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

pytest

https://docs.pytest.org/en/latest/

Jnario

http://jnario.org/
Programming language

Python

Java

Category

Unit Testing

Acceptance Testing, Unit Testing

General info

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.

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.
xUnit
Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.

No

Yes

It is an xUnit type testing framework
Client-side
Allows testing code execution on the client, such as a web browser

Yes

pytest can test any part of the stack including front-end components

Yes

You can write scenarios to test various front-end behaviours using 'Given', 'When', 'Then' steps to describe simple scenarios
Server-side
Allows testing the bahovior of a server-side code

Yes

pytest is powerful enough to test database and server components and functionality

Yes

You can write unit tests to test server side behaviours and components using Jnario specs
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

Yes

Pytest has a powerful yet simple fixture model that is unmatched in any other testing framework.

Yes

It contains the Setup & Teardown functions similar to JUnit but less verbose
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

Pytest's powerful fixture model allows grouping of fixtures

Yes

The Setup & Teardown functions can be used as group 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

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

N/A

Licence
Licence type governing the use and redistribution of the software

MIT License

Eclipse Public License v1.0

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

By either using unittest.mock or using pytest-mock a thin wrapper that provides mock functionality for pytest

Yes

You can implement mocking through the use of a third partylibrary like Mockito
Grouping
Allows organizing tests in groups

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

Yes

Jnario Suites allows you to group multiple specifications into suites and execute them together, you do this using the suite wizard
Other
Other useful information about the testing framework