Green vs Needle comparison of testing frameworks
What are the differences between Green and Needle?

	Green https://github.com/CleanCut/green	Needle http://needle.spree.de/
Programming language	Python	Java
Category	Unit Testing	Unit Testing
General info	Green is a clean, colorful, fast Python test runner This is a test runner that has pretty printing on output that makes results easy to read and understand. Some of its features include: Tests running in independent processes (fast), low redundancy in output (clean), supports pretty printing that is the terminal output, makes good use of color when the terminal supports it (colorful)	Needle is a lightweight framework for testing Java EE components outside of the container in isolation Needle reduces the test setup code by analysing dependencies and has automatic injection of mock objects by default. Therefore It will maximize the speed of development as well as the execution of unit tests
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 It can test front-end components of the django framework	Yes You can test front-end components and functionality by testing individual front-end classes and functions
Server-side Allows testing the bahovior of a server-side code	Yes It can test server-side behaviours of web applications written with Python	Yes You can test back-end components and functionality.one of needles features is database testing via a JPA (Java Persistence API) like hibernate
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 It has setUp() and tearDown() functions which are mostly used to execute database operations
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 The setUp() and tearDown functions can be used to define an environment for a group of tests
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	N/A
Licence Licence type governing the use and redistribution of the software	MIT License	GNU Lesser General Public License v2.1
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 Through the use of Python's mock library	Yes One of needle's features is automatic injection of mock objects, it supports EasyMock and Mockito out of the box
Grouping Allows organizing tests in groups	N/A	N/A
Other Other useful information about the testing framework