Test Structure¶

This directory contains all tests for dummyxarray, organized by test type and module.

Directory Structure¶

tests/
├── conftest.py                    # Shared fixtures and pytest configuration
├── unit/                          # Unit tests (per module)
│   ├── test_core.py              # DummyArray, DummyDataset core functionality
│   ├── test_history.py           # HistoryMixin tests
│   ├── test_provenance.py        # ProvenanceMixin tests
│   ├── test_cf_compliance.py     # CFComplianceMixin tests
│   ├── test_io.py                # IOMixin tests
│   ├── test_validation.py        # ValidationMixin tests
│   ├── test_data_generation.py   # DataGenerationMixin tests
│   ├── test_mfdataset.py         # Multi-file dataset support tests
│   └── test_ncdump_parser.py     # NetCDF metadata parser tests
├── integration/                   # Integration tests (workflows)
│   └── test_workflows.py         # End-to-end workflow tests
└── fixtures/                      # Test data and fixtures
    └── __init__.py

Test Categories¶

Unit Tests (`tests/unit/`)¶

Test individual modules and mixins in isolation:

test_core.py: Core classes (DummyArray, DummyDataset)
Initialization, repr, basic operations
Dimension management
Coordinate and variable management
Renaming operations
test_history.py: History tracking functionality
Operation recording
History export/replay
History visualization (text, dot, mermaid)
Reset history
test_provenance.py: Provenance tracking
Change tracking (added/removed/modified)
Provenance visualization
Rename tracking
test_cf_compliance.py: CF convention support
Axis inference (X/Y/Z/T)
Axis attribute setting
CF validation
Standard name handling
test_io.py: I/O operations
Dictionary/JSON/YAML export
File save/load
xarray conversion (to/from)
Zarr export
test_validation.py: Dataset validation
Structure validation
Dimension inference
Conflict detection
test_data_generation.py: Random data generation
Coordinate data generation
Variable data generation
Metadata-based generation
test_mfdataset.py: Multi-file dataset support
Opening multiple NetCDF files
Frequency inference
Time-based grouping
File tracking and queries
test_ncdump_parser.py: NetCDF metadata parser
Parsing ncdump output
Dimension extraction
Variable and attribute parsing

Integration Tests (`tests/integration/`)¶

Test complete workflows and interactions between modules:

test_workflows.py: End-to-end workflows
CF compliance workflow
History and provenance workflow
Data generation and export workflow
Rename workflow
Validation and fix workflow
Import/modify/export workflow

Running Tests¶

Run all tests¶

pixi run test

Run specific test file¶

pixi run test tests/unit/test_core.py

Run specific test class¶

pixi run test tests/unit/test_core.py::TestDummyArray

Run specific test¶

pixi run test tests/unit/test_core.py::TestDummyArray::test_init_empty

Run only unit tests¶

pixi run test tests/unit/

Run only integration tests¶

pixi run test tests/integration/

Run with markers¶

# Run only unit tests (if marked)
pytest -m unit

# Run only integration tests (if marked)
pytest -m integration

# Skip slow tests
pytest -m "not slow"

Run with coverage¶

pytest --cov=dummyxarray --cov-report=html

Shared Fixtures (`conftest.py`)¶

Common fixtures available to all tests:

Dataset Fixtures¶

empty_dataset: Empty DummyDataset
simple_dataset: Dataset with dimensions only
dataset_with_coords: Dataset with coordinates
dataset_with_data: Dataset with data arrays
cf_compliant_dataset: CF-compliant dataset

Array Fixtures¶

simple_array: Simple DummyArray
array_with_data: DummyArray with data

Parametrized Fixtures¶

with_history: Test with/without history tracking
viz_format: Test all visualization formats

Temporary File Fixtures¶

temp_yaml_file: Temporary YAML file path
temp_zarr_store: Temporary Zarr store path

Mock Data Fixtures¶

sample_history: Sample operation history
sample_provenance: Sample provenance data

Writing New Tests¶

Unit Test Template¶

"""Tests for [module] functionality."""

import pytest
from dummyxarray import DummyDataset


class TestFeature:
    """Test [feature] functionality."""

    def test_basic_case(self, simple_dataset):
        """Test basic [feature] usage."""
        # Arrange
        ds = simple_dataset

        # Act
        result = ds.some_method()

        # Assert
        assert result is not None

Integration Test Template¶

"""Integration tests for [workflow]."""

import pytest
from dummyxarray import DummyDataset


class TestWorkflow:
    """Test [workflow] end-to-end."""

    def test_complete_workflow(self, tmp_path):
        """Test complete [workflow] from start to finish."""
        # Create dataset
        ds = DummyDataset()

        # Perform workflow steps
        ds.add_dim("time", 10)
        # ... more steps

        # Verify final state
        assert ds.dims["time"] == 10

Best Practices¶

Use fixtures: Leverage shared fixtures from conftest.py
Test one thing: Each test should verify one specific behavior
Descriptive names: Test names should describe what they test
Arrange-Act-Assert: Follow AAA pattern for clarity
Parametrize: Use @pytest.mark.parametrize for similar tests
Mock external dependencies: Don't rely on external services
Clean up: Use fixtures with cleanup or tmp_path for files

Test Coverage¶

Current coverage: 188 tests across all modules

Unit tests: ~160 tests
Integration tests: ~28 tests

Target: >90% code coverage