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

stestr

https://pypi.org/project/stestr/

Guage

https://gauge.org/
Programming language

Python

.NET

Category

Unit Testing

Acceptance Testing

General info

stestr is a Python test runner designed to execute unittest test suites

stestr executes unittest test suites by using multiple processes to split up execution of a test suite then stores a history of all test runs to help in debugging failures and optimizing the scheduler to improve speed.

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

Stestr being a test runner that runs unittest tests, it can test fron-tend functionality and behaviour.

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

Stestr being a test runner that runs unittest tests, it can run back-end tests for functionality and behaviour.

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

By use of a third party library like Fixture

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.

By use of a third party library like Fixture

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

By using a library like test-generator

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)

N/A

Yes

You can create mocks using third party libraries like moq
Grouping
Allows organizing tests in groups

N/A

Yes

You can create test suites with Gauge which can be run using multiple parameters.
Other
Other useful information about the testing framework