prevents returning excessively large result sets. Must be a positive integer.

Return Value

Returns the result of the run_query function, which typically contains a list or collection of LIMS_Testparameters nodes that match the query criteria. The exact return type depends on the implementation of run_query, but it likely returns Neo4j query results containing node properties and data for each matching LIMS_Testparameters node. If no matches are found, it returns an empty result set.

Dependencies

  • neo4j

Required Imports

from neo4j import GraphDatabase

Usage Example

# Assuming run_query is defined and Neo4j connection is established
# Example run_query implementation:
from neo4j import GraphDatabase

driver = GraphDatabase.driver('bolt://localhost:7687', auth=('neo4j', 'password'))

def run_query(query, params):
    with driver.session() as session:
        result = session.run(query, params)
        return [record['target'] for record in result]

# Use the function to get test parameters for a specific sample test result
sample_test_id = 'STR_12345'
test_parameters = get_lims_sampletestresults_with_references_testparameters_lims_testparameters(sample_test_id, limit=50)

# Process the results
for param in test_parameters:
    print(f"Test Parameter: {param}")

# Get all test parameters (up to 100) for another sample
all_params = get_lims_sampletestresults_with_references_testparameters_lims_testparameters('STR_67890')

Best Practices

  • Ensure the source_id exists in the database before calling this function to avoid empty results
  • Adjust the limit parameter based on expected result size to optimize query performance
  • Handle the case where no test parameters are found (empty result set)
  • Consider implementing error handling for database connection issues
  • The run_query function should properly manage Neo4j sessions and transactions
  • Close the Neo4j driver connection when the application terminates
  • Validate that source_id is properly sanitized if it comes from user input (though parameterized queries provide protection against injection)
  • Consider adding pagination if working with large datasets instead of just using a limit

Tags

neo4j graph-database lims laboratory test-parameters database-query cypher relationship-traversal sample-testing data-retrieval

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