- Test Discovery: Pytest automatically discovers and runs test functions in your Python code. It can find and execute tests in files named with specific patterns, such as
test_*.pyor*_test.py. - Fixture Support: Fixtures are a way to set up and tear down resources needed for testing. Pytest provides a fixture system to simplify the setup and cleanup of these resources. Fixtures can be defined at the module, class, or function level.
- Parametrized Testing: You can easily parameterize your test functions using decorators like
@pytest.mark.parametrize. This allows you to run the same test with different input values and expected outcomes. - Assertions: Pytest provides a rich set of built-in assertions for checking conditions in your test cases. If an assertion fails, Pytest will provide detailed information about the failure.
- Plugins: Pytest has a vibrant ecosystem of plugins that extend its functionality. You can use plugins to add features like code coverage analysis, parallel test execution, and integration with other testing and reporting tools.
- Test Marking: Pytest allows you to mark tests with custom labels or categories using
@pytest.mark. This makes it easy to run specific subsets of tests, such as integration tests or slow tests. - Test Fixtures and Dependency Injection: Pytest fixtures can be used for dependency injection. You can define fixtures that provide resources to your test functions, such as databases, web servers, or mock objects.
- Command-Line Interface: Pytest comes with a powerful command-line interface (CLI) that lets you customize test runs, specify test directories, and control various testing options.
To use Pytest, you typically need to install it using a package manager like pip:
bashCopy codepip install pytest
Once installed, you can write your test functions and execute them using the pytest command. For example, if you have a file named test_my_module.py containing test functions, you can run the tests like this:
bashCopy codepytest test_my_module.py
Pytest will discover and execute the tests, providing you with detailed output about the test results.
Keep in mind that Pytest is a versatile and widely adopted testing framework, and it can be integrated into various development workflows and CI/CD pipelines to ensure the quality and reliability of your Python code.
