Doctesthttps://docs.Python.org/2/library/doctest.html |
Nosehttps://nose.readthedocs.io/en/latest/ |
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Programming language |
Python |
Python |
Category |
Unit Testing |
Unit Testing, unittest Extensions |
General info |
Doctest is an inbuilt test framework for PythonDoctest is a test framework that comes prepackaged with Python. It is a simple library with a functionality that makes it possible to search for pieces of text that look like interactive Python sessions and executes these sessions to see if they work exactly as shown. |
Nose is a Python unit test frameworkThis 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 |
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Yesnose 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 |
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YesNose 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 |
NoLacks fixture management which can make writing tests harder |
Yesnose 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. |
NoLacks fixture management |
YesGroup 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. |
N/A |
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 |
MIT 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) |
A good external library for using Mocks with Doctest is minimocks |
YesThe nose library extends the built-in Python unittest module therefore has access to unittest.mock |
Grouping
Allows organizing tests in groups |
YesOne can group tests |
YesWith 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 |
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