fixtures defines a Python contract for reusable state / support logic,
primarily for unit testing. Helper and adaption logic is included to make it
easy to write your own fixtures using the fixtures contract. Glue code is
provided that makes using fixtures that meet the Fixtures contract in
unittest compatible test cases easy and straight forward.
- Python 3.8+ This is the base language fixtures is written in and for.
pbrUsed for version and release management of fixtures.
The fixtures[streams] extra adds:
testtools<https://launchpad.net/testtools>testtoolsprovides helpful glue functions for the details API used to report information about a fixture (whether its used in a testing or production environment).
For use in a unit test suite using the included glue, you will need a test
environment that supports TestCase.addCleanup. Writing your own glue code
is easy. Alternatively, you can simply use Fixtures directly without any
support code.
To run the test suite for fixtures, testtools is needed.
Standard Python unittest provides no obvious method for making and reusing
state needed in a test case other than by adding a method on the test class.
This scales poorly - complex helper functions propagating up a test class
hierarchy is a regular pattern when this is done. Mocking, while a great tool,
doesn't itself prevent this (and helpers to mock complex things can accumulate
in the same way if placed on the test class).
By defining a uniform contract where helpers have no dependency on the test
class we permit all the regular code hygiene activities to take place without
the distorting influence of being in a class hierarchy that is modelling an
entirely different thing - which is what helpers on a TestCase suffer from.
A fixture represents some state. Each fixture has attributes on it that are
specific to the fixture. For instance, a fixture representing a directory that
can be used for temporary files might have a attribute path.
Most fixtures have complete pydoc documentation, so be sure to check
pydoc fixtures for usage information.
Minimally, subclass Fixture, define _setUp to initialize your state,
schedule a cleanup for when cleanUp is called, and you're done:
>>> import unittest
>>> import fixtures
>>> class NoddyFixture(fixtures.Fixture):
... def _setUp(self):
... self.frobnozzle = 42
... self.addCleanup(delattr, self, 'frobnozzle')This will initialize frobnozzle when setUp is called, and when
cleanUp is called get rid of the frobnozzle attribute. Prior to version
1.3.0 fixtures recommended overriding setUp. This is still supported, but
since it is harder to write leak-free fixtures in this fashion, it is not
recommended.
If your fixture has diagnostic data - for instance the log file of an
application server, or log messages - it can expose that by creating a content
object (testtools.content.Content) and calling addDetail:
>>> from testtools.content import text_content
>>> class WithLog(fixtures.Fixture):
... def _setUp(self):
... self.addDetail('message', text_content('foo bar baz'))The method useFixture will use another fixture, call setUp on it, call
self.addCleanup(thefixture.cleanUp), attach any details from it and return
the fixture. This allows simple composition of different fixtures:
>>> class ReusingFixture(fixtures.Fixture):
... def _setUp(self):
... self.noddy = self.useFixture(NoddyFixture())There is a helper for adapting a function or function pair into Fixtures. It
puts the result of the function in fn_result:
>>> import os.path
>>> import shutil
>>> import tempfile
>>> def setup_function():
... return tempfile.mkdtemp()
>>> def teardown_function(fixture):
... shutil.rmtree(fixture)
>>> fixture = fixtures.FunctionFixture(setup_function, teardown_function)
>>> fixture.setUp()
>>> print (os.path.isdir(fixture.fn_result))
True
>>> fixture.cleanUp()This can be expressed even more pithily:
>>> fixture = fixtures.FunctionFixture(tempfile.mkdtemp, shutil.rmtree)
>>> fixture.setUp()
>>> print (os.path.isdir(fixture.fn_result))
True
>>> fixture.cleanUp()Another variation is MethodFixture which is useful for adapting alternate
fixture implementations to Fixture:
>>> class MyServer:
... def start(self):
... pass
... def stop(self):
... pass
>>> server = MyServer()
>>> fixture = fixtures.MethodFixture(server, server.start, server.stop)You can also combine existing fixtures using CompoundFixture:
>>> noddy_with_log = fixtures.CompoundFixture([NoddyFixture(),
... WithLog()])
>>> with noddy_with_log as x:
... print (x.fixtures[0].frobnozzle)
42The example above introduces some of the Fixture API. In order to be able
to clean up after a fixture has been used, all fixtures define a cleanUp
method which should be called when a fixture is finished with.
