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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::
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$ py.test test_assert1.py
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======= test session starts ========
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platform linux -- Python 3.5.1, pytest-2.9.2, py-1.4.31, pluggy-0.3.1
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rootdir: $REGENDOC_TMPDIR, inifile:
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collected 1 items
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test_assert1.py F
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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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If you want to write test code that works on Python 2.4 as well,
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you may also use two other ways to test for an expected exception::
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pytest.raises(ExpectedException, func, *args, * *kwargs)
pytest.raises(ExpectedException, "func(*args, * *kwargs)")
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both of which execute the specified function with args and kwargs and
asserts that the given `` ExpectedException `` is raised. The reporter will
provide you with helpful output in case of failures such as *no
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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If you want to test that a regular expression matches on the string
representation of an exception (like the `` TestCase.assertRaisesRegexp `` method
from `` unittest `` ) you can use the `` ExceptionInfo.match `` method::
import pytest
def myfunc():
raise ValueError("Exception 123 raised")
def test_match():
with pytest.raises(ValueError) as excinfo:
myfunc()
excinfo.match(r'.* 123 .* ')
The regexp parameter of the `` match `` method is matched with the `` re.search ``
function. So in the above example `` excinfo.match('123') `` would have worked as
well.
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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
if you run this module::
$ py.test test_assert2.py
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======= test session starts ========
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platform linux -- Python 3.5.1, pytest-2.9.2, py-1.4.31, pluggy-0.3.1
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rootdir: $REGENDOC_TMPDIR, inifile:
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collected 1 items
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test_assert2.py F
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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 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 assertion comparison
----------------------------------------------
It is possible to add your own detailed explanations by implementing
the `` pytest_assertrepr_compare `` hook.
.. autofunction :: _pytest.hookspec.pytest_assertrepr_compare
As an example consider adding the following hook in a conftest.py which
provides an alternative explanation for `` Foo `` objects::
# 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
class Foo:
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::
$ py.test -q test_foocompare.py
F
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======= FAILURES ========
_______ test_compare ________
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def test_compare():
f1 = Foo(1)
f2 = Foo(2)
> assert f1 == f2
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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Advanced assertion introspection
----------------------------------
.. versionadded :: 2.1
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Reporting details about a failing assertion is achieved either by rewriting
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assert statements before they are run or re-evaluating the assert expression and
recording the intermediate values. Which technique is used depends on the
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location of the assert, `` pytest `` configuration, and Python version being used
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to run `` pytest `` .
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By default, `` pytest `` rewrites assert statements in test modules.
Rewritten assert statements put introspection information into the assertion failure message.
`` pytest `` only rewrites test modules directly discovered by its test collection process, so
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asserts in supporting modules which are not themselves test modules will not be
rewritten.
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.. note ::
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`` pytest `` rewrites test modules on import. It does this by using an import
hook to write a new pyc files. Most of the time this works transparently.
However, if you are messing with import yourself, the import hook may
interfere. If this is the case, simply use `` --assert=reinterp `` or
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`` --assert=plain `` . Additionally, rewriting will fail silently if it cannot
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write new pycs, i.e. in a read-only filesystem or a zipfile.
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If an assert statement has not been rewritten or the Python version is less than
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2.6, `` pytest `` falls back on assert reinterpretation. In assert
reinterpretation, `` pytest `` walks the frame of the function containing the
assert statement to discover sub-expression results of the failing assert
statement. You can force `` pytest `` to always use assertion reinterpretation by
passing the `` --assert=reinterp `` option.
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Assert reinterpretation has a caveat not present with assert rewriting: If
evaluating the assert expression has side effects you may get a warning that the
intermediate values could not be determined safely. A common example of this
issue is an assertion which reads from a file::
assert f.read() != '...'
If this assertion fails then the re-evaluation will probably succeed!
This is because `` f.read() `` will return an empty string when it is
called the second time during the re-evaluation. However, it is
easy to rewrite the assertion and avoid any trouble::
content = f.read()
assert content != '...'
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All assert introspection can be turned off by passing `` --assert=plain `` .
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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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.. 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 `` .