Knapsack Pro

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

mocha-parallel-tests

https://www.npmjs.com/package/mocha-parallel-tests

Python Testify

https://github.com/Yelp/Testify
Programming language

JavaScript

Python

Category

Unit Testing, Intergration Testing, End-to-End Testing

Unit Testing

General info

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

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.

N/A

No

Client-side
Allows testing code execution on the client, such as a web browser

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.

Yes

Front-end functionality and behaviour can be tested by Testify.
Server-side
Allows testing the bahovior of a server-side code

Yes

Mocha-parallel-tests provides convenient ways of testing the Node server.

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

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

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.

Yes

Group fixtures are available

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.

N/A

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

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)

Provides Mocking capabilities through third party Libraries like sinon.js, simple-mock and nock

Yes

It includes the turtle mock object library
Grouping
Allows organizing tests in groups

Yes

Grouping is supported and is accomplished by the using a nested 'describe()'

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