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

	Python Testify https://github.com/Yelp/Testify	Lettuce https://pypi.org/project/lettuce/
Programming language	Python	Python
Category	Unit Testing	Unit Testing, Acceptance Testing
General info	A Python unit testing framework modelled after unittest Testify is modelled after unittest but has more features while still supporting unittest classes. It has more pythonic naming conventions, an better test runner output visually, a decorator-based approach to fixture methods among many other features	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
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	No However It can generate xml results for behaviour tests xUnit style
Client-side Allows testing code execution on the client, such as a web browser	Yes Front-end functionality and behaviour can be tested by Testify.	Yes By integrating Lettuce with Selenium’s Python bindings, you have a robust framework for testing Django applications. It can test front-end behaviour
Server-side Allows testing the bahovior of a server-side code	Yes Testify can test various server and database behaviours and functionality	Yes Lettuce can test various server and database behaviours and interactions
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	Yes Fixture methods are supported and it follows a decorator based approach, that is they are written similar to decorators	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.	Yes Group fixtures are supported	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 One can create generator methods to yield runnable test methods which will pick out the test methods from your TestCases, and then exclude any in any of your exclude_suites method.If there are any require_suites, it will then further limit itself to test methods in those suites.	Yes By using a third party library
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	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)	Yes It includes the turtle mock object library	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 Testify includes support for detecting and running test suites, grouped by modules, classes, or individual test methods.	Yes It allows grouping of tests
Other Other useful information about the testing framework