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

	Nose https://nose.readthedocs.io/en/latest/	unittest https://docs.Python.org/3/library/unittest.html
Programming language	Python	Python
Category	Unit Testing, unittest Extensions	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.	unittest is a unit testing framework for Python The unittest test framework is Python’s xUnit style framework. It is a standard module that is bundled with Python and supports the automation and aggregation of tests and common setup and shutdown code for them.
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	Yes unittest is a xUnit style frameworkfor Python, it was previously called PyUnit.
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 Front-end functionality and behaviour can be tested by unittest.
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 Since the webserver funtionalities have their own features and each feature has its own functions, we can write tests with unittest to test each function
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 By use of the 'setUp()' function which is called to prepare the test fixture
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 unittest allows you to group your initialization code into a setUp function and clean up code in a tearDown function
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	Yes unittest contains generator methods in the module 'unittest.TestCase'
Licence Licence type governing the use and redistribution of the software	GNU Library or Lesser General Public License (LGPL) (GNU LGPL)	MIT License
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 Mocks are available from the library unittest.mock which allows you to replace parts of your system under test with mock objects
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 One can build suites either manually or use test discovery to build the suite automatically by scanning a directory
Other Other useful information about the testing framework