Changed in version 3.1: Added test skipping and expected failures.
The Python unit testing framework, sometimes referred to as “PyUnit,” is a Python language version of JUnit, by Kent Beck and Erich Gamma. JUnit is, in turn, a Java version of Kent’s Smalltalk testing framework. Each is the de facto standard unit testing framework for its respective language.
unittest supports test automation, sharing of setup and shutdown code for tests, aggregation of tests into collections, and independence of the tests from the reporting framework. The unittest module provides classes that make it easy to support these qualities for a set of tests.
To achieve this, unittest supports some important concepts:
The test case and test fixture concepts are supported through the TestCase and FunctionTestCase classes; the former should be used when creating new tests, and the latter can be used when integrating existing test code with a unittest-driven framework. When building test fixtures using TestCase, the setUp() and tearDown() methods can be overridden to provide initialization and cleanup for the fixture. With FunctionTestCase, existing functions can be passed to the constructor for these purposes. When the test is run, the fixture initialization is run first; if it succeeds, the cleanup method is run after the test has been executed, regardless of the outcome of the test. Each instance of the TestCase will only be used to run a single test method, so a new fixture is created for each test.
Test suites are implemented by the TestSuite class. This class allows individual tests and test suites to be aggregated; when the suite is executed, all tests added directly to the suite and in “child” test suites are run.
A test runner is an object that provides a single method, run(), which accepts a TestCase or TestSuite object as a parameter, and returns a result object. The class TestResult is provided for use as the result object. unittest provides the TextTestRunner as an example test runner which reports test results on the standard error stream by default. Alternate runners can be implemented for other environments (such as graphical environments) without any need to derive from a specific class.
See also
The unittest module provides a rich set of tools for constructing and running tests. This section demonstrates that a small subset of the tools suffice to meet the needs of most users.
Here is a short script to test three functions from the random module:
import random
import unittest
class TestSequenceFunctions(unittest.TestCase):
def setUp(self):
self.seq = list(range(10))
def test_shuffle(self):
# make sure the shuffled sequence does not lose any elements
random.shuffle(self.seq)
self.seq.sort()
self.assertEqual(self.seq, list(range(10)))
def test_choice(self):
element = random.choice(self.seq)
self.assertIn(element, self.seq)
def test_sample(self):
self.assertRaises(ValueError, random.sample, self.seq, 20)
for element in random.sample(self.seq, 5):
self.assertIn(element, self.seq)
if __name__ == '__main__':
unittest.main()
A testcase is created by subclassing unittest.TestCase. The three individual tests are defined with methods whose names start with the letters test. This naming convention informs the test runner about which methods represent tests.
The crux of each test is a call to assertEqual() to check for an expected result; assert_() to verify a condition; or assertRaises() to verify that an expected exception gets raised. These methods are used instead of the assert statement so the test runner can accumulate all test results and produce a report.
When a setUp() method is defined, the test runner will run that method prior to each test. Likewise, if a tearDown() method is defined, the test runner will invoke that method after each test. In the example, setUp() was used to create a fresh sequence for each test.
The final block shows a simple way to run the tests. unittest.main() provides a command line interface to the test script. When run from the command line, the above script produces an output that looks like this:
...
----------------------------------------------------------------------
Ran 3 tests in 0.000s
OK
Instead of unittest.main(), there are other ways to run the tests with a finer level of control, less terse output, and no requirement to be run from the command line. For example, the last two lines may be replaced with:
suite = unittest.TestLoader().loadTestsFromTestCase(TestSequenceFunctions)
unittest.TextTestRunner(verbosity=2).run(suite)
Running the revised script from the interpreter or another script produces the following output:
test_choice (__main__.TestSequenceFunctions) ... ok
test_sample (__main__.TestSequenceFunctions) ... ok
test_shuffle (__main__.TestSequenceFunctions) ... ok
----------------------------------------------------------------------
Ran 3 tests in 0.110s
OK
The above examples show the most commonly used unittest features which are sufficient to meet many everyday testing needs. The remainder of the documentation explores the full feature set from first principles.
