25.3. unittest
— Unit testing framework¶
(If you are already familiar with the basic concepts of testing, you might want to skip to the list of assert methods.)
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:
- test fixture
- A test fixture represents the preparation needed to perform one or more tests, and any associate cleanup actions. This may involve, for example, creating temporary or proxy databases, directories, or starting a server process.
- test case
- A test case is the smallest unit of testing. It checks for a specific
response to a particular set of inputs.
unittest
provides a base class,TestCase
, which may be used to create new test cases. - test suite
- A test suite is a collection of test cases, test suites, or both. It is used to aggregate tests that should be executed together.
- test runner
- A test runner is a component which orchestrates the execution of tests and provides the outcome to the user. The runner may use a graphical interface, a textual interface, or return a special value to indicate the results of executing the tests.
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
- Module
doctest
- Another test-support module with a very different flavor.
- unittest2: A backport of new unittest features for Python 2.4-2.6
- Many new features were added to unittest in Python 2.7, including test discovery. unittest2 allows you to use these features with earlier versions of Python.
- Simple Smalltalk Testing: With Patterns
- Kent Beck’s original paper on testing frameworks using the pattern shared
by
unittest
. - Nose and py.test
- Third-party unittest frameworks with a lighter-weight syntax for writing
tests. For example,
assert func(10) == 42
. - The Python Testing Tools Taxonomy
- An extensive list of Python testing tools including functional testing frameworks and mock object libraries.
- Testing in Python Mailing List
- A special-interest-group for discussion of testing, and testing tools, in Python.
The script Tools/unittestgui/unittestgui.py
in the Python source distribution is
a GUI tool for test discovery and execution. This is intended largely for ease of use
for those new to unit testing. For production environments it is recommended that
tests be driven by a continuous integration system such as Hudson
or Buildbot.
25.3.1. Basic example¶
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)))
# should raise an exception for an immutable sequence
self.assertRaises(TypeError, random.shuffle, (1,2,3))
def test_choice(self):
element = random.choice(self.seq)
self.assertTrue(element in self.seq)
def test_sample(self):
with self.assertRaises(ValueError):
random.sample(self.seq, 20)
for element in random.sample(self.seq, 5):
self.assertTrue(element in 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; assertTrue()
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.
25.3.2. Command-Line Interface¶
The unittest module can be used from the command line to run tests from modules, classes or even individual test methods:
python -m unittest test_module1 test_module2
python -m unittest test_module.TestClass
python -m unittest test_module.TestClass.test_method
You can pass in a list with any combination of module names, and fully qualified class or method names.
Test modules can be specified by file path as well:
python -m unittest tests/test_something.py
This allows you to use the shell filename completion to specify the test module. The file specified must still be importable as a module. The path is converted to a module name by removing the ‘.py’ and converting path separators into ‘.’. If you want to execute a test file that isn’t importable as a module you should execute the file directly instead.
You can run tests with more detail (higher verbosity) by passing in the -v flag:
python -m unittest -v test_module
When executed without arguments Test Discovery is started:
python -m unittest
For a list of all the command-line options:
python -m unittest -h
Changed in version 3.2:
Changed in version 3.2: In earlier versions it was only possible to run individual test methods and not modules or classes.
25.3.2.1. Command-line options¶
unittest supports these command-line options:
-
-b
,
--buffer
¶
The standard output and standard error streams are buffered during the test run. Output during a passing test is discarded. Output is echoed normally on test fail or error and is added to the failure messages.
-
-c
,
--catch
¶
Control-C during the test run waits for the current test to end and then reports all the results so far. A second control-C raises the normal
KeyboardInterrupt
exception.See Signal Handling for the functions that provide this functionality.
-
-f
,
--failfast
¶
Stop the test run on the first error or failure.
New in version 3.2:
New in version 3.2: The command-line options -b
, -c
and -f
were added.
The command line can also be used for test discovery, for running all of the tests in a project or just a subset.
Unittest supports simple test discovery. In order to be compatible with test discovery, all of the test files must be modules or packages importable from the top-level directory of the project (this means that their filenames must be valid identifiers).
Test discovery is implemented in TestLoader.discover()
, but can also be
used from the command line. The basic command-line usage is:
cd project_directory
python -m unittest discover
Note
As a shortcut, python -m unittest
is the equivalent of
python -m unittest discover
. If you want to pass arguments to test
discovery the discover sub-command must be used explicitly.