Because it's nice to be able to build a particular set of related fixtures in
advance of using them, fixtures also have a setUp method which should be
called before trying to use them.
One common desire with fixtures that are expensive to create is to reuse them
in many test cases; to support this the base Fixture also defines a
reset which calls self.cleanUp(); self.setUp(). Fixtures that can more
efficiently make themselves reusable should override this method. This can then
be used with multiple test state via things like testresources,
setUpClass, or setUpModule.
When using a fixture with a test you can manually call the setUp and
cleanUp methods. More convenient though is to use the included glue from
fixtures.TestWithFixtures which provides a mixin defining useFixture
(camel case because unittest is camel case throughout) method. It will call
setUp on the fixture, call self.addCleanup(fixture) to schedule a
cleanup, and return the fixture. This lets one write:
>>> import testtools
>>> import unittestNote that we use testtools.TestCase. testtools has it's own
implementation of useFixture so there is no need to use
fixtures.TestWithFixtures with testtools.TestCase:
>>> class NoddyTest(testtools.TestCase, fixtures.TestWithFixtures):
... def test_example(self):
... fixture = self.useFixture(NoddyFixture())
... self.assertEqual(42, fixture.frobnozzle)
>>> result = unittest.TestResult()
>>> _ = NoddyTest('test_example').run(result)
>>> print (result.wasSuccessful())
TrueFixtures implement the context protocol, so you can also use a fixture as a context manager:
>>> with fixtures.FunctionFixture(setup_function, teardown_function) as fixture:
... print (os.path.isdir(fixture.fn_result))
TrueWhen multiple cleanups error, fixture.cleanUp() will raise a wrapper
exception rather than choosing an arbitrary single exception to raise:
>>> import sys
>>> from fixtures.fixture import MultipleExceptions
>>> class BrokenFixture(fixtures.Fixture):
... def _setUp(self):
... self.addCleanup(lambda:1/0)
... self.addCleanup(lambda:1/0)
>>> fixture = BrokenFixture()
>>> fixture.setUp()
>>> try:
... fixture.cleanUp()
... except MultipleExceptions:
... exc_info = sys.exc_info()
>>> print (exc_info[1].args[0][0].__name__)
ZeroDivisionErrorFixtures often expose diagnostic details that can be useful for tracking down
issues. The getDetails method will return a dict of all the attached
details but can only be called before cleanUp is called. Each detail
object is an instance of testtools.content.Content:
>>> with WithLog() as l:
... print(l.getDetails()['message'].as_text())
foo bar bazThe examples above used _setUp rather than setUp because the base
class implementation of setUp acts to reduce the chance of leaking
external resources if an error is raised from _setUp. Specifically,
setUp contains a try/except block which catches all exceptions, captures
any registered detail objects, and calls self.cleanUp before propagating
the error. As long as you take care to register any cleanups before calling
the code that may fail, this will cause them to be cleaned up. The captured
detail objects are provided to the args of the raised exception.
If the error that occurred was a subclass of Exception then setUp will
raise MultipleExceptions with the last element being a SetupError that
contains the detail objects. Otherwise, to prevent causing normally
uncatchable errors like KeyboardInterrupt being caught inappropriately in
the calling layer, the original exception will be raised as-is and no
diagnostic data other than that from the original exception will be available.
A common use case within complex environments is having some fixtures shared by other ones.
Consider the case of testing using a TempDir with two fixtures built on top
of it; say a small database and a web server. Writing either one is nearly
trivial. However handling reset() correctly is hard: both the database and
web server would reasonably expect to be able to discard operating system
resources they may have open within the temporary directory before its removed.
A recursive reset() implementation would work for one, but not both.
