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