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pytest VS unittest

Compare pytest VS unittest and see what are their differences

pytest logo pytest

Javascript Testing Framework

unittest logo unittest

Testing Frameworks
  • pytest Landing page
    Landing page //
    2023-10-15
  • unittest Landing page
    Landing page //
    2023-10-19

pytest features and specs

  • Easy to Use
    Pytest is designed to be simple and easy to use, with minimal boilerplate code required to write tests. Its straightforward syntax allows users to quickly write and understand tests.
  • Extensive Plugin System
    Pytest has a flexible and powerful plugin architecture, with a wide range of community-maintained plugins available, allowing for easy customization and extension of its functionality.
  • Detailed Information on Failures
    Pytest provides detailed and informative feedback on failures, enhancing the debugging process by highlighting where and why a test failed.
  • Fixture Support
    Pytest's fixture system allows for easy setup and teardown of test environments, encouraging the reuse of setup code and reducing code duplication.
  • Compatibility
    Pytest is compatible with standard Python testing frameworks such as unittest, allowing for easy migration and integration of existing tests.

Possible disadvantages of pytest

  • Steeper Learning Curve for Advanced Features
    While basic usage is straightforward, mastering advanced pytest features, such as writing custom plugins and fixtures, can have a steeper learning curve.
  • Performance Overhead
    For very large projects, the additional features and flexibility of pytest can introduce some performance overhead when running tests, compared to simpler testing frameworks.
  • Complexity in Parameterized Testing
    While pytest supports parameterized testing, setting up and managing complex parameterizations can become cumbersome and might require additional abstraction layers.
  • Plugin Conflicts
    With a vast ecosystem of plugins, there is a potential for conflicts or compatibility issues between different plugins, especially when they modify similar pytest behaviors.

unittest features and specs

  • Standard Library Integration
    Unittest is part of the Python Standard Library, which means it is included with every standard Python installation. This makes it easily accessible and eliminates the need for additional dependencies.
  • Discoverability
    Unittest automatically discovers tests, which makes it simpler to organize and run a large suite of tests.
  • Test Suite Management
    It provides powerful mechanisms for structuring test cases, including test suites, test cases inheritance, and grouping of tests, allowing for better organization.
  • Compatibility with Other Testing Frameworks
    Unittest is compatible with test runners from other testing frameworks like pytest, providing flexibility and integration with more advanced features if needed.
  • Setup and Teardown Facilities
    It provides built-in setup and teardown methods with setUp(), tearDown(), setUpClass(), and tearDownClass(), which help in preparing the environment before tests and cleaning up afterward.

Possible disadvantages of unittest

  • Verbose Syntax
    The syntax for writing tests in unittest can be more verbose compared to some other testing frameworks, like pytest, which may lead to more boilerplate code.
  • Less Expressive Assertions
    Unittest comes with a set of built-in assertions that are sometimes not as expressive or convenient as those provided by other testing libraries like pytest.
  • Limited Fixtures Flexibility
    While unittest provides basic setUp and tearDown methods, it lacks more sophisticated fixtures that other frameworks like pytest offer, which can lead to less flexible test setups.
  • Steeper Learning Curve
    For beginners, unittest can have a steeper learning curve compared to simpler or more modern testing frameworks, mainly due to its structure and the amount of boilerplate.

pytest videos

getting started with pytest (beginner - intermediate) anthony explains #518

More videos:

  • Review - Python Code Review: Adding Pytest Tests to an Existing Python Web Scraper
  • Review - pytest: everything you need to know about fixtures (intermediate) anthony explains #487

unittest videos

No unittest videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to pytest and unittest)
Automated Testing
37 37%
63% 63
Testing
46 46%
54% 54
Online Services
50 50%
50% 50
Testing Frameworks
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare pytest and unittest

pytest Reviews

25 Python Frameworks to Master
Pytest is a widely adopted testing framework that is designed to be easy to use and extend. It helps you to write elegant tests in both small and complex Python codebases.
Source: kinsta.com

unittest Reviews

25 Python Frameworks to Master
nose2 extends the built-in unittest library and provides a more powerful and flexible way to write and run tests. It’s an extensible tool, so you can use multiple built-in and third-party plugins to your advantage.
Source: kinsta.com

