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

JDave

http://jdave.org/

TwistedTrial

https://twistedmatrix.com/trac/wiki/TwistedTrial
Programming language

Java

Python

Category

Acceptance Testing

Unit Testing, unittest Extensions

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.

Trial is a unit testing framework for Python built by Twisted Matrix labs

Trial is composed of two parts: First is a command-line test runner, which can be run on plain Python unit tests and can do automated unit-test discovery across files, modules, or even arbitrarily nested packages. Second is a test library, derived from Python's 'unittest.TestCase'
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

Front-end components can be tested for example adding a web front-end using simple twisted.web.resource.Resource objects
Server-side
Allows testing the bahovior of a server-side code

Yes

JDave can test server-side behaviour

Yes

Server-side behaviour can be tested with Trial, it has various functions for this in the twisted.web.Resource package
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

Trial supports various fixture methods such as 'setUp()' and 'tearDown' functions fixture for normal semantics of setup, and teardown
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

Yes

Methods like 'setUp()' allow for creation of group fixtures
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

Through use of third party libraries like test-generator.
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

Trial can access the mock library inbuilt in python for mocking purposes
Grouping
Allows organizing tests in groups

Yes

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

Yes

Trial allows tests to be grouped into test packages
Other
Other useful information about the testing framework