Learn what a test is and how to run the first one of your own with the pytest library! You will get used to the pytest testing framework and the command-line interface. You will also learn how to process specific contexts, like "failed tests" and "skipping the test" with pytest markers.

Introduction to Testing in Python

The first test suite

pytest.raises

Invoking pytest from CLI

# Import the pytest library
____

def multiple_of_two(num):
    if num == 0:
        raise(ValueError)
    return num % 2 == 0

def test_numbers():
    assert multiple_of_two(2) is True
    assert multiple_of_two(3) is False

def test_zero():    
    with pytest.raises(ValueError):
        multiple_of_two(0)


# Import the pytest library
import pytest

def multiple_of_two(num):
    if num == 0:
        raise(ValueError)
    return num % 2 == 0
  
def test_numbers():
    assert multiple_of_two(2) is True
    assert multiple_of_two(3) is False
  
def test_zero():    
    with pytest.raises(ValueError):
        multiple_of_two(0)


Run the test!

# Import the pytest library
____

def multiple_of_two(num):
    if num == 0:
        raise(ValueError)
    return num % 2 == 0

def test_numbers():
    assert multiple_of_two(2) == True
    assert multiple_of_two(3) == False

def test_zero():    
    with pytest.raises(ValueError):
        multiple_of_two(0)


# Import the pytest library
import pytest

def multiple_of_two(num):
    if num == 0:
        raise(ValueError)
    return num % 2 == 0

def test_numbers():
    assert multiple_of_two(2) == True
    assert multiple_of_two(3) == False

def test_zero():    
    with pytest.raises(ValueError):
        multiple_of_two(0)


Run with the keyword

Applying test markers

Options

@pytest.mark.skip

@pytest.mark.xfail

@pytest.mark.skipif

Markers use cases

Failed tests with xfail

Conditional skipping

Creating Tests with pytest

Learn what a fixture is and how to simplify your code by using it in tests. You will get familiar with the fixture @pytest.fixture decorator and the fixture tools. You will analyze your code to see the "fixture part" in it. Finally, learn how to use teardowns to prevent software failures.

Introduction to fixtures

Getting familiar with fixtures

Data preparation

Run with a fixture

Chain Fixtures Requests

Chain this out

List with a custom length

Fixtures autouse

autouse statements

Auto add numbers

Fixtures Teardowns

Data with teardown

Read data with teardown

Pytest Fixtures

Learn what the basic testing types are and their features. Learn about test cases and how they help to implement tests. You will get more skilled with creating test functions and running pytest from CLI in IDE exercises. Finally, you will be able to differentiate the different testing types and create tests for each of them.

Unit testing with pytest

Unit testing terms

Cover more test cases

Factorial of number

Run factorial

Feature testing with pytest

Feature or unit testing

Aggregate with sum

Integration testing with pytest

Integration test or not

Read the file

Performance testing with pytest

What is performance testing?

Finding an element

Speed of loops

Basic Testing Types

In this final chapter, you will meet the unittest framework. First, you will learn basic assertion methods, then its CLI interface, and how to use fixtures. Finally, you will put everything together in the practical examples of data pipelines.

Meeting the Unittest

Factorial with unittest

Is prime or not

CLI Interface

Run factorial with unittest

Erroneouos factorial

Unittest options

Fixtures in unittest

Test the string variable

Palindrome check

Practical examples

Integration and unit tests

Feature and performance tests

Energy pipeline

Congratulations!

Writing tests with unittest

DS_salaries

Energy

Games

Plenty of people write code. Some of them make it work and profitable. But sometimes, even the smartest of the best programmers makes a mistake that can cost millions of dollars. How to decrease the possibility of getting into such a fiasco? How do you ensure that you create a program that does exactly what you want? The very simple answer is: write tests!

During this journey, you will learn the very basics of creating tests in Python. You will meet four types of software testing methods. You will create your own tests to check if the program or a data pipeline works as expected before it goes to production. Whether it is the unexpected null, a typo in your dataset, or mixed-up signs in the equation. You can, and you will catch those cases with the tests.

After the course completion, you will know the types of testing methods, and you will be able to choose the most suitable ones for a specific context. You also will be able to design those tests and implement them in Python using the pytest and the unittest libraries.

<h2>Why tests?</h2>Plenty of people write code. Some of them make it work and profitable. But sometimes, even the smartest of the best programmers makes a mistake that can cost millions of dollars. How to decrease the possibility of getting into such a fiasco? How do you ensure that you create a program that does exactly what you want? The very simple answer is: write tests!<br><br><h2>Python testing basics</h2>During this journey, you will learn the very basics of creating tests in Python. You will meet four types of software testing methods. You will create your own tests to check if the program or a data pipeline works as expected before it goes to production. Whether it is the unexpected null, a typo in your dataset, or mixed-up signs in the equation. You can, and you will catch those cases with the tests.<br><br><h2>Testing with pytest and unittest</h2>After the course completion, you will know the types of testing methods, and you will be able to choose the most suitable ones for a specific context. You also will be able to design those tests and implement them in Python using the `pytest` and the `unittest` libraries.

Writing Functions in Python

Software Engineering Principles in Python

Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.

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Professional Data Engineer in Python

Python Developer

Python Programming

Run with the keyword

Introduction to Testing in Python

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