The Comprehensive Guide To Built-In Python Testing Tools
What is Python code testing and why does it matter?
In the software development life cycle, testing your code is essential. So, choosing – and using – the right Python testing tools should also be an essential part of writing good quality code.
Writing testing code and running it in parallel is now considered a good practice (that is often skipped by beginners). By implementing them wisely, testing would help to define your code’s intent more precisely and have a more decoupled architecture. If you don’t check your Python code BEFORE it reaches your end users, you run the risk of losing their goodwill if the program has bugs in it or, even worse, totally destroying your app’s reputation so nobody will want to use it in the first place.
The testing phases of the software development life cycle assist businesses in identifying all bugs and errors in the software prior to the implementation phase. If software bugs are not resolved prior to deployment, they can adversely affect the client’s business.
Furthermore, attempting to resolve these issues at a later stage can result in substantial costs. The longer you delay the detection of these issues, the greater the cost you are likely to face.
The following are different types of tests you should have and are often represented as a pyramid.
The lower you go on the pyramid, the smaller the unit of code being tested, and the more tests you should have. For example, one UI (E2E) test phase might test the flow of creating, editing, and then saving a document. That flow is composed of many different functions, each one of them should have its own unit tests.
In this article, we will limit our scope to Python’s built-in unit testing framework.
If you are looking for articles about Python profiling tools, read it here:
The following are some unittest important concepts in an object-oriented way:
| test fixture | Represents the preparation needed to perform one or more tests, and any associated cleanup actions. This could include things like making temporary or proxy databases, directories, or starting a server process. |
| test case | The individual testing unit. It looks for a specific response to a specific set of inputs. unittest includes a base class called TestCase that can be used to create new test cases. |
| test suite | A collection of test cases, test suites, or both. It is used to group tests that should be run together. |
| test runner | A component that orchestrates test execution and reports the results to the user. To indicate the results of running the tests, the runner may use a graphical interface, a textual interface, or return a special value. |
How do I get the unittest library?
As unittest is a built-in Python unit testing library, no further installation is needed.
How to perform unit testing with the unittest Python testing tools?
The following is a short script to test three-string methods (source: docs.python.org):