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

JDave

http://jdave.org/

Green

https://github.com/CleanCut/green
Programming language

Java

Python

Category

Acceptance Testing

Unit Testing

General info

JDave is a BDD framework for Java

JDave is inspired by RSpec and integrates JMock 2 as mocking framework and Hamcrest as matching library. It uses JUnit adapter to launch JDave specifications. This way it is possible to have IDE, build tool and coverage tool support from day one.

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)
xUnit
Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.

No

No

Client-side
Allows testing code execution on the client, such as a web browser

Yes

Front-end behaviour can be tested with JDave

Yes

It can test front-end components of the django framework
Server-side
Allows testing the bahovior of a server-side code

Yes

JDave can test server-side behaviour

Yes

It can test server-side behaviours of web applications written with Python
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

N/A

Licence
Licence type governing the use and redistribution of the software

Apache License 2.0

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)

Yes

It integrates JMock 2 as mocking framework

Yes

Through the use of Python's mock library
Grouping
Allows organizing tests in groups

Yes

Specifications can be grouped by tagging them with @Group annotation.

N/A

Other
Other useful information about the testing framework