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

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