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

	Green https://github.com/CleanCut/green	Fixie http://fixie.github.io/
Programming language	Python	.NET
Category	Unit Testing	Unit 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)	Fixie is a .NET test framework similar to NUnit and xUnit Fixie allows test methods to be created and executed like other test frameworks, but takes a takes a conventions-based approach, which is a benefit as we do not need to use attributes to mark classes and methods as tests
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	Yes fixie is an xUnit type testing framework
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	Yes You can unit test front-end components of youra pplications with fixie
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 You can unit test back-end components of your applications with fixie
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 Yes, fixie has fixture methods for setting up tests and at the end of tests to destroy them
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)	Yes Through the use of Python's mock library	N/A
Grouping Allows organizing tests in groups	N/A	Yes You can group tests into suites
Other Other useful information about the testing framework