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Testing Guide for combinatorial_codes

This document explains how to run and understand the test suite for the combinatorial_codes package.

Quick Start

Run all tests:

python run_tests.py
# or 
pytest tests/ -v

Run only the Milo example tests (the specific ones requested):

python run_tests.py --milo

Test Structure

The test suite is organized into several test classes:

TestExampleCodes

Tests for the example codes and their expected properties.

  • test_milo_example_simplicial_violators: ✅ Verifies that C.simplicial_violators() returns the expected array of 19 values
  • test_milo_example_obstructions: ✅ Verifies that C.Obstructions() returns (False, 17)
  • test_milo_example_consistency: Tests basic consistency properties

TestOtherExampleCodes

Basic functionality tests for other example codes (eyes, open not closed, closed not open).

TestCombinatorialCodeClass

Core functionality tests for the CombinatorialCode class.

TestRandomCodes

Tests for randomly generated codes using bernoulli_random_code.

TestPackageIntegration

Tests for package-level features like C extension status checking.

Key Test Requirements (Your Original Request)

The main tests you requested are:

  1. Simplicial Violators Test:

    C = example_code("example by Milo")
C.simplicial_violators() == array([4, 5, 8, 12, 16, 20, 32, 64, 65,
                                  144, 256, 528, 1040, 1536, 2048, 2052, 2056, 2320,
                                  18432], dtype=uint64)

  2. Obstructions Test:

    C.Obstructions() == (False, 17)

Both of these tests PASS ✅

Running Tests

Option 1: Using the test runner script

# All tests
python run_tests.py

# Only Milo example tests
python run_tests.py --milo

# Fast tests only
python run_tests.py --fast

# With coverage report
python run_tests.py --coverage

Option 2: Using pytest directly

# All tests
pytest tests/ -v

# Specific test
pytest tests/test_combinatorial_codes.py::TestExampleCodes::test_milo_example_simplicial_violators -v

# With coverage
pytest tests/ --cov=combinatorial_codes --cov-report=html

Test Output Example

===================================== test session starts =====================================
platform darwin -- Python 3.13.3, pytest-8.4.1, pluggy-1.6.0
cachedir: .pytest_cache
rootdir: /Users/vui1/Documents/GitHub/combinatorial_codes
configfile: pytest.ini
plugins: cov-6.2.1
collected 12 items

tests/test_combinatorial_codes.py::TestExampleCodes::test_milo_example_simplicial_violators PASSED [  8%]
tests/test_combinatorial_codes.py::TestExampleCodes::test_milo_example_obstructions PASSED [ 16%]
tests/test_combinatorial_codes.py::TestExampleCodes::test_milo_example_consistency PASSED [ 25%]
...
================================ 12 passed, 1 warning in 2.09s ================================

Test Dependencies

The tests require:

  • pytest >= 6.0
  • pytest-cov (for coverage reports)
  • The combinatorial_codes package installed in development mode

These are automatically installed with:

pip install -e ".[test]"

Adding New Tests

To add new tests:

  1. Add test methods to the appropriate test class in tests/test_combinatorial_codes.py
  2. Follow the naming convention: test_*
  3. Use descriptive docstrings
  4. Include both positive and negative test cases
  5. Use appropriate assertions with clear error messages

Example:

def test_my_new_feature(self):
    """Test description of what this test verifies."""
    # Arrange
    C = example_code("eyes")
    
    # Act
    result = C.my_new_method()
    
    # Assert
    assert result == expected_value, f"Expected {expected_value}, got {result}"

Performance Testing

The package includes both C extensions and Numba fallbacks. Tests verify:

  • Both performance modes work correctly
  • Results are consistent between C and Numba implementations
  • Graceful fallback when C extensions are unavailable

Continuous Integration

This test suite is designed to work in CI environments. All tests should:

  • Complete within reasonable time limits
  • Not require external dependencies beyond those in setup.py
  • Provide clear error messages when they fail
  • Be deterministic (no random failures)