Selenium vs Spock comparison of testing frameworks
What are the differences between Selenium and Spock?

	Selenium https://pypi.org/project/selenium/	Spock http://spockframework.org/
Programming language	Python	Java
Category	Web Automation	Unit Testing
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	Spock is a testing and specification framework for Java and Groovy applications Spock has a highly expressive specification language, and due to its JUnit runner, Spock is compatible with most IDEs, build tools, and continuous integration servers.Spock is inspired from JUnit, RSpec, jMock, Mockito, Groovy, Scala, Vulcans among others
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 It is primarily a browser automation tool which tests front-end components and functionality	Yes Spock tests front-end components and functionality by unit testing individual classes and functions
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 Spock tests back-end components and functionality by unit testing individual classes and functions
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 Spock contains four methods for setting up environments :setup() (run before every feature method), cleanup() (run after every feature method), setupSpec() (run before the first feature method), cleanupSpec() (run after the last feature 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 One can group fixtures if accessing Pytest's fixture model	Yes You can use the fixture methods to setup environments for groups 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 By using a library such as Faker or Fake-factory	N/A
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	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)	Yes It includes support for mocking	Yes Spock has inbuilt mocking capabilities and has no need for external libraries
Grouping Allows organizing tests in groups	Yes By using the TestNG feature with which we can create groups and maintain them easily	Yes You can create suites manually in spock
Other Other useful information about the testing framework