The basic building blocks of unit testing are test cases — single scenarios that must be set up and checked for correctness. In unittest, test cases are represented by instances of unittest‘s TestCase class. To make your own test cases you must write subclasses of TestCase, or use FunctionTestCase.
An instance of a TestCase-derived class is an object that can completely run a single test method, together with optional set-up and tidy-up code.
The testing code of a TestCase instance should be entirely self contained, such that it can be run either in isolation or in arbitrary combination with any number of other test cases.
The simplest TestCase subclass will simply override the runTest() method in order to perform specific testing code:
import unittest
class DefaultWidgetSizeTestCase(unittest.TestCase):
def runTest(self):
widget = Widget('The widget')
self.assertEqual(widget.size(), (50, 50), 'incorrect default size')
Note that in order to test something, we use the one of the assert*() methods provided by the TestCase base class. If the test fails, an exception will be raised, and unittest will identify the test case as a failure. Any other exceptions will be treated as errors. This helps you identify where the problem is: failures are caused by incorrect results - a 5 where you expected a 6. Errors are caused by incorrect code - e.g., a TypeError caused by an incorrect function call.
The way to run a test case will be described later. For now, note that to construct an instance of such a test case, we call its constructor without arguments:
testCase = DefaultWidgetSizeTestCase()
Now, such test cases can be numerous, and their set-up can be repetitive. In the above case, constructing a Widget in each of 100 Widget test case subclasses would mean unsightly duplication.
Luckily, we can factor out such set-up code by implementing a method called setUp(), which the testing framework will automatically call for us when we run the test:
import unittest
class SimpleWidgetTestCase(unittest.TestCase):
def setUp(self):
self.widget = Widget('The widget')
class DefaultWidgetSizeTestCase(SimpleWidgetTestCase):
def runTest(self):
self.assertEqual(self.widget.size(), (50,50),
'incorrect default size')
class WidgetResizeTestCase(SimpleWidgetTestCase):
def runTest(self):
self.widget.resize(100,150)
self.assertEqual(self.widget.size(), (100,150),
'wrong size after resize')
If the setUp() method raises an exception while the test is running, the framework will consider the test to have suffered an error, and the runTest() method will not be executed.
Similarly, we can provide a tearDown() method that tidies up after the runTest() method has been run:
import unittest
class SimpleWidgetTestCase(unittest.TestCase):
def setUp(self):
self.widget = Widget('The widget')
def tearDown(self):
self.widget.dispose()
self.widget = None
If setUp() succeeded, the tearDown() method will be run whether runTest() succeeded or not.
Such a working environment for the testing code is called a fixture.
Often, many small test cases will use the same fixture. In this case, we would end up subclassing SimpleWidgetTestCase into many small one-method classes such as DefaultWidgetSizeTestCase. This is time-consuming and discouraging, so in the same vein as JUnit, unittest provides a simpler mechanism:
import unittest
class WidgetTestCase(unittest.TestCase):
def setUp(self):
self.widget = Widget('The widget')
def tearDown(self):
self.widget.dispose()
self.widget = None
def test_default_size(self):
self.assertEqual(self.widget.size(), (50,50),
'incorrect default size')
def test_resize(self):
self.widget.resize(100,150)
self.assertEqual(self.widget.size(), (100,150),
'wrong size after resize')
Here we have not provided a runTest() method, but have instead provided two different test methods. Class instances will now each run one of the test_*() methods, with self.widget created and destroyed separately for each instance. When creating an instance we must specify the test method it is to run. We do this by passing the method name in the constructor:
defaultSizeTestCase = WidgetTestCase('test_default_size')
resizeTestCase = WidgetTestCase('test_resize')
Test case instances are grouped together according to the features they test. unittest provides a mechanism for this: the test suite, represented by unittest‘s TestSuite class:
widgetTestSuite = unittest.TestSuite()
widgetTestSuite.addTest(WidgetTestCase('test_default_size'))
widgetTestSuite.addTest(WidgetTestCase('test_resize'))
For the ease of running tests, as we will see later, it is a good idea to provide in each test module a callable object that returns a pre-built test suite:
def suite():
suite = unittest.TestSuite()
suite.addTest(WidgetTestCase('test_default_size'))
suite.addTest(WidgetTestCase('test_resize'))
return suite
or even:
def suite():
tests = ['test_default_size', 'test_resize']
return unittest.TestSuite(map(WidgetTestCase, tests))
Since it is a common pattern to create a TestCase subclass with many similarly named test functions, unittest provides a TestLoader class that can be used to automate the process of creating a test suite and populating it with individual tests. For example,
suite = unittest.TestLoader().loadTestsFromTestCase(WidgetTestCase)
will create a test suite that will run WidgetTestCase.test_default_size() and WidgetTestCase.test_resize. TestLoader uses the 'test' method name prefix to identify test methods automatically.
