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

	Nose https://nose.readthedocs.io/en/latest/	Quick https://github.com/quick/quick
Programming language	Python	Swift
Category	Unit Testing, unittest Extensions	Acceptance Testing, Unit 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.	Quick is a Swift (and Objective-C) testing framework. Quick is a behavior-driven development framework for Swift and Objective-C that is inspired by RSpec, Specta, and Ginkgo. Quick comes bundled with Nimble a matcher framework for your tests.
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	Yes Yes, it is an xUnit style test framework
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 Developers can test front-end behaviour and components by defining front-end feature specifications
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 Developers can test back-end behaviour and components by defining back-end feature specifications
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.	Yes Quick contains fixture methods setup() and teardown() for setting up and destroying test environments
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.	Yes Yes, example groups (logical groupings of examples/tests) can share setup and teardown code
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)	Apache License 2.0
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 Yes, developers can create mock objects with Quick using the Cuckoo library
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 In Quick test suites are named Specs, and every test suite you create starts off with a class inheriting from QuickSpec includes a main method, spec() which contains all the test cases.
Other Other useful information about the testing framework