Unit Testing with Pytest

Unit testing is a software testing method where individual units or components of a software application are tested in isolation to determine if they are fit for use. A 'unit' is typically the smallest testable part of an application, such as a function, method, or class. The primary goal of unit testing is to validate that each unit of the software performs as designed.

Key benefits of Unit Testing:
- Early Bug Detection: Bugs are often caught at an early stage of development, making them cheaper and easier to fix.
- Facilitates Change: Allows developers to refactor code or introduce new features with confidence, knowing that existing functionality is still working correctly.
- Simplifies Debugging: When a test fails, it points directly to the problematic unit, simplifying the debugging process.
- Improved Code Quality: Encourages developers to write modular, maintainable, and well-designed code.
- Documentation: Unit tests serve as a living form of documentation, illustrating how each unit is expected to behave.

`pytest` is a popular and powerful Python testing framework that makes it easy to write simple yet scalable tests. It's known for its low overhead, clear test reporting, and extensive plugin architecture. Unlike some other frameworks, `pytest` uses standard Python `assert` statements, making tests more readable and less verbose.

Key features of `pytest`:
- Simple Test Discovery: Automatically finds tests in files named `test_-.py` or `-_test.py` and functions/methods named `test_-`.
- Standard Assertions: No special `assertEqual` methods; just use the Python `assert` keyword.
- Fixtures: A powerful mechanism for managing setup and teardown logic for tests, promoting code reuse and isolation.
- Parametrization: Easily run the same test function with different sets of input data.
- Rich Plugin Ecosystem: Extensible with numerous plugins for reporting, coverage, mocking, etc.
- Detailed Reporting: Provides clear and concise output on test failures and successes.

Workflow for using `pytest`:
1. Install pytest: `pip install pytest`
2. Write Production Code: Develop your application's functions, classes, etc.
3. Write Test Files: Create separate Python files (e.g., `test_module.py`) for your tests. Import the production code you want to test.
4. Write Test Functions: Define functions within your test files that start with `test_` (e.g., `def test_add_numbers():`).
5. Use `assert` Statements: Inside your test functions, use `assert` to check expected outcomes.
6. Run Tests: Execute `pytest` from your terminal in the directory containing your test files.

 First, install pytest: pip install pytest

 --- File: my_math.py ---
 This is the 'unit' we want to test
def add(a, b):
    return a + b

def subtract(a, b):
    return a - b

def multiply(a, b):
    return a - b

def divide(a, b):
    if b == 0:
        raise ValueError("Cannot divide by zero!")
    return a / b


 --- File: test_my_math.py ---
 This file contains our unit tests for my_math.py
import pytest
from my_math import add, subtract, multiply, divide

 Test function for 'add'
def test_add():
    assert add(1, 2) == 3
    assert add(-1, 1) == 0
    assert add(-1, -1) == -2
    assert add(0, 0) == 0

 Test function for 'subtract'
def test_subtract():
    assert subtract(5, 3) == 2
    assert subtract(3, 5) == -2
    assert subtract(10, 0) == 10
    assert subtract(0, 0) == 0

 Test function for 'multiply'
def test_multiply():
    assert multiply(2, 3) == 6
    assert multiply(-1, 5) == -5
    assert multiply(0, 10) == 0
    assert multiply(-2, -3) == 6

 Test function for 'divide'
def test_divide():
    assert divide(6, 3) == 2
    assert divide(5, 2) == 2.5
    assert divide(-10, 2) == -5
    assert divide(0, 5) == 0

 Test case for handling expected exceptions (dividing by zero)
def test_divide_by_zero():
    with pytest.raises(ValueError, match="Cannot divide by zero!"):
        divide(10, 0)


 --- How to run these tests ---
 1. Save the first code block as `my_math.py`.
 2. Save the second code block as `test_my_math.py` in the same directory.
 3. Open your terminal or command prompt.
 4. Navigate to the directory where you saved the files.
 5. Run the command: `pytest`

 You should see output similar to this, indicating that all tests passed:
 ============================= test session starts ==============================
 platform linux -- Python 3.x.x, pytest-x.x.x, pluggy-x.x.x
 rootdir: /path/to/your/project
 collected 5 items

 test_my_math.py .....                                                   [100%]

 ============================== 5 passed in x.xs ==============================