Testing¶

Overview¶

Testing strategies and tools for Opifex development.

Running Tests¶

Basic Test Suite¶

# Run all tests
source activate.sh
uv run pytest

# Run specific module tests
uv run pytest tests/neural/
uv run pytest tests/core/

# Run with coverage
uv run pytest --cov=src/opifex --cov-report=html

# Full test reporting with JSON output and detailed coverage
uv run pytest -vv --json-report --json-report-file=temp/test-results.json --json-report-indent=2 --json-report-verbosity=2 --cov=src/opifex --cov-report=json:temp/coverage.json --cov-report=term-missing

Full Test Reporting¶

The full test command above generates detailed reports for CI/CD integration and analysis:

Output Files:

temp/test-results.json: Detailed test results in JSON format with full verbosity
temp/coverage.json: Coverage data in JSON format for programmatic analysis
Terminal output: Coverage report with missing lines highlighted

Note: The temp/ directory is automatically created if it doesn't exist. Output files are suitable for CI/CD integration and automated analysis tools.

Use Cases:

CI/CD Integration: Machine-readable test and coverage data
Quality Analysis: Detailed test metrics and coverage tracking
Debugging: Verbose output for investigating test failures
Reporting: Structured data for dashboard integration

Command Breakdown:

-vv: Very verbose output for detailed test information
--json-report: Enable JSON test result reporting
--json-report-file=temp/test-results.json: Output location for test results
--json-report-indent=2: Pretty-print JSON with 2-space indentation
--json-report-verbosity=2: Maximum verbosity in JSON output
--cov=src/opifex: Enable coverage for the opifex package
--cov-report=json:temp/coverage.json: Output coverage data as JSON
--cov-report=term-missing: Show missing coverage in terminal

GPU Tests¶

# Run GPU-specific tests
uv run pytest tests/ -k "gpu"

# Verify GPU functionality
python scripts/verify_opifex_gpu.py

Test Structure¶

Unit Tests¶

Individual component testing
Isolated functionality verification
Fast execution

Integration Tests¶

Component interaction testing
End-to-end workflows
Realistic scenarios

Performance Tests¶

Benchmarking critical paths
Memory usage validation
Scalability testing

Writing Tests¶

Test Guidelines¶

import pytest
import jax.numpy as jnp
from flax import nnx
from opifex.neural.base import StandardMLP

def test_mlp_creation():
    """Test MLP model creation."""
    model = StandardMLP(layer_sizes=[2, 10, 1], rngs=nnx.Rngs(0))
    assert model is not None

def test_mlp_forward_pass():
    """Test MLP forward computation."""
    model = StandardMLP(layer_sizes=[2, 10, 1], rngs=nnx.Rngs(0))
    x = jnp.array([[0.5, 0.5]])
    output = model(x)
    assert output.shape == (1, 1)

Fixtures¶

@pytest.fixture
def sample_pde_problem():
    """Fixture for test PDE problems."""
    return PDEProblem(
        equation=heat_equation,
        domain=unit_square,
        boundary_conditions=dirichlet_bcs
    )

Continuous Integration¶

Tests run automatically on:

Pull requests
Main branch commits

Pre-commit Hooks¶

# Setup pre-commit
uv run pre-commit install

# Run manually
uv run pre-commit run --all-files