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Introduction to Testing in Python
4.8(1,351)25k studentsADVANCEDEnglish
Korshub's take
The Korshub Take
Automated software testing is essential to prevent costly production errors and ensure data pipeline reliability. This advanced Python course provides a structured introduction to software testing methodologies, showing how to write effective test suites using both pytest and unittest.
Who It's For
Python developers, data engineers, and software engineers who want to automate code verification, catch edge cases early, and safeguard production workflows.
Key Takeaways
- Testing Frameworks: Master the usage of Python's built-in unittest module and the powerful pytest framework.
- Testing Types & Strategies: Distinguish between unit, integration, functional, and regression testing methods to select the right approach.
- Data Pipeline Verification: Write targeted tests to catch missing values, incorrect formulas, schema mismatches, and unexpected nulls before production deployment.
About this course
Why tests?
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!Python testing basics
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.Testing with pytest and unittest
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.Advertisement