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

SOAtest

https://www.parasoft.com/products/soatest

Python Testify

https://github.com/Yelp/Testify
Programming language

JavaScript

Python

Category

Functional Testing, Intergration Testing

Unit Testing

General info

It's a web based service platform. Script-less REST and SOAP API testing, UI testing, load/performance, and security testing that’s easy to use.

Parasoft SOAtest brings artificial intelligence and machine learning to functional testing, to help users test applications with multiple interfaces (UI, REST & SOAP APIs, web services, microservices, and more), simplifying automated end-to-end testing (databases, MQ, JMS, EDI, or even things like Kafka). Unlike any other API testing tool, Parasoft SOAtest mitigates the cost of re-work by proactively adjusting your library of tests as services change.

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
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

SOAtest is a UI and API testing framework that tests front-end functionality by capturing user interactions directly in the browser without requiring any scripting

Yes

Front-end functionality and behaviour can be tested by Testify.
Server-side
Allows testing the bahovior of a server-side code

No

Yes

Testify can test various server and database behaviours and functionality
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

No

Yes

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

No

Yes

Group fixtures are supported
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.

No

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.
Licence
Licence type governing the use and redistribution of the software

N/A

Apache License 2.0

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)

No

Yes

It includes the turtle mock object library
Grouping
Allows organizing tests in groups

No

Yes

Testify includes support for detecting and running test suites, grouped by modules, classes, or individual test methods.
Other
Other useful information about the testing framework