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