stestr vs Goblin comparison of testing frameworks
What are the differences between stestr and Goblin?

stestr

https://pypi.org/project/stestr/

Goblin

https://github.com/franela/goblin
Programming language

Python

Go

Category

Unit Testing

Unit Testing, Intergration Testing

General info

stestr is a Python test runner designed to execute unittest test suites

stestr executes unittest test suites by using multiple processes to split up execution of a test suite then stores a history of all test runs to help in debugging failures and optimizing the scheduler to improve speed.

Goblin is a simple Mocha like BDD testing framework for Go

Goblin was inspired by the simplicity and flexibility of NodeBDD and offers many features like the ability to define as many Describe and It blocks as you want, colorful reports and beautiful syntax, running tests with the go test command as usual and more
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

Stestr being a test runner that runs unittest tests, it can test fron-tend functionality and behaviour.

Yes

Yes, since it is a BDD driven framework, various front-end functionalities can be tested
Server-side
Allows testing the bahovior of a server-side code

Yes

Stestr being a test runner that runs unittest tests, it can run back-end tests for functionality and behaviour.

Yes

Yes back-end behaviour can be tested that is interactions with servers/databases
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

Yes

By use of a third party library like Fixture

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.

By use of a third party library like Fixture

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.

Yes

By using a library like test-generator

N/A

Licence
Licence type governing the use and redistribution of the software

Apache License 2.0

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)

N/A

N/A

Grouping
Allows organizing tests in groups

N/A

N/A

Other
Other useful information about the testing framework