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

Nose

https://nose.readthedocs.io/en/latest/

Guage

https://gauge.org/
Programming language

Python

.NET

Category

Unit Testing, unittest Extensions

Acceptance Testing

General info

Nose is a Python unit test framework

This is a Python unit test framework that intergrates well with doctests, unnittests, and 'no-boilerplate tests', that is tests written from scratch without a specific boilerplate.

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

nose is a unit testing tool which is very similar to unittest. It is basically unittest with extensions therefore just like unittest is can test front-end components 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

Nose can test back-end components and functionality as small units. One can write tests for each function that provides back-end 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

nose supports fixtures at the package, module, class, and test case levels, so that initialization which can be expensive is done as infrequently as possible.

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 allowed with nose, where a multitest state can be defined.

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.

Through use of third party libraries like test-generator and from the 'unittest.TestCase' library

N/A

Licence
Licence type governing the use and redistribution of the software

GNU Library or Lesser General Public License (LGPL) (GNU LGPL)

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

The nose library extends the built-in Python unittest module therefore has access to unittest.mock

Yes

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

Yes

With nose it collects tests automatically and there’s no need to manually collect test cases into test suites.

Yes

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