Calling reset() on the TempDir instance between each test is probably
desirable but we don't want to have to do a complete cleanUp of the higher
layer fixtures (which would make the TempDir be unused and trivially
resettable. We have a few options available to us.
Imagine that the webserver does not depend on the DB fixture in any way - we just want the webserver and DB fixture to coexist in the same tempdir.
A simple option is to just provide an explicit dependency fixture for the higher layer fixtures to use. This pushes complexity out of the core and onto users of fixtures:
>>> class WithDep(fixtures.Fixture):
... def __init__(self, tempdir, dependency_fixture):
... super(WithDep, self).__init__()
... self.tempdir = tempdir
... self.dependency_fixture = dependency_fixture
... def setUp(self):
... super(WithDep, self).setUp()
... self.addCleanup(self.dependency_fixture.cleanUp)
... self.dependency_fixture.setUp()
... # we assume that at this point self.tempdir is usable.
>>> DB = WithDep
>>> WebServer = WithDep
>>> tempdir = fixtures.TempDir()
>>> db = DB(tempdir, tempdir)
>>> server = WebServer(tempdir, db)
>>> server.setUp()
>>> server.cleanUp()Another option is to write the fixtures to gracefully handle a dependency being reset underneath them. This is insufficient if the fixtures would block the dependency resetting (for instance by holding file locks open in a tempdir - on Windows this will prevent the directory being deleted).
Another approach which fixtures neither helps nor hinders is to raise
a signal of some sort for each user of a fixture before it is reset. In the
example here, TempDir might offer a subscribers attribute that both the
DB and web server would be registered in. Calling reset or cleanUp
on the tempdir would trigger a callback to all the subscribers; the DB and
web server reset methods would look something like:
>>> def reset(self):
... if not self._cleaned:
... self._clean()(Their action on the callback from the tempdir would be to do whatever work
was needed and set self._cleaned.) This approach has the (perhaps)
surprising effect that resetting the webserver may reset the DB - if the
webserver were to be depending on tempdir.reset as a way to reset the
webserver's state.
Another approach which is not currently implemented is to provide an object
graph of dependencies and a reset mechanism that can traverse that, along with
a separation between 'reset starting' and 'reset finishing' - the DB and
webserver would both have their reset_starting methods called, then the
tempdir would be reset, and finally the DB and webserver would have
reset_finishing called.
In addition to the Fixture, FunctionFixture and MethodFixture
classes, fixtures includes a number of pre-canned fixtures. The API docs for
fixtures will list the complete set of these, should the docs be out of date or
not to hand. For the complete feature set of each fixture please see the API
docs.
Trivial adapter to make a BytesIO (though it may in future auto-spill to
disk for large content) and expose that as a detail object, for automatic
inclusion in test failure descriptions. Very useful in combination with
MonkeyPatch:
>>> fixture = fixtures.StringStream('my-content')
>>> fixture.setUp()
>>> with fixtures.MonkeyPatch('sys.something', fixture.stream):
... pass
>>> fixture.cleanUp()This requires the fixtures[streams] extra.
Isolate your code from environmental variables, delete them or set them to a new value:
>>> fixture = fixtures.EnvironmentVariable('HOME')Isolate your code from an external logging configuration - so that your test gets the output from logged messages, but they don't go to e.g. the console:
>>> fixture = fixtures.FakeLogger()Pretend to run an external command rather than needing it to be present to run tests:
>>> from io import BytesIO
>>> fixture = fixtures.FakePopen(lambda _:{'stdout': BytesIO('foobar')})Replace or extend a logger's handlers. The behavior of this fixture depends on
the value of the nuke_handlers parameter: if true, the logger's
existing handlers are removed and replaced by the provided handler, while if
false the logger's set of handlers is extended by the provided handler:
>>> from logging import StreamHandler
>>> fixture = fixtures.LogHandler(StreamHandler())Adapts unittest.mock.patch.object to be used as a fixture:
>>> class Fred:
... value = 1
>>> fixture = fixtures.MockPatchObject(Fred, 'value', 2)
>>> with fixture:
... Fred().value
2
>>> Fred().value
1Adapts unittest.mock.patch to be used as a fixture:
>>> fixture = fixtures.MockPatch('subprocess.Popen.returncode', 3)Adapts unittest.mock.patch.multiple to be used as a fixture:
>>> fixture = fixtures.MockPatchMultiple('subprocess.Popen', returncode=3)Control the value of a named Python attribute
>>> def fake_open(path, mode):
... pass
>>> fixture = fixtures.MonkeyPatch('__builtin__.open', fake_open)Note that there are some complexities when patching methods - please see the API documentation for details.
