Getting Started with Pytest: A Comprehensive Guide

What is Pytest?

Pytest is a popular testing framework for Python that makes it easy to write simple and scalable test cases. It provides a robust set of features for creating and executing tests, making it a preferred choice for Python developers.

Key Features:

• Simple Syntax: Write tests using standard Python assert statements.
• Auto-Discovery: Automatically finds and runs tests in your project.
• Detailed Reporting: Provides comprehensive information on test failures.
• Fixtures: A powerful mechanism for test setup and dependency injection.
• Parameterization: Run the same test with different input values.
• Plugin System: An extensive ecosystem of plugins for additional functionality.

When to Use Pytest:

Pytest is particularly useful in the following scenarios:

• Unit Testing: Testing individual components and functions in isolation.
• Integration Testing: Assessing how different parts of your application work together.
• Functional Testing: Evaluating complete features from a user’s perspective.
• API Testing: Verifying API endpoints and responses.

Basic Example:

Installation

pip install pytest
        

Here’s a simple test function:

def test_addition():
    assert 1 + 1 == 2
        

In this example, the test_addition function checks that the sum of 1 and 1 equals 2. Pytest also supports fixtures, which are functions that provide a fixed baseline for tests. Fixtures can be used for setup and teardown operations.

import pytest

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

def test_list_length(sample_data):
    assert len(sample_data) == 3
        

In this case, the sample_data fixture provides a list, and the test_list_length function verifies that its length is 3.

• There is an tab in cursor/vscode/pycharm that you can configure to see better the pytests, as you can see in the image below configured for pytest. You can run individual tests and debug easier, really easy to setup

• If you use the command "pytest -lf" you will run only last failed tests
• If you use "pytest -nf", it will show new tests
• If you use "pytest -sw" will stop when something fails, so you can test.
• If you want to see more history testing details, you should use .pytest_cache

Here are some test examples you can see from my github, that you can clone at the link https://github.com/henrique-frank/PyTest.git:

def test_hello():
    expected = "Hello World"
    assert expected == "Hello World"

def test_fail():
    expected = "Hello World"
    assert expected == "Hello World", 'failed test internal'

def test_a1():
    print("This is my first test")
    assert 5 + 5 == 0
    assert 5 - 5 == 0
    assert 5 * 5 == 25
    assert 5 / 5 == 1

def test_a2():
    assert 'a'in 'Santa', 'failed test internal'
        

Best Practices:

To make the most of Pytest, consider the following best practices:

• Naming Conventions: Name test files with the prefix test_ or suffix _test.
• Descriptive Test Names: Write clear, descriptive test names that indicate what’s being tested.
• Modular Fixtures: Use fixtures to manage setup and teardown, promoting code reuse.
• Parameterized Tests: Leverage parameterization to run tests with multiple sets of data.
• Continuous Integration: Integrate Pytest with CI/CD pipelines to automate testing.

By following these practices, you can write efficient and maintainable tests, ensuring the reliability of your Python applications.

For more detailed information and advanced features, refer to the official Pytest documentation.

#Python #Pytest #Testing #SoftwareDevelopment #QA