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

	Quick https://github.com/quick/quick	Nose https://nose.readthedocs.io/en/latest/
Programming language	Swift	Python
Category	Acceptance Testing, Unit Testing	Unit Testing, unittest Extensions
General info	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.	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.	Yes Yes, it is an xUnit style test framework	No
Client-side Allows testing code execution on the client, such as a web browser	Yes Developers can test front-end behaviour and components by defining front-end feature specifications	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 Developers can test back-end behaviour and components by defining back-end feature specifications	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 Quick contains fixture methods setup() and teardown() for setting up and destroying test environments	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 Yes, example groups (logical groupings of examples/tests) can share setup and teardown code	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 Yes, developers can create mock objects with Quick using the Cuckoo library	Yes The nose library extends the built-in Python unittest module therefore has access to unittest.mock
Grouping Allows organizing tests in groups	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.	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