Knapsack Pro

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

Python Testify

https://github.com/Yelp/Testify

Kahlan

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

Python

PHP

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

Kahlan is a full-featured BDD testing framework

It is a full-featured BDD testing framework that embraces the KISS (Keep It Simple, Stupid) design principle. Kahlan makes it possible to write unit tests using the 'describe-it' syntax and requires at least PHP 5.5
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

Kahlan allows you to test front-end components and behaviour easily
Server-side
Allows testing the bahovior of a server-side code

Yes

Testify can test various server and database behaviours and functionality

Yes

You can test individual back-end components using Kahlan
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

Yes

Fixtures can be defined by use of 'setUp()'method and cleaned using the 'tearDown()'method
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

Yes

You can write 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

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

Yes

With Kahlan's stubbing system you are able to set stubs (like mocks) directly to your class methods (dynamic mocking)
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

Kahlan allows you to group tests syntactically using a closure syntax. It has describe and context methods for grouping
Other
Other useful information about the testing framework