Intern vs Python Testify comparison of testing frameworks
What are the differences between Intern and Python Testify?

	Intern https://github.com/theintern/intern	Python Testify https://github.com/Yelp/Testify
Programming language	JavaScript	Python
Category	Unit Testing, Functional Testing	Unit Testing
General info	Intern is minimal test system for JavaScript designed to write and run consistent. Intern is a complete test system for JavaScript designed to help you write and run consistent, high-quality test cases for your JavaScript libraries and applications. Using Intern we can write tests in JavaScript and TypeScript using any style like TDD, and BDD. Intern can run unit tests in most browsers that support ECMAScript	A Python unit testing framework modelled after unittest Testify is modelled after unittest but has more features while still supporting unittest classes. It has more pythonic naming conventions, an better test runner output visually, a decorator-based approach to fixture methods among many other features
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 Intern is a complete test system for JavaScript It Runs in the browser and can test any front-end component and functionality	Yes Front-end functionality and behaviour can be tested by Testify.
Server-side Allows testing the bahovior of a server-side code	Yes Since it is a complete testing system that can test any type of JavaScript code, it can test server-side behaviour and components as well	Yes Testify can test various server and database behaviours and functionality
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	N/A	Yes Fixture methods are supported and it follows a decorator based approach, that is they are written similar to decorators
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.	N/A	Yes Group fixtures are supported
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 One can create generator methods to yield runnable test methods which will pick out the test methods from your TestCases, and then exclude any in any of your exclude_suites method.If there are any require_suites, it will then further limit itself to test methods in those suites.
Licence Licence type governing the use and redistribution of the software	FreeBSD 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)	Intern uses the Dojo Toolkit’s AMD loader. To mock, you should be able to just use the standard AMD 'map' feature, else you can use third party libraries like sinon.js	Yes It includes the turtle mock object library
Grouping Allows organizing tests in groups	Yes You can group tests into Suites which may be specified as file paths or using glob expressions, there is typically one top-level suite per module.	Yes Testify includes support for detecting and running test suites, grouped by modules, classes, or individual test methods.
Other Other useful information about the testing framework