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A test function that validates the extraction of analysis descriptions from combined request strings containing 'Analysis:' and 'Data:' sections.

Purpose

This function tests a string parsing algorithm that extracts analysis descriptions from formatted text requests. It validates three scenarios: standard format with Data followed by Analysis, reversed order with Analysis followed by Data, and edge case with no Analysis section. The function demonstrates how to parse structured text requests and extract specific sections based on delimiter keywords.

Source Code

def test_analysis_extraction():
    """Test extracting analysis description from combined request"""
    print("=== Testing Analysis Description Extraction ===")
    
    # Test case 1: Standard format
    combined_request1 = """Data: Recent laboratory test results from the last 3 months with customer information

Analysis: Descriptive statistics on the analysis type distribution in time and relative numbers."""
    
    analysis_description = ""
    if "Analysis:" in combined_request1:
        analysis_part = combined_request1.split("Analysis:", 1)[1].strip()
        if "Data:" in analysis_part:
            analysis_part = analysis_part.split("Data:", 1)[0].strip()
        analysis_description = analysis_part
    
    print(f"✅ Test 1 - Standard format:")
    print(f"   Input: {repr(combined_request1[:50])}...")
    print(f"   Extracted: {repr(analysis_description)}")
    
    # Test case 2: Different order
    combined_request2 = """Analysis: Analyze testing patterns and trends over time
Data: Laboratory results with dates and test types"""
    
    analysis_description2 = ""
    if "Analysis:" in combined_request2:
        analysis_part = combined_request2.split("Analysis:", 1)[1].strip()
        if "Data:" in analysis_part:
            analysis_part = analysis_part.split("Data:", 1)[0].strip()
        analysis_description2 = analysis_part
    
    print(f"✅ Test 2 - Different order:")
    print(f"   Input: {repr(combined_request2[:50])}...")
    print(f"   Extracted: {repr(analysis_description2)}")
    
    # Test case 3: No analysis section
    combined_request3 = "Data: Just some data request without analysis"
    
    analysis_description3 = ""
    if "Analysis:" in combined_request3:
        analysis_part = combined_request3.split("Analysis:", 1)[1].strip()
        if "Data:" in analysis_part:
            analysis_part = analysis_part.split("Data:", 1)[0].strip()
        analysis_description3 = analysis_part
    
    print(f"✅ Test 3 - No analysis section:")
    print(f"   Input: {repr(combined_request3)}")
    print(f"   Extracted: {repr(analysis_description3)}")
    print(f"   Should be empty: {analysis_description3 == ''}")

Return Value

This function does not return any value (implicitly returns None). It prints test results to stdout showing the extraction process and validation for three different test cases.

Usage Example

# Simply call the function to run all test cases
test_analysis_extraction()

# Expected output:
# === Testing Analysis Description Extraction ===
# ✅ Test 1 - Standard format:
#    Input: 'Data: Recent laboratory test results from the l'...
#    Extracted: 'Descriptive statistics on the analysis type distribution in time and relative numbers.'
# ✅ Test 2 - Different order:
#    Input: 'Analysis: Analyze testing patterns and trends ov'...
#    Extracted: 'Analyze testing patterns and trends over time'
# ✅ Test 3 - No analysis section:
#    Input: 'Data: Just some data request without analysis'
#    Extracted: ''
#    Should be empty: True

Best Practices

• This is a test function demonstrating a parsing pattern; in production code, consider extracting the parsing logic into a separate reusable function
• The parsing logic uses simple string splitting which assumes well-formed input; consider adding error handling for malformed requests
• For more complex parsing needs, consider using regular expressions or a proper parser library
• The test function prints results but doesn't use assertions; consider using a proper testing framework like pytest or unittest for production tests
• The parsing logic is duplicated across test cases; refactor into a helper function to follow DRY principles

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