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The writing and reporting of assertions in tests
==================================================
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.. _`assertfeedback`:
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.. _`assert with the assert statement`:
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.. _`assert`:
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Asserting with the `` assert `` statement
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---------------------------------------------------------
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`` pytest `` allows you to use the standard python `` assert `` for verifying
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expectations and values in Python tests. For example, you can write the
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following::
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# content of test_assert1.py
def f():
return 3
def test_function():
assert f() == 4
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to assert that your function returns a certain value. If this assertion fails
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you will see the return value of the function call:
.. code-block :: pytest
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$ pytest test_assert1.py
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=========================== test session starts ============================
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platform linux -- Python 3.x.y, pytest-4.x.y, py-1.x.y, pluggy-0.x.y
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cachedir: $PYTHON_PREFIX/.pytest_cache
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rootdir: $REGENDOC_TMPDIR
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collected 1 item
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test_assert1.py F [100%]
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================================= FAILURES =================================
______________________________ test_function _______________________________
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def test_function():
> assert f() == 4
E assert 3 == 4
E + where 3 = f()
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test_assert1.py:5: AssertionError
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========================= 1 failed in 0.12 seconds =========================
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`` pytest `` has support for showing the values of the most common subexpressions
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including calls, attributes, comparisons, and binary and unary
operators. (See :ref: `tbreportdemo` ). This allows you to use the
idiomatic python constructs without boilerplate code while not losing
introspection information.
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However, if you specify a message with the assertion like this::
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assert a % 2 == 0, "value was odd, should be even"
then no assertion introspection takes places at all and the message
will be simply shown in the traceback.
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See :ref: `assert-details` for more information on assertion introspection.
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.. _`assertraises`:
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Assertions about expected exceptions
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------------------------------------------
In order to write assertions about raised exceptions, you can use
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`` pytest.raises `` as a context manager like this::
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import pytest
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def test_zero_division():
with pytest.raises(ZeroDivisionError):
1 / 0
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and if you need to have access to the actual exception info you may use::
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def test_recursion_depth():
with pytest.raises(RuntimeError) as excinfo:
def f():
f()
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f()
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assert 'maximum recursion' in str(excinfo.value)
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`` excinfo `` is a `` ExceptionInfo `` instance, which is a wrapper around
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the actual exception raised. The main attributes of interest are
`` .type `` , `` .value `` and `` .traceback `` .
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You can pass a `` match `` keyword parameter to the context-manager to test
that a regular expression matches on the string representation of an exception
(similar to the `` TestCase.assertRaisesRegexp `` method from `` unittest `` )::
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import pytest
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def myfunc():
raise ValueError("Exception 123 raised")
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def test_match():
with pytest.raises(ValueError, match=r'.* 123 .* '):
myfunc()
The regexp parameter of the `` match `` method is matched with the `` re.search ``
function, so in the above example `` match='123' `` would have worked as
well.
There's an alternate form of the `` pytest.raises `` function where you pass
a function that will be executed with the given `` *args `` and `` **kwargs `` and
assert that the given exception is raised::
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pytest.raises(ExpectedException, func, *args, * *kwargs)
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The reporter will provide you with helpful output in case of failures such as *no
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exception* or * wrong exception*.
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Note that it is also possible to specify a "raises" argument to
`` pytest.mark.xfail `` , which checks that the test is failing in a more
specific way than just having any exception raised::
@pytest.mark.xfail(raises=IndexError)
def test_f():
f()
Using `` pytest.raises `` is likely to be better for cases where you are testing
exceptions your own code is deliberately raising, whereas using
`` @pytest.mark.xfail `` with a check function is probably better for something
like documenting unfixed bugs (where the test describes what "should" happen)
or bugs in dependencies.
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.. _`assertwarns`:
Assertions about expected warnings
-----------------------------------------
.. versionadded :: 2.8
You can check that code raises a particular warning using
:ref: `pytest.warns <warns>` .
