wru vs Green comparison of testing frameworks
What are the differences between wru and Green?

wru

https://github.com/WebReflection/wru

Green

https://github.com/CleanCut/green
Programming language

JavaScript

Python

Category

Unit Testing

Unit Testing

General info

wru is an essential general purpose test framework compatible with web environment, node.js, Rhino, and now PhantomJS too.

wru is compatible with basically all possible browsers out there included IE5.5, IE6, IE7, IE8, IE9, IE10, Chrome, Firefox, Safari, Webkit based, Mobile Browsers, and Opera. On server side wru is compatible with latest node.js, Rhino, PhantomJS, and JavaScriptCore versions.

Green is a clean, colorful, fast Python test runner

This is a test runner that has pretty printing on output that makes results easy to read and understand. Some of its features include: Tests running in independent processes (fast), low redundancy in output (clean), supports pretty printing that is the terminal output, makes good use of color when the terminal supports it (colorful)
xUnit
Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.

Yes

Wru is compatible with xUnit

No

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

Yes

Wru tests front-end components and functions, it is compatible with HTML and runs on probably all browsers

Yes

It can test front-end components of the django framework
Server-side
Allows testing the bahovior of a server-side code

Yes

It is used to test back-end components and behaviour and runs in server environments

Yes

It can test server-side behaviours of web applications written with Python
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

N/A

N/A

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

N/A

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

N/A

Licence
Licence type governing the use and redistribution of the software

MIT 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)

You can implement your stubs and mocks using a wru.assert(...) when necessary during a specific test.

Yes

Through the use of Python's mock library
Grouping
Allows organizing tests in groups

N/A

N/A

Other
Other useful information about the testing framework