pytest vs Test::Unit comparison of testing frameworks
What are the differences between pytest and Test::Unit?

pytest

https://docs.pytest.org/en/latest/

Test::Unit

https://test-unit.github.io/
Programming language

Python

Ruby

Category

Unit Testing

Unit Testing, Intergration Testing

General info

Pytest is the TDD 'all in one' testing framework for Python

Pytest is a powerful Python testing framework that can test all and levels of software. It is considered by many to be the best testing framework in Python with many projects on the internet having switched to it from other frameworks, including Mozilla and Dropbox. This is due to its many powerful features such as ‘assert‘ rewriting, a third-party plugin model and a powerful yet simple fixture model.

Test::Unit is a unit testing framework for Ruby

Test::Unit is an implementation of the xUnit testing framework for ruby which is used for Unit Testing. However Test::Unit has been left in the standard library to support legacy test suites therefore if you are writing new test code use Minitest instead of Test::Unit
xUnit
Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.

No

Yes

test-unit is a xUnit family unit testing framework for Ruby
Client-side
Allows testing code execution on the client, such as a web browser

Yes

pytest can test any part of the stack including front-end components

It could have tested some front-end components but its now legacy hence wouldn't work with the many new front-end components
Server-side
Allows testing the bahovior of a server-side code

Yes

pytest is powerful enough to test database and server components and functionality

Yes

Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

Yes

Pytest has a powerful yet simple fixture model that is unmatched in any other testing framework.

Yes

Fixture methods are available through its ClassMethods Module
Group fixtures
Allows defining a fixed, specific states of data for a group of tests (group-fixtures). This ensures specific environment for a given group of tests.

Yes

Pytest's powerful fixture model allows grouping of fixtures

Yes

Group fixture methods are supported
Generators
Supports data generators for tests. Data generators generate input data for test. The test is then run for each input data produced in this way.

Yes

pytest has a hook function called pytest_generate_tests hook which is called when collecting a test function and one can use it to generate data

No

Licence
Licence type governing the use and redistribution of the software

MIT License

LGPLv2.1, Ruby Licence

Mocks
Mocks are objects that simulate the behavior of real objects. Using mocks allows testing some part of the code in isolation (with other parts mocked when needed)

Yes

By either using unittest.mock or using pytest-mock a thin wrapper that provides mock functionality for pytest

No

Grouping
Allows organizing tests in groups

Yes

Tests can be grouped with pytest by use of markers which are applied to various tests and one can run tests with the marker applied

No

Other
Other useful information about the testing framework