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

	Robot Framework https://robotframework.org/	pytest https://docs.pytest.org/en/latest/
Programming language	Python	Python
Category	Acceptance Testing	Unit Testing
General info	Robot is a Python framework used for acceptance/functional testing Robot is an automated test framework which has a simple plain text syntax and can be extended easily with Python or Java libraries. It can run on the .net-based IronPython and on Jython which is Java based.	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.
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	No
Client-side Allows testing code execution on the client, such as a web browser	Yes Robot has a rich library and can also be easily integrated with Selenium for browser automation to test front-end components	Yes pytest can test any part of the stack including front-end components
Server-side Allows testing the bahovior of a server-side code	Yes Robot can be used for back-end tests as well	Yes pytest is powerful enough to test database and server components and functionality
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	There is no inbuilt way to work with fixtures in Robot however it can integrate with unittest and use fixtures that way	Yes Pytest has a powerful yet simple fixture model that is unmatched in any other testing framework.
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.	By integrating with unittest	Yes Pytest's powerful fixture model allows grouping of fixtures
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 Robot has a library called the Robot Framework Faker library. It contains 147 keywords used for generating random test data	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
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	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 Robot can access Python's mock library for mocking	Yes By either using unittest.mock or using pytest-mock a thin wrapper that provides mock functionality for pytest
Grouping Allows organizing tests in groups	Yes One can create a test suite with Robot	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
Other Other useful information about the testing framework