Social recommendations and mentions

Based on our record, unittest seems to be a lot more popular than pytest. While we know about 63 links to unittest, we've tracked only 5 mentions of pytest. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

pytest mentions (5)

  • An Introduction to Testing with Django for Python
    Pytest is an excellent alternative to unittest. Even though it doesn't come built-in to Python itself, it is considered more pythonic than unittest. It doesn't require a TestClass, has less boilerplate code, and has a plain assert statement. Pytest has a rich plugin ecosystem, including a specific Django plugin, pytest-django. - Source: dev.to / about 1 year ago
  • How I Added Continuous Integration (CI) to a C++ Project
    For this lab exercise I had the opportunity to add unit tests to a classmate's project and experience their CI workflow. For this exercise I worked on go-go-web by kliu57. Go-Go Web is written in Python and uses the pytest testing framework. This was my first time writing tests for pytest, but I found the pytest docs helpful. However, more helpful was the information provided in the associated issue and the tests... - Source: dev.to / over 1 year ago
  • CI/CD Part 1: Unit/Integration Testing
    This week, in a setup for a CI/CD pipeline, I added unit and integration testing using Pytest to my Python CLI and utilized pytest-cov for generating a coverage report. As always, the merged commit for changes to the repo can be found here. - Source: dev.to / over 1 year ago
  • Testing in Python
    After looking through the various unit testing tools available for Python like pytest, unittest (built-in), and nose, I went with pytest for its simlpicity and ease of use. - Source: dev.to / over 1 year ago
  • Testing and Refactoring With pytest and pytest-cov
    Up until now we've been using python's unittest module. This was chosen as a first step since it comes with python out of the box. Now that we've gone over dev dependencies I think it's a good time to look at pytest as a unit test alternative. I highly recommend getting accustomed to pytest as it's used quite often in the python ecosystem to handle testing for projects. It's also a bit more user friendly in how it... - Source: dev.to / over 1 year ago

unittest mentions (63)

  • Building a serverless GenAI API with FastAPI, AWS, and CircleCI
    Testing and validating the API is crucial to ensure it is functioning correctly before deploying it. Below are several tests using pytest and unittest packages. The unit tests check if the app runs locally and in AWS Lambda, ensuring that requests work in both setups. - Source: dev.to / about 2 months ago
  • Using Selenium Webdriver with Python's unittest framework
    In this tutorial, we'll be going over how to use Selenium Webdriver with Python's unittest framework. We'll use webdriver-manager to automatically download and install the latest version of Chrome. - Source: dev.to / 3 months ago
  • Asynchronous Server: Building and Rigorously Testing a WebSocket and HTTP Server
    The last part of our CI/CD was running tests and getting coverage reports. In the Python ecosystem, pytest is an extremely popular testing framework. Though very tempting and might still be used later on, we will stick with Python's built-in testing library, unittest, and use coverage for measuring code test coverage of our program. Let's start with the test setup:. - Source: dev.to / 3 months ago
  • Enhance Your Project Quality with These Top Python Libraries
    Unittest is a built-in module of Python. It’s inspired by the xUnit framework architecture. This is a great tool to create and organise test cases in a systematic way. You can use unittest.mock with pytest when you need to create mock objects in your tests. The unittest.mock module is a powerful feature in Python’s standard library for creating mock objects in your tests. It allows you to replace parts of your... - Source: dev.to / about 1 year ago
  • An Introduction to Testing with Django for Python
    Unittest is Python's built-in testing framework. Django extends it with some of its own functionality. - Source: dev.to / about 1 year ago
View more

What are some alternatives?

When comparing pytest and unittest, you can also consider the following products

JUnit - JUnit is a simple framework to write repeatable tests.

Rumprun - The Rumprun unikernel and toolchain for various platforms - rumpkernel/rumprun

Cucumber - Cucumber is a BDD tool for specification of application features and user scenarios in plain text.

PHPTester.net - PHPTester.net gives developers and learners the ability to write their PHP code and get the output online.

RSpec - RSpec is a testing tool for the Ruby programming language born under the banner of Behavior-Driven Development featuring a rich command line program, textual descriptions of examples, and more.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.