The 7 Best Frameworks for Integration and Unit Testing in Python
Bulletproof your software with a rigorous testing regime, made easy by these Python frameworks.
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Python’s simplicity makes it one of the best programming languages for writing automated tests. The language offers a couple of software testing frameworks to help you test more efficiently.
Whether you’re in for an end-to-end test, load and stress testing, or more, these are the best Python-based software testing frameworks.
1. Pytest
Pytest is a simple testing framework written in Python and for Python. Why should you use it for testing? It has an easy learning curve and is a go-to framework for unit and integration testing. It also supports class inheritance from unittest.
One of the strong points of the framework is that it provides a cleaner and shorter way of writing tests in Python. For instance, validating a code output is as straightforward as calling an assert keyword. If you want to run multiple tests simultaneously, Pytest saves time with its headless parallel testing feature.
Pytest also supports command-line execution of test suites. This is as simple as running the pytest command from the test folder terminal. You don’t have to bother about the test files, as the framework detects them automatically.
However, the command also works with file declaration. So you can also invoke Pytest with a file name:
Running a test file with Pytest produces human-friendly output that traces the test steps and tells you where the fault lies:
2. Playwright
The playwright framework is Microsoft’s offering to the software testing community. While many frameworks operate headless-only testing, Playright supports both headless and head modes. It’s one of the best frameworks to test the user interface, with support for Firefox and Chromium-based browsers like Edge and Chrome.
Feature-wise, Playwright is close to Selenium. It matches the latter for cloud-based parallel testing and orchestration tools. But it beats Selenium with its API-testing functionality. Playwright’s parallel testing can be tricky, though—since its event loop only runs single test capability by default. However, you can find your way around this with suitable use of Python loops.
If you want to go codeless, you can use Playwright’s codegen to write test code dynamically. It generates a language-specific test file as you interact with the DOM. Its selector generator also lets you pick web elements easily by merely hovering over them without the pain of inspecting the DOM.
Playwright has default auto-wait. Thus, it pauses for the DOM to load before running test cases. As of writing, the playwright framework supports JavaScript, TypeScript, Java, and .NET in addition to Python.
3. Selenium
Selenium is one of the most-used automation testing frameworks with good community support. Unlike Playwright, it doesn’t offer API-testing capability. So it’s not the framework for testing backend logic. But it does provide both Chromium and non-Chromium-based browser drivers to assess and validate the UI.
The framework has more programming language support and is more versatile in general web automation. It also accepts cloud grid capability for orchestrating test cases in parallel. Thus, it’s an excellent choice for cross-browser and cross-platform testing.
Selenium has an array of dedicated selectors that let you interact with the UI as a regular user. And if you need a dose of UI action assertion, you can inherit this from the unittest class. Selenium also has an IDE extension for Chrome and Firefox. This offers record-and-play testing. But unlike Playwright’s codegen, it doesn’t generate test code.
4. Robot
Robot is a keyword-driven, open-source Python testing framework. Overall, it makes test automation as easy as possible. While you have to write code for test cases in other frameworks, it’s plain English in Robot. So it comes in handy for writing more human-friendly test cases.
Its strength is acceptance testing—to ascertain that software meets specified criteria. Beyond testing, it also features general robotic automation tools for automating UI tasks.
Starting with the Robot framework is easy; you can create a set of tasks written in plain human language. Then prepare test cases for each in separate files. Robot provides little testing functionality, but you can extend this with other testing libraries. For instance, you can pair it with Selenium to add browser capabilities to UI testing.
5. Doctest
Doctest is a built-in Python testing library that lets you document your code as you test. It’s one of the best choices for executing unit tests. But it also supports UI component testing. The library is intuitive, reading docstrings from your code and validating your expected output.
Doctest works by checking a function against a set output. It only throws an error and returns the correctly computed output if your expected result is wrong. Test output in Doctest is clean. If testing on multiple input data, for instance, it gives a detailed failure report, including where the code fails.
A piece of Doctest documented piece of test looks like this, for example:
def findFirst(text):
«»«
Given a string, return the first alphabet
:param: string
>>> findFirst(«Idowu»)
U
«»«
return text[0].upper()
if __name__==«__main__»:
import doctest
doctest.testmod()
The documented test above fails since we expect a U, but the computed result is I instead:
6. Unittest
Unittest provides one of the most structured ways to write unit tests. It supports object-oriented programming by default. It wraps test cases in dedicated classes and executes them in an event loop. With that in mind, unittest is an excellent choice if you prefer to structure your tests in a page object model.
Unittest doesn’t offer UI testing by default. But you can pair it with another testing framework like Selenium to get multiple browser capabilities. You can also run parallel tests with unittest when paired with cloud grid-supported frameworks. Thus, you can leverage its power in integration and end-to-end testing.
When combined with Selenium, for instance, you can check an expected output against a component’s result using the inherited assert keyword. However, unlike Pytest, you’re likely to write more code in unittest since its assertion invocation is more hard-coded.
7. Nose2
Nose2 is closely related to Pytest in functionality. However, it inherits its core properties from the unittest framework. Like Pytest, you can use it as a test runner for test cases written in other frameworks like Selenium or unittest.
It supports both unit and integration testing. So whether you want to test the UI or check your code functions, Nose2 provides all the needed utilities.
It also accepts parameterized testing. This involves inserting test parameters like test browsers and platforms inside a decorator. You can then access each parameter within the code body. This makes Nose2 one of the best frameworks for running cross-browser tests in parallel over cloud grids.
Test Your Program and Release Quality Software
Testing is a good practice in programming that helps you detect and remove bugs before public release. While some testing frameworks are primarily Python-based, others support multiple programming languages.
Although it’s best to keep unit tests to your development language, can be more language-independent. Feel free to use any of these Python testing frameworks accordingly.