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

	Lettuce https://pypi.org/project/lettuce/	Nose https://nose.readthedocs.io/en/latest/
Programming language	Python	Python
Category	Unit Testing, Acceptance Testing	Unit Testing, unittest Extensions
General info	Lettuce is a BDD testing tool for Python Lettuce is a testing tool for Python which is inspired by Ruby's Cucumber that supports Gherkin. It can execute plain-text functional descriptions as automated tests for Python projects just like Cucumber does for Ruby	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 However It can generate xml results for behaviour tests xUnit style	No
Client-side Allows testing code execution on the client, such as a web browser	Yes By integrating Lettuce with Selenium’s Python bindings, you have a robust framework for testing Django applications. It can test front-end behaviour	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 Lettuce can test various server and database behaviours and interactions	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	N/A	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.	N/A	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.	Yes By using a third party library	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	Unknown	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)	By adding the lettuce-tools library one has access to the Mock module to implement a configurable http REST mock.	Yes The nose library extends the built-in Python unittest module therefore has access to unittest.mock
Grouping Allows organizing tests in groups	Yes It allows grouping of tests	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