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

	Jnario http://jnario.org/	pytest https://docs.pytest.org/en/latest/
Programming language	Java	Python
Category	Acceptance Testing, Unit Testing	Unit Testing
General info	Jnario is a test framework for Java focusing on the design and documentation aspects of testing Jnario is based on Xtend and consists of two domain-specific languages, one for writing readable acceptance tests, the other for succinct unit tests. Together they are well suited for behavior-driven development of Java programs.	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.	Yes It is an xUnit type testing framework	No
Client-side Allows testing code execution on the client, such as a web browser	Yes You can write scenarios to test various front-end behaviours using 'Given', 'When', 'Then' steps to describe simple scenarios	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 You can write unit tests to test server side behaviours and components using Jnario specs	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 It contains the Setup & Teardown functions similar to JUnit but less verbose	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 The Setup & Teardown functions can be used as 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.	N/A	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	Eclipse Public License v1.0	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)	Yes You can implement mocking through the use of a third partylibrary like Mockito	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 Jnario Suites allows you to group multiple specifications into suites and execute them together, you do this using the suite wizard	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