Note that the order in which the various test cases will be run is determined by sorting the test function names with respect to the built-in ordering for strings.
Often it is desirable to group suites of test cases together, so as to run tests for the whole system at once. This is easy, since TestSuite instances can be added to a TestSuite just as TestCase instances can be added to a TestSuite:
suite1 = module1.TheTestSuite()
suite2 = module2.TheTestSuite()
alltests = unittest.TestSuite([suite1, suite2])
You can place the definitions of test cases and test suites in the same modules as the code they are to test (such as widget.py), but there are several advantages to placing the test code in a separate module, such as test_widget.py:
Some users will find that they have existing test code that they would like to run from unittest, without converting every old test function to a TestCase subclass.
For this reason, unittest provides a FunctionTestCase class. This subclass of TestCase can be used to wrap an existing test function. Set-up and tear-down functions can also be provided.
Given the following test function:
def testSomething():
something = makeSomething()
assert something.name is not None
# ...
one can create an equivalent test case instance as follows:
testcase = unittest.FunctionTestCase(testSomething)
If there are additional set-up and tear-down methods that should be called as part of the test case’s operation, they can also be provided like so:
testcase = unittest.FunctionTestCase(testSomething,
setUp=makeSomethingDB,
tearDown=deleteSomethingDB)
To make migrating existing test suites easier, unittest supports tests raising AssertionError to indicate test failure. However, it is recommended that you use the explicit TestCase.fail*() and TestCase.assert*() methods instead, as future versions of unittest may treat AssertionError differently.
Note
Even though FunctionTestCase can be used to quickly convert an existing test base over to a unittest-based system, this approach is not recommended. Taking the time to set up proper TestCase subclasses will make future test refactorings infinitely easier.
In some cases, the existing tests may have been written using the doctest module. If so, doctest provides a DocTestSuite class that can automatically build unittest.TestSuite instances from the existing doctest-based tests.
Unittest supports skipping individual test methods and even whole classes of tests. In addition, it supports marking a test as a “expected failure,” a test that is broken and will fail, but shouldn’t be counted as a failure on a TestResult.
Skipping a test is simply a matter of using the skip() decorator or one of its conditional variants.
Basic skipping looks like this:
class MyTestCase(unittest.TestCase):
@unittest.skip("demonstrating skipping")
def test_nothing(self):
self.fail("shouldn't happen")
@unittest.skipIf(mylib.__version__ < (1, 3), "not supported in this library version")
def test_format(self):
# Tests that work for only a certain version of the library.
pass
@unittest.skipUnless(sys.platform.startswith("win"), "requires Windows")
def test_windows_support(self):
# windows specific testing code
pass
This is the output of running the example above in verbose mode:
test_format (__main__.MyTestCase) ... skipped 'not supported in this library version'
test_nothing (__main__.MyTestCase) ... skipped 'demonstrating skipping'
test_windows_support (__main__.MyTestCase) ... skipped 'requires Windows'
----------------------------------------------------------------------
Ran 3 tests in 0.005s
OK (skipped=3)
Classes can be skipped just like methods:
@skip("showing class skipping")
class MySkippedTestCase(unittest.TestCase):
def test_not_run(self):
pass
TestCase.setUp() can also skip the test. This is useful when a resource that needs to be set up is not available.
