restructured a bit and added some more content...
diff --git a/Lib/test/README b/Lib/test/README
index 2cf7736..c969fcc 100644
--- a/Lib/test/README
+++ b/Lib/test/README
@@ -1,40 +1,73 @@
- Writing Python Test Cases
- -------------------------
+ Writing Python Regression Tests
+ -------------------------------
Skip Montanaro
+ (skip@mojam.com)
+
+
+Introduction
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:
+module, you should write one or more test cases to exercise that new
+functionality. The mechanics of how the test system operates are fairly
+straightforward. When a test case is run, the output is compared with the
+expected output that is stored in .../Lib/test/output. If the test runs to
+completion and the actual and expected outputs match, the test succeeds, if
+not, it fails. If an ImportError is raised, the test is not run.
- cd .../Lib/test
- python regrtest.py -g test_zyzzyx.py
+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. In particular, you will be
+able to refer to the C and Python code in the CVS repository when writing
+your regression test cases.
-Any time you modify test_zyzzyx.py you need to generate a new expected
+
+Executing Test Cases
+
+If you are writing test cases for module spam, you need to create a file
+in .../Lib/test named test_spam.py and an expected output file in
+.../Lib/test/output named test_spam ("..." represents the top-level
+directory in the Python source tree, the directory containing the configure
+script). From the top-level directory, generate the initial version of the
+test output file by executing:
+
+ ./python Lib/test/regrtest.py -g test_spam.py
+
+Any time you modify test_spam.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
+ ./python Lib/test/regrtest.py test_spam.py
+
+While debugging a regression test, you can of course execute it
+independently of the regression testing framework and see what it prints:
+
+ ./python Lib/test/test_spam.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.
+On non-Unix platforms where make may not be available, you can simply
+execute the two runs of regrtest (optimized and non-optimized) directly:
+
+ ./python Lib/test/regrtest.py
+ ./python -O Lib/test/regrtest.py
+
+
+Test cases generate output based upon values computed by the test 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 (e.g. the return value of
+the id() builtin function) or floating point numbers with large numbers of
+significant digits (unless you understand what you are doing!).
+
+
+Test Case Writing Tips
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.
@@ -46,32 +79,88 @@
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:
+case that doesn't uncover a bug is much 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).
+ * 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).
+ * You should consider any boundary values that may tickle exceptional
+ conditions (e.g. if you were writing regression tests for division,
+ 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.
+ * 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 loops, you should create test cases that exercise the
+ loop zero, one and multiple times.
+
+ * You should test with obviously invalid input. If you know that a
+ function requires an integer input, try calling it with other types of
+ objects to see how it responds.
+
+ * You should test with obviously out-of-range input. If the domain of a
+ function is only defined for positive integers, try calling it with a
+ negative integer.
+
+ * If you are going to fix a bug that wasn't uncovered by an existing
+ test, try to write a test case that exposes the bug (preferably before
+ fixing it).
+
+
+Regression Test Writing Rules
+
+Each test case is different. There is no "standard" form for a Python
+regression test case, though there are some general rules:
+
+ * If your test case detects a failure, raise TestFailed (found in
+ test_support).
+
+ * Import everything you'll need as early as possible.
+
+ * If you'll be importing objects from a module that is at least
+ partially platform-dependent, only import those objects you need for
+ the current test case to avoid spurious ImportError exceptions that
+ prevent the test from running to completion.
+
+ * Print all your test case results using the print statement. For
+ non-fatal errors, print an error message (or omit a successful
+ completion print) to indicate the failure, but proceed instead of
+ raising TestFailed.
+
+
+Miscellaneous
+
+There is a test_support module you can import from your test case. It
+provides the following useful objects:
+
+ * TestFailed - raise this exception when your regression test detects a
+ failure.
+
+ * findfile(file) - you can call this function to locate a file somewhere
+ along sys.path or in the Lib/test tree - see test_linuxaudiodev.py for
+ an example of its use.
+
+ * verbose - you can use this variable to control print output. Many
+ modules use it. Search for "verbose" in the test_*.py files to see
+ lots of examples.
+
+ * fcmp(x,y) - you can call this function to compare two floating point
+ numbers when you expect them to only be approximately equal withing a
+ fuzz factor (test_support.FUZZ, which defaults to 1e-6).
+
+Python and C statement coverage results are currently available at
+
+ http://www.musi-cal.com/~skip/python/Python/dist/src/
+
+As of this writing (July, 2000) these results are being generated nightly.
+You can refer to the summaries and the test coverage output files to see
+where coverage is adequate or lacking and write test cases to beef up the
+coverage.