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