104. Unit Testing with pytest

1. Basic Test with assert Statement

# 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.

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2. Testing Functions with Multiple Assertions

# 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.

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3. Using pytest.mark.parametrize to Parametrize Tests

# 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.

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4. Testing Exceptions with pytest.raises

# 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.

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5. Using Fixtures for Test Setup

# 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.

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6. Test Skipping with pytest.mark.skip

# 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.

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7. Test Condition with pytest.mark.skipif

# 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.

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8. Testing a Class Method

# 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.

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9. Using pytest.fixture for Cleanup (Teardown)

# 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.

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10. Test Coverage with pytest-cov

# 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.

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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:

   pytest test_example.py

2. To install pytest:

   • Install it via pip:

   pip install pytest

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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.