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

Nose

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

JGiven

http://jgiven.org/
Programming language

Python

Java

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.

JGiven is a BDD tool for Java in plain java.

With JGiven Developers write scenarios in plain Java using a fluent, domain-specific API, JGiven generates reports that are readable by domain experts.
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 UI functionality or behaviour by writing scenarios that cover 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 write 'scenarios' to test server-side behaviours
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.

N/A

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)

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 use third party libraries such as JMock and JMockit to mock objects and functions
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.

Other
Other useful information about the testing framework