Kiểm thử tạo QR Code: Test đơn vị và tích hợp

Testing QR Code Generation: Unit and Integration Tests

Robust testing ensures your QR code generation produces valid, scannable codes under all input conditions.

Unit Tests

Round-trip testing: The most fundamental test — generate a QR code and decode it, verifying the output matches the input:

import segno
import io
from pyzbar.pyzbar import decode
from PIL import Image

def test_round_trip():
    data = "https://example.com/test"
    qr = segno.make(data, error="m")
    buffer = io.BytesIO()
    qr.save(buffer, kind="png", scale=10)
    buffer.seek(0)
    image = Image.open(buffer)
    results = decode(image)
    assert len(results) == 1
    assert results[0].data.decode("utf-8") == data

Encoding mode verification: Verify the library selects the expected encoding mode:

def test_numeric_mode():
    qr = segno.make("1234567890")
    assert qr.mode == "numeric"

def test_alphanumeric_mode():
    qr = segno.make("HTTPS://EXAMPLE.COM")
    # Verify version is lower than byte mode would require

Edge Case Tests

Test boundary conditions:

• Empty string: Should the library raise an error or generate a valid code?
• Maximum capacity: Data that exactly fills a module count." data-category="QR Code Structure">version's capacity
• Special characters: Unicode, emoji, control characters
• Very long URLs: Data requiring Version 30+
• All encoding modes: Numeric, alphanumeric, byte, kanji

Integration Tests

Multi-scanner validation: Decode generated QR codes with multiple reader libraries:

def test_multi_scanner(qr_image):
    # Test with pyzbar
    pyzbar_result = pyzbar_decode(qr_image)
    # Test with OpenCV
    opencv_result = opencv_decode(qr_image)
    # Both should produce identical results
    assert pyzbar_result == opencv_result

Print simulation: Test with simulated print degradation (add noise, reduce contrast, blur edges).

Visual Regression Testing

For custom-styled QR codes, compare generated images against known-good reference images:

• Pixel-difference comparison with tolerance threshold
• Perceptual hash comparison for layout changes
• Automated scanning to verify functional equivalence

Key Takeaways

• Round-trip testing (generate then decode) is the essential baseline test
• Test all encoding modes, edge cases, and capacity boundaries
• Multi-scanner validation ensures broad compatibility
• Visual regression catches unintended design changes
• Simulate print degradation for production-readiness testing