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

pytest

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

Needle

http://needle.spree.de/
Programming language

Python

Java

Category

Unit 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.

Needle is a lightweight framework for testing Java EE components outside of the container in isolation

Needle reduces the test setup code by analysing dependencies and has automatic injection of mock objects by default. Therefore It will maximize the speed of development as well as the execution of unit tests
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

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

Yes

You can test front-end components and functionality by testing individual front-end classes and functions
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 test back-end components and functionality.one of needles features is database testing via a JPA (Java Persistence API) like hibernate
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 has setUp() and tearDown() functions which are mostly used to execute database operations
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() and tearDown functions can be used to define an environment for a group of tests
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

GNU Lesser General Public License v2.1

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

One of needle's features is automatic injection of mock objects, it supports EasyMock and Mockito out of the box
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

N/A

Other
Other useful information about the testing framework