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unittest vs beanSpec comparison of testing frameworks
What are the differences between unittest and beanSpec?

unittest

https://docs.Python.org/3/library/unittest.html

beanSpec

https://sourceforge.net/p/beanspec/wiki/Home/
Programming language

Python

Java

Category

Unit Testing

Unit Testing

General info

unittest is a unit testing framework for Python

The unittest test framework is Python’s xUnit style framework. It is a standard module that is bundled with Python and supports the automation and aggregation of tests and common setup and shutdown code for them.

beanSpec is a java based testing solution that uses Behaviour Driven Development

BeanSpec is a java based testing solution that is used for specifiying, checking and summarizing the behaviour of a component in a declarative, narrative style
xUnit
Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.

Yes

unittest is a xUnit style frameworkfor Python, it was previously called PyUnit.

N/A

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

Yes

Front-end functionality and behaviour can be tested by unittest.

Yes

BeanSpec can be used to test front-end components
Server-side
Allows testing the bahovior of a server-side code

Yes

Since the webserver funtionalities have their own features and each feature has its own functions, we can write tests with unittest to test each function

Yes

BeanSpec is used to test server-side components and functionality
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

Yes

By use of the 'setUp()' function which is called to prepare the test fixture

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

unittest allows you to group your initialization code into a setUp function and clean up code in a tearDown function

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.

Yes

unittest contains generator methods in the module 'unittest.TestCase'

N/A

Licence
Licence type governing the use and redistribution of the software

MIT License

Apache License 2.0

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

Mocks are available from the library unittest.mock which allows you to replace parts of your system under test with mock objects

N/A

Grouping
Allows organizing tests in groups

Yes

One can build suites either manually or use test discovery to build the suite automatically by scanning a directory

N/A

Other
Other useful information about the testing framework