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

Lettuce

https://pypi.org/project/lettuce/

Fixie

http://fixie.github.io/
Programming language

Python

.NET

Category

Unit Testing, Acceptance Testing

Unit 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

Fixie is a .NET test framework similar to NUnit and xUnit

Fixie allows test methods to be created and executed like other test frameworks, but takes a takes a conventions-based approach, which is a benefit as we do not need to use attributes to mark classes and methods as tests
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

Yes

fixie is an xUnit type testing framework
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 unit test front-end components of youra pplications with fixie
Server-side
Allows testing the bahovior of a server-side code

Yes

Lettuce can test various server and database behaviours and interactions

Yes

You can unit test back-end components of your applications with fixie
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

Yes, fixie has fixture methods for setting up tests and at the end of tests to destroy them
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.

Yes

By using a third party library

N/A

Licence
Licence type governing the use and redistribution of the software

Unknown

MIT 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)

By adding the lettuce-tools library one has access to the Mock module to implement a configurable http REST mock.

N/A

Grouping
Allows organizing tests in groups

Yes

It allows grouping of tests

Yes

You can group tests into suites
Other
Other useful information about the testing framework