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