104. Unit Testing with pytest

The pytest framework is one of the most popular testing frameworks for Python. It allows for simple unit testing with powerful features such as fixtures, parameterized tests, and detailed assertion introspection.

Below are 10 Python snippets demonstrating how to write and execute tests using pytest.

1. Basic Test with assert Statement

Copy

# test_example.py
def test_addition():
    result = 2 + 3
    assert result == 5  # This test will pass

Explanation: This is a simple test where we check if the addition of 2 and 3 equals 5. The assert statement is used to verify the correctness of the output.

---

2. Testing Functions with Multiple Assertions

Copy

# test_example.py
def test_multiplication_and_division():
    assert 2 * 3 == 6
    assert 9 / 3 == 3

Explanation: We can use multiple assertions in a single test to check different conditions.

---

3. Using pytest.mark.parametrize to Parametrize Tests

Copy

# test_example.py
import pytest

@pytest.mark.parametrize("a, b, expected", [(2, 3, 5), (5, 5, 10), (1, 9, 10)])
def test_addition(a, b, expected):
    assert a + b == expected

Explanation: pytest.mark.parametrize allows us to run the same test with different input values, reducing code duplication and testing various cases.

---

4. Testing Exceptions with pytest.raises

Copy

# test_example.py
import pytest

def test_zero_division():
    with pytest.raises(ZeroDivisionError):
        result = 1 / 0

Explanation: pytest.raises is used to check if an exception is raised when a specific code is executed. In this case, dividing by zero should raise a ZeroDivisionError.

---

5. Using Fixtures for Test Setup

Copy

# test_example.py
import pytest

@pytest.fixture
def setup_data():
    return {"name": "Alice", "age": 30}

def test_greeting(setup_data):
    assert setup_data["name"] == "Alice"
    assert setup_data["age"] == 30

Explanation: pytest.fixture allows us to define setup code that can be shared across multiple tests. Here, setup_data is used to provide data for the test_greeting function.

---

6. Test Skipping with pytest.mark.skip

Copy

# test_example.py
import pytest

@pytest.mark.skip(reason="This test is skipped for now")
def test_addition():
    assert 2 + 3 == 5

Explanation: pytest.mark.skip is used to skip a test. You can also add a reason for skipping the test.

---

7. Test Condition with pytest.mark.skipif

Copy

# test_example.py
import pytest
import sys

@pytest.mark.skipif(sys.version_info < (3, 7), reason="Python version too old")
def test_feature_that_requires_python37():
    assert True

Explanation: pytest.mark.skipif is used to skip tests based on certain conditions. In this example, the test is skipped if the Python version is less than 3.7.

---

8. Testing a Class Method

Copy

# test_example.py
class Calculator:
    def add(self, a, b):
        return a + b
    
def test_add_method():
    calc = Calculator()
    result = calc.add(2, 3)
    assert result == 5

Explanation: Here, we test a method of a class (add) to ensure it performs the correct operation.

---

9. Using pytest.fixture for Cleanup (Teardown)

Copy

# test_example.py
import pytest

@pytest.fixture
def setup_and_teardown():
    print("\nSetting up resources")
    yield "some_data"
    print("\nTearing down resources")

def test_resource(setup_and_teardown):
    assert setup_and_teardown == "some_data"

Explanation: Fixtures can also handle teardown. In the above example, yield allows us to perform cleanup after the test is executed.

---

10. Test Coverage with pytest-cov

Copy

# To run tests with coverage, use pytest with the `--cov` flag:
pytest --cov=your_module_name

Explanation: pytest-cov is a plugin that helps you measure test coverage. You can use the --cov flag to specify the module for which you want to check the test coverage.

---

Running the Tests:

1. To run the tests:

   • Save the above code snippets into a file named test_example.py.

   • Run the tests with pytest in the terminal:

   Copy

   pytest test_example.py

2. To install pytest:

   • Install it via pip:

   Copy

   pip install pytest

---

Summary of Key Concepts:

• assert: Used for basic assertions in tests.

• pytest.mark.parametrize: Parametrizes the test to run with multiple sets of inputs.

• pytest.raises: Used to test for exceptions in a block of code.

• pytest.fixture: Provides setup and teardown functionality for tests.

• Test skipping: Skipping tests using skip or conditionally with skipif.

• Test class methods: Testing instance methods of classes.

• Test cleanup: Using yield in fixtures to handle teardown logic.

• Test coverage: Using the pytest-cov plugin to measure test coverage.

These features of pytest help you write flexible, efficient, and maintainable tests for your Python code.