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

	Nose https://nose.readthedocs.io/en/latest/	SpecFlow https://specflow.org/
Programming language	Python	.NET
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.	SpecFlow is a test automation solution for .NET SpecFlow is a test automation solution for .NET which follows the BDD paradigm, and is part of the Cucumber family. SpecFlow tests are written with Gherkin, using the official Gherkin parser which allows you to write test cases using natural languages and supports over 70 languages.
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 Front-end behaviour is tested. With specflow specifications of the expected behaviours are made and specflow tests against this
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 Back-end behaviour is tested. Specifications of the expected behaviours are made and specflow tests against them
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 BeforeTestRun and AfterTestRun are executed once for each thread which is a limitation of the current architecture.
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	Yes SpecFlow contains a generator component. The SpecFlow IDE integration tries to locate the generator component in your project structure, in order to use the generator version matching the SpecFlow runtime in your project
Licence Licence type governing the use and redistribution of the software	GNU Library or Lesser General Public License (LGPL) (GNU LGPL)	BSD 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 Specflow intergrates well with mock to give it excellent mocking capabilities
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 You can create test suites with specflow
Other Other useful information about the testing framework