pytest vs unittest comparison of testing frameworks
What are the differences between pytest and unittest?

	pytest https://docs.pytest.org/en/latest/	unittest https://docs.Python.org/3/library/unittest.html
Programming language	Python	Python
Category	Unit Testing	Unit 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.	unittest is a unit testing framework for Python The unittest test framework is Python’s xUnit style framework. It is a standard module that is bundled with Python and supports the automation and aggregation of tests and common setup and shutdown code for them.
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	Yes unittest is a xUnit style frameworkfor Python, it was previously called PyUnit.
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	Yes Front-end functionality and behaviour can be tested by unittest.
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 Since the webserver funtionalities have their own features and each feature has its own functions, we can write tests with unittest to test each function
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 By use of the 'setUp()' function which is called to prepare the test fixture
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 unittest allows you to group your initialization code into a setUp function and clean up code in a tearDown function
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	Yes unittest contains generator methods in the module 'unittest.TestCase'
Licence Licence type governing the use and redistribution of the software	MIT License	MIT License
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	Yes Mocks are available from the library unittest.mock which allows you to replace parts of your system under test with mock objects
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	Yes One can build suites either manually or use test discovery to build the suite automatically by scanning a directory
Other Other useful information about the testing framework