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

	Green https://github.com/CleanCut/green	Lettuce https://pypi.org/project/lettuce/
Programming language	Python	Python
Category	Unit Testing	Unit Testing, Acceptance Testing
General info	Green is a clean, colorful, fast Python test runner This is a test runner that has pretty printing on output that makes results easy to read and understand. Some of its features include: Tests running in independent processes (fast), low redundancy in output (clean), supports pretty printing that is the terminal output, makes good use of color when the terminal supports it (colorful)	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 It can test front-end components of the django framework	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 It can test server-side behaviours of web applications written with Python	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	N/A	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	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.	N/A	Yes By using a third party library
Licence Licence type governing the use and redistribution of the software	MIT License	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 Through the use of Python's mock 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	N/A	Yes It allows grouping of tests
Other Other useful information about the testing framework