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| * UnitTest in the standard library (http://www.python.org/doc/current/lib/module-unittest.html) | * UnitTest in the standard library (http://docs.python.org/lib/module-unittest.html) |
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| * [http://www.python.org/pypi/zope.testing zope.testing] provides a powerful test runner that supports test discovery and a wide range of options to control how tests are run and results reported. |
Software
UnitTest in the standard library (http://docs.python.org/lib/module-unittest.html)
[http://www.garethrees.org/2001/12/04/python-coverage/ StatementCoverage] This module runs your code, then produces a report on how many statements were executed, and which ones were not. Use it to ensure your unit tests test everything.
McCabe-like Python Cyclomatic Complexity analysis tools are available at http://journyx.com/curt/complexity.html. They're written in Perl, but read and analyze only Python code. Complexity is bad, this will help you simplify code - especially code you didn't write.
[http://www.python.org/pypi/zope.testing zope.testing] provides a powerful test runner that supports test discovery and a wide range of options to control how tests are run and results reported.
Best Practices
Discussion
Sprouted out by http://formencode.org/docs/DataTest/TODO.html.
What I need is a layered test system like
- test suit
- with fast/normal/detailed mode
- with known failing tests excluded
- test package to group related tests with preset parameters
- individual test
- with options like log details
- with ability to flex parameters, extend options etc.
- test utilities
- fuzzy difference
- different logging/reporting/visualization helpers
- with output capture capability