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

DOH

https://dojotoolkit.org/reference-guide/1.10/util/doh.html

pytest

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

JavaScript

Python

Category

Unit Testing

Unit Testing

General info

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

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

DOH is both flexible and extendable and runs in many environments including many browsers to test various front-end functionalities and 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

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

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

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

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.

Yes

It supports group fixtures

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.

N/A

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

FreeBSD 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)

N/A

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

There is a function that allows you to group tests, the 'doh.register(...)' function. It's most commonly used for registering Unit Tests

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