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

	Fixie http://fixie.github.io/	Python Testify https://github.com/Yelp/Testify
Programming language	.NET	Python
Category	Unit Testing	Unit Testing
General info	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	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.	Yes fixie is an xUnit type testing framework	No
Client-side Allows testing code execution on the client, such as a web browser	Yes You can unit test front-end components of youra pplications with fixie	Yes Front-end functionality and behaviour can be tested by Testify.
Server-side Allows testing the bahovior of a server-side code	Yes You can unit test back-end components of your applications with fixie	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	Yes Yes, fixie has fixture methods for setting up tests and at the end of tests to destroy them	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.	N/A	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)	N/A	Yes It includes the turtle mock object library
Grouping Allows organizing tests in groups	Yes You can group tests into suites	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