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

	TwistedTrial https://twistedmatrix.com/trac/wiki/TwistedTrial	Python Testify https://github.com/Yelp/Testify
Programming language	Python	Python
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'	A Python unit testing framework modelled after unittest Testify is modelled after unittest but has more features while still supporting unittest classes. It has more pythonic naming conventions, an better test runner output visually, a decorator-based approach to fixture methods among many other features
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 Front-end components can be tested for example adding a web front-end using simple twisted.web.resource.Resource objects	Yes Front-end functionality and behaviour can be tested by Testify.
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 Testify can test various server and database behaviours 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 Trial supports various fixture methods such as 'setUp()' and 'tearDown' functions fixture for normal semantics of setup, and teardown	Yes Fixture methods are supported and it follows a decorator based approach, that is they are written similar to decorators
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	Yes Group fixtures are supported
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.	Yes One can create generator methods to yield runnable test methods which will pick out the test methods from your TestCases, and then exclude any in any of your exclude_suites method.If there are any require_suites, it will then further limit itself to test methods in those suites.
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 Trial can access the mock library inbuilt in python for mocking purposes	Yes It includes the turtle mock object library
Grouping Allows organizing tests in groups	Yes Trial allows tests to be grouped into test packages	Yes Testify includes support for detecting and running test suites, grouped by modules, classes, or individual test methods.
Other Other useful information about the testing framework