mirror of https://github.com/python/cpython.git
78 lines
4.0 KiB
Plaintext
78 lines
4.0 KiB
Plaintext
Writing Python Test Cases
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Skip Montanaro
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If you add a new module to Python or modify the functionality of an existing
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module, it is your responsibility to write one or more test cases to test
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that new functionality. The mechanics of the test system are fairly
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straightforward. If you are writing test cases for module zyzzyx, you need
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to create a file in .../Lib/test named test_zyzzyx.py and an expected output
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file in .../Lib/test/output named test_zyzzyx ("..." represents the
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top-level directory in the Python source tree, the directory containing the
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configure script). Generate the initial version of the test output file by
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executing:
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cd .../Lib/test
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python regrtest.py -g test_zyzzyx.py
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Any time you modify test_zyzzyx.py you need to generate a new expected
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output file. Don't forget to desk check the generated output to make sure
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it's really what you expected to find! To run a single test after modifying
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a module, simply run regrtest.py without the -g flag:
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cd .../Lib/test
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python regrtest.py test_zyzzyx.py
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To run the entire test suite, make the "test" target at the top level:
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cd ...
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make test
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Test cases generate output based upon computed values and branches taken in
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the code. When executed, regrtest.py compares the actual output generated
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by executing the test case with the expected output and reports success or
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failure. It stands to reason that if the actual and expected outputs are to
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match, they must not contain any machine dependencies. This means
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your test cases should not print out absolute machine addresses or floating
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point numbers with large numbers of significant digits.
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Writing good test cases is a skilled task and is too complex to discuss in
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detail in this short document. Many books have been written on the subject.
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I'll show my age by suggesting that Glenford Myers' "The Art of Software
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Testing", published in 1979, is still the best introduction to the subject
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available. It is short (177 pages), easy to read, and discusses the major
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elements of software testing, though its publication predates the
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object-oriented software revolution, so doesn't cover that subject at all.
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Unfortunately, it is very expensive (about $100 new). If you can borrow it
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or find it used (around $20), I strongly urge you to pick up a copy.
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As an author of at least part of a module, you will be writing unit tests
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(isolated tests of functions and objects defined by the module) using white
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box techniques. (Unlike black box testing, where you only have the external
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interfaces to guide your test case writing, in white box testing you can see
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the code being tested and tailor your test cases to exercise it more
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completely).
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The most important goal when writing test cases is to break things. A test
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case that doesn't uncover a bug is less valuable than one that does. In
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designing test cases you should pay attention to the following:
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1. Your test cases should exercise all the functions and objects defined
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in the module, not just the ones meant to be called by users of your
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module. This may require you to write test code that uses the module
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in ways you don't expect (explicitly calling internal functions, for
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example - see test_atexit.py).
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2. You should consider any boundary values that may tickle exceptional
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conditions (e.g. if you were testing a division module you might well
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want to generate tests with numerators and denominators at the limits
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of floating point and integer numbers on the machine performing the
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tests as well as a denominator of zero).
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3. You should exercise as many paths through the code as possible. This
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may not always be possible, but is a goal to strive for. In
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particular, when considering if statements (or their equivalent), you
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want to create test cases that exercise both the true and false
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branches. For while and for statements, you should create test cases
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that exercise the loop zero, one and multiple times.
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