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Retrieves LIMS_Tests4Pathogens nodes from a Neo4j graph database with a configurable limit on the number of results returned.

Purpose

This function queries a Neo4j database to fetch all nodes labeled as LIMS_Tests4Pathogens, which likely represent laboratory information management system (LIMS) test data related to pathogen testing. It's designed for retrieving pathogen test records from a graph database, with a default limit to prevent overwhelming data retrieval. The function uses Cypher query language to match and return nodes.

Source Code

def get_all_lims_tests4pathogens(limit=100):
    """Return LIMS_Tests4Pathogens nodes (limited to 25)"""
    query = """
    MATCH (n:LIMS_Tests4Pathogens)
    RETURN n
    LIMIT $limit
    """
    return run_query(query, {"limit": limit})

Parameters

Parameter Details

limit: Integer value that controls the maximum number of LIMS_Tests4Pathogens nodes to return from the database. Default is 100, though the docstring incorrectly states 25. Must be a positive integer. Higher values will return more results but may impact performance.

Return Value

Returns the result of run_query() function execution, which typically contains a list or collection of Neo4j node objects representing LIMS_Tests4Pathogens records. The exact return type depends on the implementation of run_query(), but it likely returns a list of dictionaries or Neo4j Record objects containing node properties. Returns up to 'limit' number of nodes.

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 records
results = get_all_lims_tests4pathogens()
for record in results:
    print(record['n'])

# Example 2: Get only 10 records
results = get_all_lims_tests4pathogens(limit=10)

# Example 3: Get maximum 500 records
results = get_all_lims_tests4pathogens(limit=500)

Best Practices

• Note the discrepancy: docstring says 'limited to 25' but default parameter is 100 - update documentation for consistency
• Consider adding error handling for database connection failures
• Be mindful of the limit parameter when dealing with large datasets to avoid memory issues
• Ensure the run_query() function properly handles parameterized queries to prevent Cypher injection
• Consider adding pagination support for very large result sets instead of just a limit
• Validate that the limit parameter is a positive integer before executing the query
• Consider adding filters or search parameters to make the function more flexible for specific use cases

Tags

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