Knapsack Pro

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

Green

https://github.com/CleanCut/green

TestCafe

https://devexpress.github.io/testcafe/
Programming language

Python

JavaScript

Category

Unit Testing

End-to-End Testing, Regression 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)

TestCafe is a Node.js tool to automate end-to-end web testing.

TestCafe runs on Windows, MacOs, and Linux and supports mobile, remote and cloud browsers (UI or headless). It is also free and open source
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

TestCafe is primarily a front-end testing tool
Server-side
Allows testing the bahovior of a server-side code

Yes

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

No

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

You can create fixtures with TestCafe
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

We can mock requests with the 'RequestMock' hook
Grouping
Allows organizing tests in groups

N/A

N/A

Other
Other useful information about the testing framework