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

	Guage https://gauge.org/	Python Testify https://github.com/Yelp/Testify
Programming language	.NET	Python
Category	Acceptance Testing	Unit Testing
General info	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.	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.	No	No
Client-side Allows testing code execution on the client, such as a web browser	Yes You can test front-end behaviour by creating testing specifications to test front-end behaviour	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 test back-end behaviour by creating testing specifications to test back-end behaviour	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 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.	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	GNU General Public License v3.0	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)	Yes You can create mocks using third party libraries like moq	Yes It includes the turtle mock object library
Grouping Allows organizing tests in groups	Yes You can create test suites with Gauge which can be run using multiple parameters.	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