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

	Spock http://spockframework.org/	Nose https://nose.readthedocs.io/en/latest/
Programming language	Java	Python
Category	Unit Testing	Unit Testing, unittest Extensions
General info	Spock is a testing and specification framework for Java and Groovy applications Spock has a highly expressive specification language, and due to its JUnit runner, Spock is compatible with most IDEs, build tools, and continuous integration servers.Spock is inspired from JUnit, RSpec, jMock, Mockito, Groovy, Scala, Vulcans among others	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.
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 Spock tests front-end components and functionality by unit testing individual classes and functions	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
Server-side Allows testing the bahovior of a server-side code	Yes Spock tests back-end components and functionality by unit testing individual classes and functions	Yes Nose can test back-end components and functionality as small units. One can write tests for each function that provides back-end functionality
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	Yes Spock contains four methods for setting up environments :setup() (run before every feature method), cleanup() (run after every feature method), setupSpec() (run before the first feature method), cleanupSpec() (run after the last feature method)	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 You can use the fixture methods to setup environments for groups 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.	N/A	Through use of third party libraries like test-generator and from the 'unittest.TestCase' library
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	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 Spock has inbuilt mocking capabilities and has no need for external libraries	Yes The nose library extends the built-in Python unittest module therefore has access to unittest.mock
Grouping Allows organizing tests in groups	Yes You can create suites manually in spock	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