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

	Specter http://specter.sourceforge.net/	Lettuce https://pypi.org/project/lettuce/
Programming language	.NET	Python
Category	Acceptance Testing	Unit Testing, Acceptance Testing
General info	Specter is a behaviour-driven development framework for .NET and Mono Specter enables behavior driven development (BDD) by allowing developers to write executable specifications for their objects, before actually implementing them, this is similar to test driven development however the different nomenclature makes it different from writing 'tests' for code that does not exist yet	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 Developers can create specfications of the expected front-end behaviours and test them	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 Yes developers can create specfications of the expected back-end behaviours and test these.	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	BSD 3-Clause 'New' or 'Revised' 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)	N/A	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 You can create your own test suites with specter	Yes It allows grouping of tests
Other Other useful information about the testing framework