Python Testify vs mocha-parallel-tests comparison of testing frameworks
What are the differences between Python Testify and mocha-parallel-tests?

	Python Testify https://github.com/Yelp/Testify	mocha-parallel-tests https://www.npmjs.com/package/mocha-parallel-tests
Programming language	Python	JavaScript
Category	Unit Testing	Unit Testing, Intergration Testing, End-to-End Testing
General info	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	mocha-parallel-tests is a test runner for tests written with mocha testing framework. mocha-parallel-tests allows you to run your tests in parallel and executes each of your test files in a separate process while still maintaining the output of mocha
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	N/A
Client-side Allows testing code execution on the client, such as a web browser	Yes Front-end functionality and behaviour can be tested by Testify.	Yes Mocha-parallel-tests Runs in the browser and is used widely to test front-end components and functionality. It can test various DOM elements, front-end functions and so on.
Server-side Allows testing the bahovior of a server-side code	Yes Testify can test various server and database behaviours and functionality	Yes Mocha-parallel-tests provides convenient ways of testing the Node server.
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	Yes Fixture methods are supported and it follows a decorator based approach, that is they are written similar to decorators	Mocha, which is the the framework which mocha-parallel-tests runs provides the hooks before(), after(), beforeEach(), and afterEach() to set up preconditions and clean up after your tests
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 Group fixtures are supported	Yes Group fixtures are available
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.	N/A
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 It includes the turtle mock object library	Provides Mocking capabilities through third party Libraries like sinon.js, simple-mock and nock
Grouping Allows organizing tests in groups	Yes Testify includes support for detecting and running test suites, grouped by modules, classes, or individual test methods.	Yes Grouping is supported and is accomplished by the using a nested 'describe()'
Other Other useful information about the testing framework