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

pytest

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

Robot Framework

https://robotframework.org/
Programming language

Python

Python

Category

Unit Testing

Acceptance 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.

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.
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

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

Yes

Robot has a rich library and can also be easily integrated with Selenium for browser automation to test 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

Robot can be used for back-end tests as well
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.

There is no inbuilt way to work with fixtures in Robot however it can integrate with unittest and use fixtures that way
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

By integrating with unittest
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

Robot has a library called the Robot Framework Faker library. It contains 147 keywords used for generating random test data
Licence
Licence type governing the use and redistribution of the software

MIT License

Apache License 2.0

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

Robot can access Python's mock library for mocking
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 create a test suite with Robot
Other
Other useful information about the testing framework