The discover
sub-command has the following options:
-
-v
,
--verbose
¶
Verbose output
-
-s
directory
¶ Directory to start discovery (‘.’ default)
-
-p
pattern
¶ Pattern to match test files (‘test*.py’ default)
-
-t
directory
¶ Top level directory of project (defaults to start directory)
The -s
, -p
, and -t
options can be passed in
as positional arguments in that order. The following two command lines
are equivalent:
python -m unittest discover -s project_directory -p '*_test.py'
python -m unittest discover project_directory '*_test.py'
As well as being a path it is possible to pass a package name, for example
myproject.subpackage.test
, as the start directory. The package name you
supply will then be imported and its location on the filesystem will be used
as the start directory.
Caution
Test discovery loads tests by importing them. Once test discovery has found
all the test files from the start directory you specify it turns the paths
into package names to import. For example foo/bar/baz.py
will be
imported as foo.bar.baz
.
If you have a package installed globally and attempt test discovery on a different copy of the package then the import could happen from the wrong place. If this happens test discovery will warn you and exit.
If you supply the start directory as a package name rather than a path to a directory then discover assumes that whichever location it imports from is the location you intended, so you will not get the warning.
Test modules and packages can customize test loading and discovery by through the load_tests protocol.
25.3.4. Organizing test code¶
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 unittest.TestCase
instances.
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
:
- The test module can be run standalone from the command line.
- The test code can more easily be separated from shipped code.
- There is less temptation to change test code to fit the code it tests without a good reason.
- Test code should be modified much less frequently than the code it tests.
- Tested code can be refactored more easily.
- Tests for modules written in C must be in separate modules anyway, so why not be consistent?
- If the testing strategy changes, there is no need to change the source code.
25.3.5. Re-using old test code¶
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:
-
@
unittest.
skip
(reason)¶ Unconditionally skip the decorated test. reason should describe why the test is being skipped.
-
@
unittest.
skipIf
(condition, reason)¶ Skip the decorated test if condition is true.
-
@
unittest.
skipUnless
(condition, reason)¶ Skip the decorated test unless condition is true.
-
@
unittest.
expectedFailure
¶ Mark the test as an expected failure. If the test fails when run, the test is not counted as a failure.
Skipped tests will not have setUp()
or tearDown()
run around them.
Skipped classes will not have setUpClass()
or tearDownClass()
run.
25.3.7. Classes and functions¶
This section describes in depth the API of unittest
.
25.3.7.1. Test cases¶
-
class
unittest.
TestCase
(methodName='runTest')¶ Instances of the
TestCase
class represent the smallest testable units in theunittest
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.Changed in version 3.2:
Changed in version 3.2:
TestCase
can be instantiated successfully without providing a method name. This makes it easier to experiment with TestCase from the interactive interpreter.
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:
-
setUp
()¶ Method called to prepare the test fixture. This is called immediately before calling the test method; any exception raised by this method will be considered an error rather than a test failure. The default implementation does nothing.
-
tearDown
()¶ Method called immediately after the test method has been called and the result recorded. This is called even if the test method raised an exception, so the implementation in subclasses may need to be particularly careful about checking internal state. Any exception raised by this method will be considered an error rather than a test failure. This method will only be called if the
setUp()
succeeds, regardless of the outcome of the test method. The default implementation does nothing.
-
setUpClass
()¶ A class method called before tests in an individual class run.
setUpClass
is called with the class as the only argument and must be decorated as aclassmethod()
:@classmethod def setUpClass(cls): ...
See Class and Module Fixtures for more details.
New in version 3.2:
New in version 3.2.
-
tearDownClass
()¶ A class method called after tests in an individual class have run.
tearDownClass
is called with the class as the only argument and must be decorated as aclassmethod()
:@classmethod def tearDownClass(cls): ...
See Class and Module Fixtures for more details.
New in version 3.2:
New in version 3.2.
-
run
(result=None)¶ 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 thedefaultTestResult()
method) and used. The result object is not returned torun()
‘s caller.The same effect may be had by simply calling the
TestCase
instance.
-
skipTest
(reason)¶ 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:
New in version 3.1.