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