This three-day course provides an introduction and deep dive into testing Python code. The course is intended for users with prior experience in Python who want to develop a better understanding of testing their own code against failures and regressions, and of improving the test coverage of existing code bases. The participants get instructive problems to solve using the newly learned techniques. 

-Why should I test my code?

-How can tests help in pinpointing problems?

-What makes a good test and how can I write it?

-How can I test code with external dependencies?

-How can I avoid them?

-How can I avoid writing (too much) test code?

-How can I keep my test suite maintainable in the future?

-When and why would I use “unittest”, “pytest” or “doctest”?

What do you learn on the first day?

You will learn how to write your first unit testing program in Python. We start slowly and look at the should/actual principle of testing frameworks. You learn how the test structure should look like, how you should name your test methods and how you can find the test data. The equivalence classes and boundary value techniques are suitable for this. You master the syntax and semantics of Unit Test and PyTest. After this day, you will be able to write and use good unit tests for your Python code.

What do you learn on the second day?

On the second day you learn more advanced techniques with Pytest, Unit Test and doctest. For example, you learn how to test database and third-party APIs by simulating their code. This is what the Test Double technique is for. Test Double is a collective term for 5 techniques: Dummy, Fake, Stub, Spy and Mock. You will learn how to use these techniques with the Python test frameworks.

What do you learn on the third day?

The last Unit Testing training with Java is about how to write good tests. Here you will learn the SOLID principles for testable design. Then we look at the Test-Driven-Development (TDD) technique. TDD implements the "Test First: Test code before Production code" method. 

TDD slows down the development speed at the beginning, but later on it catches up massively in speed and is definitely more advantageous than writing the tests afterwards. After all, Clean Code is largely based on writing unit tests before production code, so you have to think about the production code in a fundamental way! You will also learn the important rules for writing meaningful and good tests and the best practices. This will help you recognise the so-called "test smells". 

Test smells is a term for bad tests that bring more disadvantages than advantages. There is a long catalogue for this, which divides the test smells into 3 categories and in each category there are several test smells cases. We look at the most important test smells cases.

CERTIFICATE

Of course, you will receive a certificate as a participant in the Python Unit Test Course for Programmers. The prerequisite for this is the complete participation in all course units and programming tasks and the successful programming of a small final project. However, this will be more fun than stressful for you after this intensive unit testing course.

The agenda is written in English due to the numerous technical terms. Descriptions and course material are in German. You can book the course either in German or English.

All seminar contents are individually adapted to the wishes of our participants. They can vary depending on the level of knowledge and will be defined together with the seminar leader on day 1. In this Python unit test seminar you can choose from the following topics:

Test Double

• Motivation
• Testing Database?
• Dummy
• Fake
• Stub
• Spy
• Mock

doctest

• why doctest?
• Executable documentation
• Executable specification
• pytst vs. unites vs. doctest

Test Driven Development

• Motivation
• RED
• GREEN
• REFACTORING
• Baby Steps
• TDD Advantages

Testable Design

• SOLID Principle
• Single Responsibility
• Open Close
• Liskov Substitution
• Interface Segregation
• Dependency Inversion

Clean Test

• Clean Test Rules
• Test Readability
• Test Maintainability
• Test Trustworthiness
• Test Smells Catalog