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

	HavaRunner https://github.com/havarunner/havarunner	stestr https://pypi.org/project/stestr/
Programming language	Java	Python
Category	Unit Testing	Unit Testing
General info	HavaRuner is a Java test framework with built-in concurrency support, suites and scenarios HavaRunner is a Java test framework that has built in support for concurrency and enables you to create suites. You can run the same test against multiple scenarios and speeds up development cycles with faster tests.HavaRunner is a JUnit runner, which means that it is built on top of JUnit it's fairly straightforward to adopt it in a codebase that already has JUnit tests.	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 functionality and components with havarunner	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 HavaRunner is able to test server side functions and components	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	N/A	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.	N/A	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	MIT License	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)		N/A
Grouping Allows organizing tests in groups	Yes You can group your tests by annotating them as @PartOf a suite	N/A
Other Other useful information about the testing framework