Expected failures use the expectedFailure() decorator.
class ExpectedFailureTestCase(unittest.TestCase):
@unittest.expectedFailure
def test_fail(self):
self.assertEqual(1, 0, "broken")
It’s easy to roll your own skipping decorators by making a decorator that calls skip() on the test when it wants it to be skipped. This decorator skips the test unless the passed object has a certain attribute:
def skipUnlessHasattr(obj, attr):
if hasattr(obj, attr):
return lambda func: func
return unittest.skip("{0!r} doesn't have {1!r}".format(obj, attr))
The following decorators implement test skipping and expected failures:
This section describes in depth the API of unittest.
Instances of the TestCase class represent the smallest testable units in the unittest universe. This class is intended to be used as a base class, with specific tests being implemented by concrete subclasses. This class implements the interface needed by the test runner to allow it to drive the test, and methods that the test code can use to check for and report various kinds of failure.
Each instance of TestCase will run a single test method: the method named methodName. If you remember, we had an earlier example that went something like this:
def suite():
suite = unittest.TestSuite()
suite.addTest(WidgetTestCase('test_default_size'))
suite.addTest(WidgetTestCase('test_resize'))
return suite
Here, we create two instances of WidgetTestCase, each of which runs a single test.
methodName defaults to runTest().
TestCase instances provide three groups of methods: one group used to run the test, another used by the test implementation to check conditions and report failures, and some inquiry methods allowing information about the test itself to be gathered.
Methods in the first group (running the test) are:
Run the test, collecting the result into the test result object passed as result. If result is omitted or None, a temporary result object is created (by calling the defaultTestResult() method) and used. The result object is not returned to run()‘s caller.
The same effect may be had by simply calling the TestCase instance.
Calling this during a test method or setUp() skips the current test. See Skipping tests and expected failures for more information.
New in version 3.1.
The test code can use any of the following methods to check for and report failures.
Signal a test failure if expr is false; the explanation for the failure will be msg if given, otherwise it will be None.
Deprecated since version 3.1: failUnless().
Test that first and second are equal. If the values do not compare equal, the test will fail with the explanation given by msg, or None. Note that using assertEqual() improves upon doing the comparison as the first parameter to assertTrue(): the default value for msg include representations of both first and second.
In addition, if first and second are the exact same type and one of list, tuple, dict, set, or frozenset or any type that a subclass registers addTypeEqualityFunc() the type specific equality function will be called in order to generate a more useful default error message.
Changed in version 3.1: Added the automatic calling of type specific equality function.
Deprecated since version 3.1: failUnlessEqual().
Test that first and second are not equal. If the values do compare equal, the test will fail with the explanation given by msg, or None. Note that using assertNotEqual() improves upon doing the comparison as the first parameter to assertTrue() is that the default value for msg can be computed to include representations of both first and second.
Deprecated since version 3.1: failIfEqual().
Test that first and second are approximately equal by computing the difference, rounding to the given number of decimal places (default 7), and comparing to zero.
Note that comparing a given number of decimal places is not the same as comparing a given number of significant digits. If the values do not compare equal, the test will fail with the explanation given by msg, or None.
Deprecated since version 3.1: failUnlessAlmostEqual().
Test that first and second are not approximately equal by computing the difference, rounding to the given number of decimal places (default 7), and comparing to zero.
Note that comparing a given number of decimal places is not the same as comparing a given number of significant digits. If the values do not compare equal, the test will fail with the explanation given by msg, or None.
Deprecated since version 3.1: failIfAlmostEqual().
