Organizing test data, fixtures, and Mocks in Python

Kristian Rother is a professional Python trainer, software engineer, and author with 20+ years of experience in Python and teaching. During the past 5 years, he has trained 400 Data Scientists in one of the largest boot camps in Germany. He has also translated several well-known Data Science books for O’Reilly and authored two Python books independently. Currently, he is building ML pipelines in the real estate sector.

In this tutorial, we will write tests for a Python REST API powered by a database.
We will use the pytest framework to create Unit Tests and Integration Tests.

— code structures that make code well-testable
— organizing test data for use with and without
— efficient use of fixtures
— the pros and cons of mocking
— building a small test database
— error handling in tests

The tutorial will be rounded off with a few useful tools that make your life easier when testing Python code.

All materials will be shared under the CC-BY-SA 4.0 License. I believe teacher training is important. I am happy to give a “behind the scenes” tour of the material to people interested in running a similar tutorial or course.

Developers who would like to test Python applications. Basic knowledge of Python is sufficient. You don’t need prior experience with automated testing. To execute the integration tests, Docker is required.

Language: English
When? 15 of March, 19:00 (Kyiv time)
Tickets: teeko.io/...​tures-and-mocks-in-python

100% of the funds from ticket sales will be transferred to the charity fund Children of Heroes for warm clothes for children who lost their parents because of russian aggression on the territory of Ukraine.