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

Green

https://github.com/CleanCut/green

Wallaby

https://github.com/elixir-wallaby/wallaby
Programming language

Python

Elixir

Category

Unit Testing

Intergration Testing, Browser Automation

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)

Library for end-to-end intergration testing for Elixir apps

Wallaby supports concurrent feature testing (i.e multiple tests can run concurrently) as well as browser management
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

It works well for automated E2E testing; Wallaby also has an experimental Chrome Driver that works well
Server-side
Allows testing the bahovior of a server-side code

Yes

It can test server-side behaviours of web applications written with Python

N/A
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

Available through third party libraries like Mock and Mockery
Grouping
Allows organizing tests in groups

N/A

N/A

Other
Other useful information about the testing framework