Change the default directory that the tempfile module places temporary
files and directories in. This can be useful for containing the noise created
by code which doesn't clean up its temporary files. This does not affect
temporary file creation where an explicit containing directory was provided
>>> fixture = fixtures.NestedTempfile()Adds a single directory to the path for an existing Python package. This adds
to the package.__path__ list. If the directory is already in the path,
nothing happens, if it isn't then it is added on setUp and removed on
cleanUp:
>>> fixture = fixtures.PackagePathEntry('package/name', '/foo/bar')Creates a python package directory. Particularly useful for testing code that dynamically loads packages/modules, or for mocking out the command line entry points to Python programs:
>>> fixture = fixtures.PythonPackage('foo.bar', [('quux.py', '')])Adds a single directory to sys.path. If the directory is already in the
path, nothing happens, if it isn't then it is added on setUp and removed on
cleanUp:
>>> fixture = fixtures.PythonPathEntry('/foo/bar')Trivial adapter to expose a file-like object as a detail object, for automatic
inclusion in test failure descriptions. StringStream and BytesStream
provided concrete users of this fixture.
This requires the fixtures[streams] extra.
Trivial adapter to make a StringIO (though it may in future auto-spill to
disk for large content) and expose that as a detail object, for automatic
inclusion in test failure descriptions. Very useful in combination with
MonkeyPatch:
>>> fixture = fixtures.StringStream('stdout')
>>> fixture.setUp()
>>> with fixtures.MonkeyPatch('sys.stdout', fixture.stream):
... pass
>>> fixture.cleanUp()This requires the fixtures[streams] extra.
Create a temporary directory and clean it up later:
>>> fixture = fixtures.TempDir()The created directory is stored in the path attribute of the fixture after
setUp.
Create a temporary directory and set it as $HOME in the environment:
>>> fixture = fixtures.TempHomeDir()The created directory is stored in the path attribute of the fixture after
setUp.
The environment will now have $HOME set to the same path, and the value
will be returned to its previous value after tearDown.
Aborts if the covered code takes more than a specified number of whole wall-clock seconds.
There are two possibilities, controlled by the gentle argument: when gentle,
an exception will be raised and the test (or other covered code) will fail.
When not gentle, the entire process will be terminated, which is less clean,
but more likely to break hangs where no Python code is running.
Caution!
Only one timeout can be active at any time across all threads in a single process. Using more than one has undefined results. (This could be improved by chaining alarms.)
Note
Currently supported only on Unix because it relies on the alarm system
call.
Capture warnings for later analysis:
>>> fixture = fixtures.WarningsCapture()The captured warnings are stored in the captures attribute of the fixture
after setUp.
Configure warnings filters during test runs:
>>> fixture = fixtures.WarningsFilter(
... [
... {
... 'action': 'ignore',
... 'message': 'foo',
... 'category': DeprecationWarning,
... },
... ]
... )Order is important: entries closer to the front of the list override entries later in the list, if both match a particular warning.
Fixtures has its project homepage on GitHub <https://github.com/testing-cabal/fixtures>.
Copyright (c) 2010, Robert Collins <[email protected]>
Licensed under either the Apache License, Version 2.0 or the BSD 3-clause license at the users choice. A copy of both licenses are available in the project source as Apache-2.0 and BSD. You may not use this file except in compliance with one of these two licences.
Unless required by applicable law or agreed to in writing, software distributed under these licenses is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the license you chose for the specific language governing permissions and limitations under that license.