stestr vs fast-check comparison of testing frameworks
What are the differences between stestr and fast-check?

	stestr https://pypi.org/project/stestr/	fast-check https://github.com/dubzzz/fast-check
Programming language	Python	JavaScript
Category	Unit Testing	Unit 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.	It's a property based testing framework written in typescript Fast-check provides another way to test programs by using property testing, Property testing is a way to test functionality by automatically generating many different inputs. This means Instead of relying on hard-coded inputs and outputs, it checks characteristics of the output given the whole range of possible inputs
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	N/A
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 It can test 'units' of front-end code for functionality and behaviour
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 It is a unit testing framework in essence and can test back-end 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 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