Unit Testing with Python Training Course
Unit Testing is a testing approach that tests individual units of source code by modifying their properties or triggering an event to confirm whether the outcome is as expected. PyTest is a full-featured, API-independent, flexible, and extensible testing framework with an advanced, full-bodied fixture model.
In this instructor-led, live training, participants will learn how to use PyTest to write short, maintainable tests that are elegant, expressive and readable.
By the end of this training, participants will be able to:
- Write readable and maintainable tests without the need for boilerplate code.
- Use the fixture model to write small tests.
- Scale tests up to complex functional testing for applications, packages, and libraries.
- Understand and apply PyTest features such as hooks, assert rewriting and plug-ins.
- Reduce test times by running tests in parallel and across multiple processors.
- Run tests in a continuous integration environment, together with other utilities such as tox, mock, coverage, unittest, doctest and Selenium.
- Use Python to test non-Python applications.
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Course Outline
Introduction to Unit Testing with PyTest
Unit Testing with UnitTest vs Unit Testing with PyTest
Writing Readable and Maintainable Tests
Using Mocks, Fakes and Stubs
Using Hooks, Assert Rewriting and Plug-ins
Streamlining Your Tests with Fixtures and Parameterized Testing
Obtaining the Desired Test Coverage
Generating Testable Documentation with Doctest
Integrating Python Unit Tests into a Continuous Integration (CI) Environment
Scaling Your Python Unit Tests
Use Python to Test Non-Python Applications
Summary and Conclusion
Requirements
- A general understanding of automation testing
Audience
- Software testers
Open Training Courses require 5+ participants.
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Testimonials (7)
Expertise of the trainer, even if we asked very precise questions about specific topic, he was able to provide really meaningful and valuable for us questions. He has designed agenda of the training according to our needs and requests.
Filip - Orange Szkolenia Sp. z o.o.
Course - Unit Testing with Python
I loved summaries
Martyna - Orange Szkolenia Sp. z o.o.
Course - Unit Testing with Python
Materials Trainer
Zakar Abid - TII
Course - Unit Testing with Python
Did hands on exercise. Walked through the code. Explained everything very well
Steve Thomas - TII
Course - Unit Testing with Python
No rushing things, though a bit too slow sometimes. Checking excercises with group and comparing solutions
Piotr - ArcelorMittal Business Center of Excellence Poland Sp. z o.o. Sp. k.
Course - Unit Testing with Python
The trainer is interactive with the audience. He is able to reply the questions easily and gives the accurate examples and illustrations in real life. The theoritical and practical rythm are smooth. The exercices give the user a better experience to think and structure his/ her way of testing and developping. Numpy and Pandas may be useful in order to better exploit data, such as performance results, statistics, image treatement, calculating the correlation for biological set images. The Django framework would be helpful for building web API. All this knowledge is an asset. However, I am not sure this would be fruitful for other contexts, since we need unit and Integration tests of Java apps in Python.
Soumaya ELALOUANI - Telemis
Course - Unit Testing with Python
That we started from a simple implementation, adding functionalities/features until we need to update the design to keep having a maintainable software. Definitely real life job problems I see value in this. Also liked the use of VideoUpload project as we can relate to this working in Consult Red. Very open to questions, driving the class in a way asked by the audience.
Thibault Marechal - Red Embedded Consulting Sp. z o.o.
Course - Unit Testing with Python
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