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

	pytest https://docs.pytest.org/en/latest/	DOH https://dojotoolkit.org/reference-guide/1.10/util/doh.html
Programming language	Python	JavaScript
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.	D.O.H means Dojo Objective Harness, it's a test framework for the DOJO web apps which tests and runs on the browser and on cloud test execution services like Browserstack Dojo is a Typescript framework build for modern web application, and D.O.H is a basically unit test library to test JavaScript functions and custom widgets
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 DOH is both flexible and extendable and runs in many environments including many browsers to test various front-end functionalities and 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 Pieces of back-end code can be tested with DOH as it performs Unit tests. It is flexible enough to test server-side behaviour and functionality
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.	It has various fixture methods like setUp(), tearDown() and Performance test fixtures which are just like a regular test fixtures, but with extra options. Specifically, it uses 'testType' to mark it as a "perf" test, which instructs the D.O.H. runner to treat the tests as performance and use the calibrate and execute test runner
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 It supports group 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 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	N/A
Licence Licence type governing the use and redistribution of the software	MIT License	FreeBSD 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	N/A
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 There is a function that allows you to group tests, the 'doh.register(...)' function. It's most commonly used for registering Unit Tests
Other Other useful information about the testing framework