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
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Unit Testing, unittest Extensions
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| General info |
Doctest is an inbuilt test framework for Python Doctest 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 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. |
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xUnit
Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality. |
No
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No
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Client-side
Allows testing code execution on the client, such as a web browser |
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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 |
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Server-side
Allows testing the bahovior of a server-side code |
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Yes Nose can test back-end components and functionality as small units. One can write tests for each function that provides back-end functionality |
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Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test |
No Lacks fixture management which can make writing tests harder |
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. |
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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. |
No Lacks fixture management |
Yes Group fixtures are allowed with nose, where a multitest state can be defined. |
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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
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Through use of third party libraries like test-generator and from the 'unittest.TestCase' library |
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Licence
Licence type governing the use and redistribution of the software |
MIT License
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GNU Library or Lesser General Public License (LGPL) (GNU LGPL)
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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 |
Yes The nose library extends the built-in Python unittest module therefore has access to unittest.mock |
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Grouping
Allows organizing tests in groups |
Yes One can group tests |
Yes With nose it collects tests automatically and there’s no need to manually collect test cases into test suites. |
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Other
Other useful information about the testing framework |
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