UNIT-TEST.md

Development Guide

Testing

pytest is used to run tests to verify data correctness. All tests in the suite must pass in a branch before a pull request can be merged. Along with a core set of tests to catch basic regressions, pull requests for new features or fixes are expected to have accompanying unit tests that demonstrate the correctness of the change.

Writing tests

In aiming to keep tests readable and succinct, there are some preset patterns and helpers available to those writing tests.

Available files

Lists of expected file paths are created in test/__init__.py. Tests can use these expected file paths as test targets. File path lists can be imported like so:

from test import __nodes_files__
from test import __lowfat_files__

Parameterized Tests

pytest offers decorators that allow a single test to be parameterized across a set of files. This allows us to write a single test that can be applied to all of the files in a dataset. When a failure occurs, pytest prints of the condition failure and the parameter that the test failed on.

Example: this test will run for each file defined in the __nodes_files__ list:

@pytest.mark.parametrize("nodes_file", __nodes_files__)
def test_file_is_valid_xml(nodes_file):
    assert etree.parse(nodes_file)

Additional Helpers

run_xpath_for_file

Takes an xpath expression and a file path. Returns a list of elements matched by the expression.

Running the test suite locally

Prerequisites:

• Python 3.x
• Poetry (dependency management for python)

In the project root, install dependencies:

poetry install

Run all tests:

poetry run pytest

Run a specific test file:

poetry run pytest test/test_lowfat.py

Run the tests with console output:

poetry run pytest -rP