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

	Selenium https://pypi.org/project/selenium/	Goconvey https://github.com/smartystreets/goconvey
Programming language	Python	Go
Category	Web Automation	Regression Testing, 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	BDD style testing framework for Go Goconvey is a two pronged testing tool consisting of a test runner that watches your code for changes, runs 'go test' and renders your results in a web browser and the second a library that allows you to write BDD-style tests with standard 'go test' functions
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 Yes, Goconvey can perform front-end tests
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 Yes one can perform end-to-end HTTP tests with goconvey to see how an application works against remote servers
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 Yes, Goconvey uses scopes to define fixtures and a reset function for teardown
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 One can define group fixtures using scopes
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 The web UI has a button to open the built in generator
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	Goconvey 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 support for mocking	Yes Using the mock package or mockery library to autogenerate mock code
Grouping Allows organizing tests in groups	Yes By using the TestNG feature with which we can create groups and maintain them easily	Yes Similar to a table driven approach an entire suite can be contained in a single function
Other Other useful information about the testing framework