Test that first is respectively >, >=, < or <= than second depending on the method name. If not, the test will fail with an explanation or with the explanation given by msg:
>>> self.assertGreaterEqual(3, 4)
AssertionError: "3" unexpectedly not greater than or equal to "4"
New in version 3.1.
Test that the multiline string first is equal to the string second. When not equal a diff of the two strings highlighting the differences will be included in the error message.
If specified msg will be used as the error message on failure.
New in version 3.1.
Verifies that a regexp search matches text. Fails with an error message including the pattern and the text. regexp may be a regular expression object or a string containing a regular expression suitable for use by re.search().
New in version 3.1.
Tests that first is or is not in second with an explanatory error message as appropriate.
If specified msg will be used as the error message on failure.
New in version 3.1.
Test that sequence expected contains the same elements as actual, regardless of their order. When they don’t, an error message listing the differences between the sequences will be generated.
Duplicate elements are ignored when comparing actual and expected. It is the equivalent of assertEqual(set(expected), set(actual)) but it works with sequences of unhashable objects as well.
If specified msg will be used as the error message on failure.
New in version 3.1.
Tests that two sets are equal. If not, an error message is constructed that lists the differences between the sets.
Fails if either of set1 or set2 does not have a set.difference() method.
If specified msg will be used as the error message on failure.
New in version 3.1.
Test that two dictionaries are equal. If not, an error message is constructed that shows the differences in the dictionaries.
If specified msg will be used as the error message on failure.
New in version 3.1.
Tests whether the key/value pairs in dictionary actual are a superset of those in expected. If not, an error message listing the missing keys and mismatched values is generated.
If specified msg will be used as the error message on failure.
New in version 3.1.
Tests that two lists or tuples are equal. If not an error message is constructed that shows only the differences between the two. An error is also raised if either of the parameters are of the wrong type.
If specified msg will be used as the error message on failure.
New in version 3.1.
Tests that two sequences are equal. If a seq_type is supplied, both seq1 and seq2 must be instances of seq_type or a failure will be raised. If the sequences are different an error message is constructed that shows the difference between the two.
If specified msg will be used as the error message on failure.
This method is used to implement assertListEqual() and assertTupleEqual().
New in version 3.1.
Test that an exception is raised when callable is called with any positional or keyword arguments that are also passed to assertRaises(). The test passes if exception is raised, is an error if another exception is raised, or fails if no exception is raised. To catch any of a group of exceptions, a tuple containing the exception classes may be passed as exception.
If only the exception argument is given, returns a context manager so that the code under test can be written inline rather than as a function:
with self.assertRaises(SomeException):
do_something()
Changed in version 3.1: Added the ability to use assertRaises() as a context manager.
Deprecated since version 3.1: failUnlessRaises().
Like assertRaises() but also tests that regexp matches on the string representation of the raised exception. regexp may be a regular expression object or a string containing a regular expression suitable for use by re.search(). Examples:
self.assertRaisesRegexp(ValueError, 'invalid literal for.*XYZ$',
int, 'XYZ')
or:
with self.assertRaisesRegexp(ValueError, 'literal'):
int('XYZ')
New in version 3.1.
This signals a test failure if expr is not None.
New in version 3.1.
The inverse of the assertIsNone() method. This signals a test failure if expr is None.
New in version 3.1.
This signals a test failure if expr1 and expr2 don’t evaluate to the same object.
New in version 3.1.
The inverse of the assertIs() method. This signals a test failure if expr1 and expr2 evaluate to the same object.
New in version 3.1.
The inverse of the assertTrue() method is the assertFalse() method. This signals a test failure if expr is true, with msg or None for the error message.
Deprecated since version 3.1: failIf().
If set to True then any explicit failure message you pass in to the assert methods will be appended to the end of the normal failure message. The normal messages contain useful information about the objects involved, for example the message from assertEqual shows you the repr of the two unequal objects. Setting this attribute to True allows you to have a custom error message in addition to the normal one.
This attribute defaults to False, meaning that a custom message passed to an assert method will silence the normal message.
