Pytest

Overview

Pytest is a powerful testing framework for Python that makes it easy to write simple unit tests as well as complex functional testing. This skill provides guidance on pytest best practices, test creation, fixtures, and test execution patterns.

Quick Start

Basic Test Structure

python

# content of test_sample.py
def inc(x):
    return x + 1

def test_answer():
    assert inc(3) == 4  # This should pass

Key Conventions

•Test functions should start with test_
•Test files should start with test_ or end with _test.py
•Use plain assert statements for testing

Core Capabilities

1. Basic Test Creation

Create simple tests with assert statements:

python

def test_addition():
    assert 2 + 2 == 4

def test_string_contains():
    text = "Hello, pytest!"
    assert "pytest" in text

2. Test Fixtures

Fixtures provide a baseline for tests and can set up preconditions and clean up after tests:

python

import pytest

@pytest.fixture
def sample_data():
    return [1, 2, 3, 4, 5]

def test_list_length(sample_data):
    assert len(sample_data) == 5

3. Parameterized Tests

Run the same test with different inputs:

python

import pytest

@pytest.mark.parametrize("input,expected", [
    (2, 4),
    (3, 6),
    (4, 8),
])
def test_double(input, expected):
    assert input * 2 == expected

4. Exception Testing

Test that specific exceptions are raised:

python

def test_raises():
    with pytest.raises(ValueError):
        int("not_a_number")

Test Execution

Basic Commands

bash

pytest                    # Run all tests in current directory
pytest test_file.py       # Run specific test file
pytest test_file.py::test_function  # Run specific test function
pytest -v                 # Verbose output
pytest -x                 # Stop after first failure
pytest --tb=short         # Short traceback format

Running Specific Tests

bash

pytest -k "test_name"     # Run tests matching pattern
pytest -m "marker_name"   # Run tests with specific marker
pytest --lf               # Run only the tests that failed in the last run
pytest --ff               # Run failed tests first

Advanced Features

Markers

Use markers to categorize and control test execution:

python

import pytest

@pytest.mark.skip(reason="Not implemented yet")
def test_incomplete():
    pass

@pytest.mark.skipif(sys.version_info < (3, 8), reason="Requires Python 3.8+")
def test_python38_feature():
    pass

@pytest.mark.slow
def test_slow_function():
    pass

Fixtures with Different Scopes

•function: Run once per test function (default)
•class: Run once per test class
•module: Run once per module
•session: Run once per test session

python

@pytest.fixture(scope="session")
def database_connection():
    # Setup database connection once for all tests
    db = connect_to_db()
    yield db
    # Cleanup after all tests are done
    db.close()

Setup and Teardown with Fixtures

python

@pytest.fixture
def temporary_file(tmp_path):
    file_path = tmp_path / "temp.txt"
    file_path.write_text("test content")
    yield file_path  # This is where the test runs
    # Cleanup happens after the yield
    file_path.unlink()

Best Practices

•Use descriptive test names that explain what is being tested
•Follow the Arrange-Act-Assert pattern: Set up data, perform action, assert result
•Keep tests focused - one assertion per test when possible
•Use fixtures to avoid code duplication across tests
•Use parametrized tests for testing the same logic with different inputs
•Use markers to categorize tests and control execution

Configuration

Create a pytest.ini, pyproject.toml, or setup.cfg file to configure pytest:

ini

# pytest.ini
[tool:pytest]
testpaths = tests
addopts = -v --tb=short
markers =
    slow: marks tests as slow
    integration: marks tests as integration tests

Or in pyproject.toml:

toml

[tool.pytest.ini_options]
testpaths = ["tests"]
addopts = "-v --tb=short"
markers = [
    "slow: marks tests as slow",
    "integration: marks tests as integration tests"
]

Troubleshooting Common Issues

Test Discovery Issues

•Ensure test files and functions follow naming conventions (test_ prefix)
•Check that pytest can find your tests with pytest --collect-only

Fixture Issues

•Make sure fixture names match between the fixture definition and test function parameter
•Check fixture scopes to ensure they're appropriate for your use case

Assertion Failures

•Use pytest -v for verbose output to see which tests are running
•Use pytest --tb=long for detailed tracebacks
•Pytest provides detailed introspection for assertion failures without special methods