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

	Crosscheck https://github.com/cross-check/cross-check	Python Testify https://github.com/Yelp/Testify
Programming language	JavaScript	Python
Category	Unit Testing	Unit Testing
General info	Crosscheck is a JavaScript unit-testing framework capable of emulating multiple browser environments Crosscheck is an open source testing framework for verifying your in-browser JavaScript. It helps you ensure that your code will run in many different browsers such as Internet Explorer, Chrome and Firefox, but without needing installations of those browsers. The only thing you need is a Java Virtual Machine.	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.	N/A	No
Client-side Allows testing code execution on the client, such as a web browser	No	Yes Front-end functionality and behaviour can be tested by Testify.
Server-side Allows testing the bahovior of a server-side code	Yes Crosscheck is used to verify in-browser JavaScript and is a headless test framework, it tests back-end components and functionality	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	N/A	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.	N/A	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.	N/A	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	N/A	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)	N/A	Yes It includes the turtle mock object library
Grouping Allows organizing tests in groups	N/A	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