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

Goconvey

https://github.com/smartystreets/goconvey

Nose

https://nose.readthedocs.io/en/latest/
Programming language

Go

Python

Category

Regression Testing, Unit Testing

Unit Testing, unittest Extensions

General info

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

Nose is a Python unit test framework

This is a Python unit test framework that intergrates well with doctests, unnittests, and 'no-boilerplate tests', that is tests written from scratch without a specific boilerplate.
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

Yes, Goconvey can perform front-end tests

Yes

nose is a unit testing tool which is very similar to unittest. It is basically unittest with extensions therefore just like unittest is can test front-end components and behaviour
Server-side
Allows testing the bahovior of a server-side code

Yes

Yes one can perform end-to-end HTTP tests with goconvey to see how an application works against remote servers

Yes

Nose can test back-end components and functionality as small units. One can write tests for each function that provides back-end functionality
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test

Yes

Yes, Goconvey uses scopes to define fixtures and a reset function for teardown

Yes

nose supports fixtures at the package, module, class, and test case levels, so that initialization which can be expensive is done as infrequently as possible.
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 define group fixtures using scopes

Yes

Group fixtures are allowed with nose, where a multitest state can be defined.
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

The web UI has a button to open the built in generator

Through use of third party libraries like test-generator and from the 'unittest.TestCase' library
Licence
Licence type governing the use and redistribution of the software

Goconvey License

GNU Library or Lesser General Public License (LGPL) (GNU LGPL)

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

Using the mock package or mockery library to autogenerate mock code

Yes

The nose library extends the built-in Python unittest module therefore has access to unittest.mock
Grouping
Allows organizing tests in groups

Yes

Similar to a table driven approach an entire suite can be contained in a single function

Yes

With nose it collects tests automatically and there’s no need to manually collect test cases into test suites.
Other
Other useful information about the testing framework