The class setting can be overridden in individual tests by assigning an instance attribute to True or False before calling the assert methods.
New in version 3.1.
Testing frameworks can use the following methods to collect information on the test:
Return an instance of the test result class that should be used for this test case class (if no other result instance is provided to the run() method).
For TestCase instances, this will always be an instance of TestResult; subclasses of TestCase should override this as necessary.
Returns a description of the test, or None if no description has been provided. The default implementation of this method returns the first line of the test method’s docstring, if available, along with the method name.
Changed in version 3.1: In earlier versions this only returned the first line of the test method’s docstring, if available or the None. That led to undesirable behavior of not printing the test name when someone was thoughtful enough to write a docstring.
Registers a type specific assertEqual() equality checking function to be called by assertEqual() when both objects it has been asked to compare are exactly typeobj (not subclasses). function must take two positional arguments and a third msg=None keyword argument just as assertEqual() does. It must raise self.failureException when inequality between the first two parameters is detected.
One good use of custom equality checking functions for a type is to raise self.failureException with an error message useful for debugging the problem by explaining the inequalities in detail.
New in version 3.1.
Add a function to be called after tearDown() to cleanup resources used during the test. Functions will be called in reverse order to the order they are added (LIFO). They are called with any arguments and keyword arguments passed into addCleanup() when they are added.
If setUp() fails, meaning that tearDown() is not called, then any cleanup functions added will still be called.
New in version 3.2.
This method is called unconditionally after tearDown(), or after setUp() if setUp() raises an exception.
It is responsible for calling all the cleanup functions added by addCleanup(). If you need cleanup functions to be called prior to tearDown() then you can call doCleanups() yourself.
doCleanups() pops methods off the stack of cleanup functions one at a time, so it can be called at any time.
New in version 3.2.
This class represents an aggregation of individual tests cases and test suites. The class presents the interface needed by the test runner to allow it to be run as any other test case. Running a TestSuite instance is the same as iterating over the suite, running each test individually.
If tests is given, it must be an iterable of individual test cases or other test suites that will be used to build the suite initially. Additional methods are provided to add test cases and suites to the collection later on.
TestSuite objects behave much like TestCase objects, except they do not actually implement a test. Instead, they are used to aggregate tests into groups of tests that should be run together. Some additional methods are available to add tests to TestSuite instances:
Add all the tests from an iterable of TestCase and TestSuite instances to this test suite.
This is equivalent to iterating over tests, calling addTest() for each element.
TestSuite shares the following methods with TestCase:
Tests grouped by a TestSuite are always accessed by iteration. Subclasses can lazily provide tests by overriding __iter__(). Note that this method maybe called several times on a single suite (for example when counting tests or comparing for equality) so the tests returned must be the same for repeated iterations.
Changed in version 3.2: In earlier versions the TestSuite accessed tests directly rather than through iteration, so overriding __iter__() wasn’t sufficient for providing tests.
In the typical usage of a TestSuite object, the run() method is invoked by a TestRunner rather than by the end-user test harness.
The TestLoader class is used to create test suites from classes and modules. Normally, there is no need to create an instance of this class; the unittest module provides an instance that can be shared as unittest.defaultTestLoader. Using a subclass or instance, however, allows customization of some configurable properties.
TestLoader objects have the following methods:
Return a suite of all tests cases contained in the given module. This method searches module for classes derived from TestCase and creates an instance of the class for each test method defined for the class.
Note
While using a hierarchy of TestCase-derived classes can be convenient in sharing fixtures and helper functions, defining test methods on base classes that are not intended to be instantiated directly does not play well with this method. Doing so, however, can be useful when the fixtures are different and defined in subclasses.
Return a suite of all tests cases given a string specifier.
The specifier name is a “dotted name” that may resolve either to a module, a test case class, a test method within a test case class, a TestSuite instance, or a callable object which returns a TestCase or TestSuite instance. These checks are applied in the order listed here; that is, a method on a possible test case class will be picked up as “a test method within a test case class”, rather than “a callable object”.
