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

	Lettuce https://pypi.org/project/lettuce/	Unitils http://www.unitils.org/summary.html
Programming language	Python	Java
Category	Unit Testing, Acceptance Testing	Unit Testing, Intergration Testing
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	Unitils is an open source library whose goal is to make unit and integration testing easy and maintainable. Unitils is divided into modules, each of them providing support for a certain aspect of your unit and integration tests. For example if you need mocking for your tests, just include unitils-mock as a dependency, If you would also want to load DbUnit data sets, just include unitils-dbunit
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 You can perform unit tests on various components and functionality that make up the front-end
Server-side Allows testing the bahovior of a server-side code	Yes Lettuce can test various server and database behaviours and interactions	Yes Unitils provides support for testing the back-end through modules such as DbUnit which specifically tests your database, i.e connections setup and so on
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	N/A
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
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
Licence Licence type governing the use and redistribution of the software	Unknown
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.
Grouping Allows organizing tests in groups	Yes It allows grouping of tests
Other Other useful information about the testing framework