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

	Python Testify https://github.com/Yelp/Testify	Guage https://gauge.org/
Programming language	Python	.NET
Category	Unit Testing	Acceptance Testing
General info	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	Gauge is a light-weight cross-platform test automation tool for writing acceptance tests. Gauge is a free and open source framework for writing and running acceptance tests. Some of its key features include: -Simple, flexible and rich syntax based on Markdown.; -Consistent cross platform/language support for writing test code.; -A modular architecture with plugins support.
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	No
Client-side Allows testing code execution on the client, such as a web browser	Yes Front-end functionality and behaviour can be tested by Testify.	Yes You can test front-end behaviour by creating testing specifications to test front-end behaviour
Server-side Allows testing the bahovior of a server-side code	Yes Testify can test various server and database behaviours and functionality	Yes You can test back-end behaviour by creating testing specifications to test back-end behaviour
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	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.	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.	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.	N/A
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	GNU General Public License v3.0
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)	Yes It includes the turtle mock object library	Yes You can create mocks using third party libraries like moq
Grouping Allows organizing tests in groups	Yes Testify includes support for detecting and running test suites, grouped by modules, classes, or individual test methods.	Yes You can create test suites with Gauge which can be run using multiple parameters.
Other Other useful information about the testing framework