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.. _newreport:
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Making use of context-sensitive comparisons
-------------------------------------------------
.. versionadded :: 2.0
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`` pytest `` has rich support for providing context-sensitive information
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when it encounters comparisons. For example::
# content of test_assert2.py
def test_set_comparison():
set1 = set("1308")
set2 = set("8035")
assert set1 == set2
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if you run this module:
.. code-block :: pytest
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$ pytest test_assert2.py
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=========================== test session starts ============================
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platform linux -- Python 3.x.y, pytest-4.x.y, py-1.x.y, pluggy-0.x.y
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cachedir: $PYTHON_PREFIX/.pytest_cache
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rootdir: $REGENDOC_TMPDIR
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collected 1 item
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test_assert2.py F [100%]
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================================= FAILURES =================================
___________________________ test_set_comparison ____________________________
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def test_set_comparison():
set1 = set("1308")
set2 = set("8035")
> assert set1 == set2
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E AssertionError: assert {'0', '1', '3', '8'} == {'0', '3', '5', '8'}
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E Extra items in the left set:
E '1'
E Extra items in the right set:
E '5'
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E Use -v to get the full diff
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test_assert2.py:5: AssertionError
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========================= 1 failed in 0.12 seconds =========================
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Special comparisons are done for a number of cases:
* comparing long strings: a context diff is shown
* comparing long sequences: first failing indices
* comparing dicts: different entries
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See the :ref: `reporting demo <tbreportdemo>` for many more examples.
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Defining your own explanation for failed assertions
---------------------------------------------------
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It is possible to add your own detailed explanations by implementing
the `` pytest_assertrepr_compare `` hook.
.. autofunction :: _pytest.hookspec.pytest_assertrepr_compare
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:noindex:
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As an example consider adding the following hook in a :ref: `conftest.py <conftest.py>`
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file which provides an alternative explanation for `` Foo `` objects::
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# content of conftest.py
from test_foocompare import Foo
def pytest_assertrepr_compare(op, left, right):
if isinstance(left, Foo) and isinstance(right, Foo) and op == "==":
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return ['Comparing Foo instances:',
' vals: %s != %s' % (left.val, right.val)]
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now, given this test module::
# content of test_foocompare.py
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class Foo(object):
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def __init__(self, val):
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self.val = val
def __eq__(self, other):
return self.val == other.val
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def test_compare():
f1 = Foo(1)
f2 = Foo(2)
assert f1 == f2
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you can run the test module and get the custom output defined in
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the conftest file:
.. code-block :: pytest
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$ pytest -q test_foocompare.py
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F [100%]
================================= FAILURES =================================
_______________________________ test_compare _______________________________
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def test_compare():
f1 = Foo(1)
f2 = Foo(2)
> assert f1 == f2
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E assert Comparing Foo instances:
E vals: 1 != 2
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test_foocompare.py:11: AssertionError
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1 failed in 0.12 seconds
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.. _assert-details:
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.. _`assert introspection`:
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Assertion introspection details
-------------------------------
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.. versionadded :: 2.1
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Reporting details about a failing assertion is achieved by rewriting assert
statements before they are run. Rewritten assert statements put introspection
information into the assertion failure message. `` pytest `` only rewrites test
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modules directly discovered by its test collection process, so **asserts in
supporting modules which are not themselves test modules will not be rewritten**.
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You can manually enable assertion rewriting for an imported module by calling
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`register_assert_rewrite <https://docs.pytest.org/en/latest/writing_plugins.html#assertion-rewriting> `_
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before you import it (a good place to do that is in your root `` conftest.py `` ).
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For further information, Benjamin Peterson wrote up `Behind the scenes of pytest's new assertion rewriting <http://pybites.blogspot.com/2011/07/behind-scenes-of-pytests-new-assertion.html> `_ .
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Assertion rewriting caches files on disk
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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`` pytest `` will write back the rewritten modules to disk for caching. You can disable
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this behavior (for example to avoid leaving stale `` .pyc `` files around in projects that
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move files around a lot) by adding this to the top of your `` conftest.py `` file:
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.. code-block :: python
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import sys
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sys.dont_write_bytecode = True
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Note that you still get the benefits of assertion introspection, the only change is that
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the `` .pyc `` files won't be cached on disk.
Additionally, rewriting will silently skip caching if it cannot write new `` .pyc `` files,
i.e. in a read-only filesystem or a zipfile.
Disabling assert rewriting
~~~~~~~~~~~~~~~~~~~~~~~~~~
`` pytest `` rewrites test modules on import by using an import
hook to write new `` pyc `` files. Most of the time this works transparently.
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However, if you are working with the import machinery yourself, the import hook may
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interfere.
If this is the case you have two options:
* Disable rewriting for a specific module by adding the string
`` PYTEST_DONT_REWRITE `` to its docstring.
* Disable rewriting for all modules by using `` --assert=plain `` .
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.. versionadded :: 2.1
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Add assert rewriting as an alternate introspection technique.
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.. versionchanged :: 2.1
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Introduce the `` --assert `` option. Deprecate `` --no-assert `` and
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`` --nomagic `` .
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.. versionchanged :: 3.0
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Removes the `` --no-assert `` and `` --nomagic `` options.
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Removes the `` --assert=reinterp `` option.