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

	Green https://github.com/CleanCut/green	Testify https://github.com/stretchr/testify
Programming language	Python	Go
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)	A set of golang packages that has many tools for testing Go code Testify is a Go testing framework that has some great features like easier assertions, Test suite Interfaces, and Mocks
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 Yes, since it is also easily hooked to 'testing' package it is used to test front-end components
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 Yes it can also be used to test back-end 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	N/A	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.	N/A	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.	N/A	N/A
Licence Licence type governing the use and redistribution of the software	MIT License	MIT License
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 Its 'mock' package has a mechanism for easily writing mock objects that are used in place of real objects
Grouping Allows organizing tests in groups	N/A	Yes Using the 'suite' package developers can build a test suite as a struct build teardown and setup methods as well as testing methods on the struct then run them with 'go test'
Other Other useful information about the testing framework