For example, if you have a module SampleTests containing a TestCase-derived class SampleTestCase with three test methods (test_one(), test_two(), and test_three()), the specifier 'SampleTests.SampleTestCase' would cause this method to return a suite which will run all three test methods. Using the specifier 'SampleTests.SampleTestCase.test_two' would cause it to return a test suite which will run only the test_two() test method. The specifier can refer to modules and packages which have not been imported; they will be imported as a side-effect.
The method optionally resolves name relative to the given module.
The following attributes of a TestLoader can be configured either by subclassing or assignment on an instance:
String giving the prefix of method names which will be interpreted as test methods. The default value is 'test'.
This affects getTestCaseNames() and all the loadTestsFrom*() methods.
This class is used to compile information about which tests have succeeded and which have failed.
A TestResult object stores the results of a set of tests. The TestCase and TestSuite classes ensure that results are properly recorded; test authors do not need to worry about recording the outcome of tests.
Testing frameworks built on top of unittest may want access to the TestResult object generated by running a set of tests for reporting purposes; a TestResult instance is returned by the TestRunner.run() method for this purpose.
TestResult instances have the following attributes that will be of interest when inspecting the results of running a set of tests:
A list containing 2-tuples of TestCase instances and strings holding the reason for skipping the test.
New in version 3.1.
This method can be called to signal that the set of tests being run should be aborted by setting the shouldStop attribute to True. TestRunner objects should respect this flag and return without running any additional tests.
For example, this feature is used by the TextTestRunner class to stop the test framework when the user signals an interrupt from the keyboard. Interactive tools which provide TestRunner implementations can use this in a similar manner.
The following methods of the TestResult class are used to maintain the internal data structures, and may be extended in subclasses to support additional reporting requirements. This is particularly useful in building tools which support interactive reporting while tests are being run.
Called when the test case test is about to be run.
The default implementation simply increments the instance’s testsRun counter.
Called after the test case test has been executed, regardless of the outcome.
The default implementation does nothing.
Called once before any tests are executed.
New in version 3.2.
Called once before any tests are executed.
New in version 3.2.
Called when the test case test raises an unexpected exception err is a tuple of the form returned by sys.exc_info(): (type, value, traceback).
The default implementation appends a tuple (test, formatted_err) to the instance’s errors attribute, where formatted_err is a formatted traceback derived from err.
Called when the test case test signals a failure. err is a tuple of the form returned by sys.exc_info(): (type, value, traceback).
The default implementation appends a tuple (test, formatted_err) to the instance’s failures attribute, where formatted_err is a formatted traceback derived from err.
Called when the test case test succeeds.
The default implementation does nothing.
Called when the test case test is skipped. reason is the reason the test gave for skipping.
The default implementation appends a tuple (test, reason) to the instance’s skipped attribute.
Called when the test case test fails, but was marked with the expectedFailure() decorator.
The default implementation appends a tuple (test, formatted_err) to the instance’s expectedFailures attribute, where formatted_err is a formatted traceback derived from err.
Called when the test case test was marked with the expectedFailure() decorator, but succeeded.
The default implementation appends the test to the instance’s unexpectedSuccesses attribute.
A basic test runner implementation which prints results on standard error. It has a few configurable parameters, but is essentially very simple. Graphical applications which run test suites should provide alternate implementations.
A command-line program that runs a set of tests; this is primarily for making test modules conveniently executable. The simplest use for this function is to include the following line at the end of a test script:
if __name__ == '__main__':
unittest.main()
The testRunner argument can either be a test runner class or an already created instance of it. By default main calls sys.exit() with an exit code indicating success or failure of the tests run.
main supports being used from the interactive interpreter by passing in the argument exit=False. This displays the result on standard output without calling sys.exit():
>>> from unittest import main
>>> main(module='test_module', exit=False)
Calling main actually returns an instance of the TestProgram class. This stores the result of the tests run as the result attribute.
Changed in version 3.1: The exit parameter was added.