StoryPlayer vs pytest comparison of testing frameworks
What are the differences between StoryPlayer and pytest?

	StoryPlayer http://datasift.github.io/storyplayer/	pytest https://docs.pytest.org/en/latest/
Programming language	PHP	Python
Category	Unit testing, Functional Testing	Unit Testing
General info	Storyplayer is a full-stack testing framework Storyplayer follows a TDD testing approach and makes it possible to write end-to-end tests for an entire platform. It has support for creating and destroying test environments on demand	Pytest is the TDD 'all in one' testing framework for Python Pytest is a powerful Python testing framework that can test all and levels of software. It is considered by many to be the best testing framework in Python with many projects on the internet having switched to it from other frameworks, including Mozilla and Dropbox. This is due to its many powerful features such as ‘assert‘ rewriting, a third-party plugin model and a powerful yet simple fixture model.
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 By running a 'user story' which is a simple statement that describes one action, and who can perform that action then record of the conversations about this action, this is how you would test front-end functionality and components	Yes pytest can test any part of the stack including front-end components
Server-side Allows testing the bahovior of a server-side code	Yes By writing a 'service story' which is a 'userstory' except it describes the behaviour of your back-end systems	Yes pytest is powerful enough to test database and server components and functionality
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	Yes Storyplayer has fixtures that can create and destroy test environments on demand	Yes Pytest has a powerful yet simple fixture model that is unmatched in any other testing framework.
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 It supports group fixtures	Yes Pytest's powerful fixture model allows grouping of fixtures
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 foreach(hostWithRole()) is a generator allows you to easily perform actions against all hosts in your test environment without having to hard-code the host IDs or hostnames into your story.	Yes pytest has a hook function called pytest_generate_tests hook which is called when collecting a test function and one can use it to generate data
Licence Licence type governing the use and redistribution of the software	New BSD 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)	By using a library like mockery which intergrates well with storyplayer	Yes By either using unittest.mock or using pytest-mock a thin wrapper that provides mock functionality for pytest
Grouping Allows organizing tests in groups	Yes Storyplayer’s job is to execute a suite of functional tests	Yes Tests can be grouped with pytest by use of markers which are applied to various tests and one can run tests with the marker applied
Other Other useful information about the testing framework