Green vs Test::Unit comparison of testing frameworks
What are the differences between Green and Test::Unit?

	Green https://github.com/CleanCut/green	Test::Unit https://test-unit.github.io/
Programming language	Python	Ruby
Category	Unit Testing	Unit Testing, Intergration Testing
General info	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)	Test::Unit is a unit testing framework for Ruby Test::Unit is an implementation of the xUnit testing framework for ruby which is used for Unit Testing. However Test::Unit has been left in the standard library to support legacy test suites therefore if you are writing new test code use Minitest instead of Test::Unit
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	Yes test-unit is a xUnit family unit testing framework for Ruby
Client-side Allows testing code execution on the client, such as a web browser	Yes It can test front-end components of the django framework	It could have tested some front-end components but its now legacy hence wouldn't work with the many new front-end components
Server-side Allows testing the bahovior of a server-side code	Yes It can test server-side behaviours of web applications written with Python	Yes
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 available through its ClassMethods Module
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 fixture methods 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	No
Licence Licence type governing the use and redistribution of the software	MIT License	LGPLv2.1, Ruby Licence
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 Through the use of Python's mock library	No
Grouping Allows organizing tests in groups	N/A	No
Other Other useful information about the testing framework