Seleniumhttps://pypi.org/project/selenium/ |
Python Testifyhttps://github.com/Yelp/Testify |
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Programming language | Python | Python |
Category |
Web Automation
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Unit Testing
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General info |
Selenium is an open source tool used to test web applications Selenium is a powerful testing tool which can send standard Python commands to different browsers, despite variations in browser design. It also provides extensions to emulate user interaction with browsers, a distribution server for scaling browser allocation, and the infrastructure for implementations of the W3C WebDriver specification that lets you write interchangeable code for all major web browsers |
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
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No
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Client-side
Allows testing code execution on the client, such as a web browser |
Yes It is primarily a browser automation tool which tests front-end components and functionality |
Yes Front-end functionality and behaviour can be tested by Testify. |
Server-side
Allows testing the bahovior of a server-side code |
Yes It can perform Unit tests and can test various components and behaviours in the backend using a BDD or TDD approach |
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 |
Yes By writing your Selenium WebDriver tests in PyTest, this gives you access to Pytest's powerful fixture model |
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. |
Yes One can group fixtures if accessing Pytest's fixture model |
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. |
Yes By using a library such as Faker or Fake-factory |
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 |
Apache License 2.0
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Apache License 2.0
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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 support for mocking |
Yes It includes the turtle mock object library |
Grouping
Allows organizing tests in groups |
Yes By using the TestNG feature with which we can create groups and maintain them easily |
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 |
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