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

Fuchu

https://github.com/mausch/Fuchu

stestr

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

.NET

Python

Category

Unit Testing

Unit Testing

General info

Fuchu is functional test library for F# / C# / VB.NET

Fuchu is a test library for .NET, that supports C# and VB.NET but with a special focus on F#. It draws heavily from Haskell's test-framework and HUnit.

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.
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

You can test front-end components by testing individual front-end classes and modules

Yes

Stestr being a test runner that runs unittest tests, it can test fron-tend functionality and behaviour.
Server-side
Allows testing the bahovior of a server-side code

Yes

You can test back-end components by testing individual back-end classes and modules

Yes

Stestr being a test runner that runs unittest tests, it can run back-end tests for functionality and behaviour.
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

Yes

It can do TestFixtureSetups (SetUp/TearDown), but not TestFixtureTearDowns (not unless you treat that test suite separately)

Yes

By use of a third party library like Fixture
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.

Yes

Group fixtures are available in Fuchu

By use of a third party library like Fixture
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

Yes

By using a library like test-generator
Licence
Licence type governing the use and redistribution of the software

Apache License 2.0

Apache License 2.0

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

You can create mock objects using the third party library moq

N/A

Grouping
Allows organizing tests in groups

Yes

You can organize tests in suites and give them names

N/A

Other
Other useful information about the testing framework