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Python Testify vs HavaRunner comparison of testing frameworks
What are the differences between Python Testify and HavaRunner?

Python Testify

https://github.com/Yelp/Testify

HavaRunner

https://github.com/havarunner/havarunner
Programming language

Python

Java

Category

Unit Testing

Unit Testing

General info

A Python unit testing framework modelled after unittest

Testify is modelled after unittest but has more features while still supporting unittest classes. It has more pythonic naming conventions, an better test runner output visually, a decorator-based approach to fixture methods among many other features

HavaRuner is a Java test framework with built-in concurrency support, suites and scenarios

HavaRunner is a Java test framework that has built in support for concurrency and enables you to create suites. You can run the same test against multiple scenarios and speeds up development cycles with faster tests.HavaRunner is a JUnit runner, which means that it is built on top of JUnit it's fairly straightforward to adopt it in a codebase that already has JUnit 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

Front-end functionality and behaviour can be tested by Testify.

Yes

You can test front-end functionality and components with havarunner
Server-side
Allows testing the bahovior of a server-side code

Yes

Testify can test various server and database behaviours and functionality

Yes

HavaRunner is able to test server side functions and components
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

Yes

Fixture methods are supported and it follows a decorator based approach, that is they are written similar to decorators

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.

Yes

Group fixtures are supported

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

One can create generator methods to yield runnable test methods which will pick out the test methods from your TestCases, and then exclude any in any of your exclude_suites method.If there are any require_suites, it will then further limit itself to test methods in those suites.

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)

Yes

It includes the turtle mock object library

Grouping
Allows organizing tests in groups

Yes

Testify includes support for detecting and running test suites, grouped by modules, classes, or individual test methods.

Yes

You can group your tests by annotating them as @PartOf a suite
Other
Other useful information about the testing framework