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