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function create_lims_importerrors

Maturity: 48

Creates a new LIMS_ImportErrors node in a Neo4j graph database with the specified properties and returns the created node.

File:
/tf/active/vicechatdev/neo4j_schema/neo4j_python_snippets.py
Lines:
49 - 58
Complexity:
simple

Purpose

This function is designed to log import errors in a Laboratory Information Management System (LIMS) by creating error nodes in a Neo4j graph database. It dynamically constructs a Cypher query to create a node with custom properties, making it useful for tracking and auditing data import failures or validation errors in LIMS workflows.

Source Code

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

Parameters

Name Type Default Kind
properties - - positional_or_keyword

Parameter Details

properties: A dictionary containing key-value pairs representing the properties to be set on the LIMS_ImportErrors node. Keys should be valid Neo4j property names (strings), and values can be any Neo4j-compatible data types (strings, numbers, booleans, dates, etc.). Example: {'error_message': 'Invalid sample ID', 'timestamp': '2024-01-01T10:00:00', 'source_file': 'samples.csv'}

Return Value

Returns the first element from the query result (the created LIMS_ImportErrors node) if the query execution is successful and returns results. Returns None if the query fails or returns an empty result set. The returned node is typically a dictionary-like object containing all the properties set on the created node.

Dependencies

  • neo4j

Required Imports

from neo4j import GraphDatabase

Usage Example

# Assuming run_query function is defined and Neo4j connection is configured

# Example 1: Create an import error node with basic properties
error_properties = {
    'error_message': 'Duplicate sample ID found',
    'error_code': 'ERR_001',
    'timestamp': '2024-01-15T14:30:00',
    'source_file': 'batch_import_2024.csv',
    'line_number': 42,
    'severity': 'high'
}

result = create_lims_importerrors(error_properties)
if result:
    print(f"Error node created successfully: {result}")
else:
    print("Failed to create error node")

# Example 2: Create error node with minimal properties
minimal_error = {
    'error_message': 'Connection timeout',
    'timestamp': '2024-01-15T15:00:00'
}

error_node = create_lims_importerrors(minimal_error)

Best Practices

  • Always validate the properties dictionary before passing it to ensure it contains valid Neo4j property types
  • Include timestamp information in properties for proper error tracking and chronological ordering
  • Check the return value for None to handle cases where node creation fails
  • Sanitize user input in properties to prevent Cypher injection attacks
  • Consider adding error handling around the function call to catch potential Neo4j connection or query execution errors
  • Use consistent property naming conventions across all LIMS_ImportErrors nodes for easier querying
  • Avoid passing empty dictionaries as properties parameter, as this would create a node with no properties
  • Consider implementing property validation or a schema to ensure required fields are present
  • Be aware that the function uses parameterized queries which helps prevent injection attacks, but property keys are directly interpolated into the query string

Tags

neo4j graph-database lims error-logging database-insert cypher-query node-creation error-tracking data-import audit-trail

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