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

	TwistedTrial https://twistedmatrix.com/trac/wiki/TwistedTrial	DbUnit http://dbunit.sourceforge.net/
Programming language	Python	Java
Category	Unit Testing, unittest Extensions	Unit Testing
General info	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'	Dbunit is a Junit extension for unit testing database driven programs DbUnit has the ability to export and import your database data to and from XML datasets. Since version 2.0, DbUnit can also work with very large datasets when used in streaming mode and can also help you to verify that your database data match an expected set of values
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	Yes It is a JUnit extension which is one of the most widely known members of the xUnit family
Client-side Allows testing code execution on the client, such as a web browser	Yes Front-end components can be tested for example adding a web front-end using simple twisted.web.resource.Resource objects	No
Server-side Allows testing the bahovior of a server-side code	Yes Server-side behaviour can be tested with Trial, it has various functions for this in the twisted.web.Resource package	Yes Yes its used to test database functionality
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	Yes Trial supports various fixture methods such as 'setUp()' and 'tearDown' functions fixture for normal semantics of setup, and teardown	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.	Yes Methods like 'setUp()' allow for creation of group fixtures	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.	Through use of third party libraries like test-generator.	N/A
Licence Licence type governing the use and redistribution of the software	MIT License	GNU 2.1 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 Trial can access the mock library inbuilt in python for mocking purposes	No
Grouping Allows organizing tests in groups	Yes Trial allows tests to be grouped into test packages	No
Other Other useful information about the testing framework