How to write and report assertions in tests¶
Asserting with the assert statement¶
pytest allows you to use the standard Python assert for verifying
expectations and values in Python tests. For example, you can write the
following:
# content of test_assert1.py
def f():
return 3
def test_function():
assert f() == 4
to assert that your function returns a certain value. If this assertion fails you will see the return value of the function call:
$ pytest test_assert1.py
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-9.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 1 item
test_assert1.py F [100%]
================================= FAILURES =================================
______________________________ test_function _______________________________
def test_function():
> assert f() == 4
E assert 3 == 4
E + where 3 = f()
test_assert1.py:6: AssertionError
========================= short test summary info ==========================
FAILED test_assert1.py::test_function - assert 3 == 4
+ where 3 = f()
============================ 1 failed in 0.12s =============================
pytest has support for showing the values of the most common subexpressions
including calls, attributes, comparisons, and binary and unary
operators. (See Demo of Python failure reports with pytest). This allows you to use the
idiomatic python constructs without boilerplate code while not losing
introspection information.
If a message is specified with the assertion like this:
assert a % 2 == 0, "value was odd, should be even"
it is printed alongside the assertion introspection in the traceback.
See Assertion introspection details for more information on assertion introspection.
Assertions about approximate equality¶
When comparing floating point values (or arrays of floats), small rounding
errors are common. Instead of using assert abs(a - b) < tol or
numpy.isclose, you can use pytest.approx():
import pytest
import numpy as np
def test_floats():
assert (0.1 + 0.2) == pytest.approx(0.3)
def test_arrays():
a = np.array([1.0, 2.0, 3.0])
b = np.array([0.9999, 2.0001, 3.0])
assert a == pytest.approx(b)
pytest.approx works with scalars, lists, dictionaries, and NumPy arrays.
It also supports comparisons involving NaNs.
See pytest.approx() for details.
Assertions about expected exceptions¶
In order to write assertions about raised exceptions, you can use
pytest.raises() as a context manager like this:
import pytest
def test_zero_division():
with pytest.raises(ZeroDivisionError):
1 / 0
and if you need to have access to the actual exception info you may use:
def test_recursion_depth():
with pytest.raises(RuntimeError) as excinfo:
def f():
f()
f()
assert "maximum recursion" in str(excinfo.value)
excinfo is an ExceptionInfo instance, which is a wrapper around
the actual exception raised. The main attributes of interest are
.type, .value and .traceback.
Note that pytest.raises will match the exception type or any subclasses (like the standard except statement).
If you want to check if a block of code is raising an exact exception type, you need to check that explicitly:
def test_foo_not_implemented():
def foo():
raise NotImplementedError
with pytest.raises(RuntimeError) as excinfo:
foo()
assert excinfo.type is RuntimeError
The pytest.raises() call will succeed, even though the function raises NotImplementedError, because
NotImplementedError is a subclass of RuntimeError; however the following assert statement will
catch the problem.
Matching exception messages¶
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.assertRaisesRegex method from unittest):
import pytest
def myfunc():
raise ValueError("Exception 123 raised")
def test_match():
with pytest.raises(ValueError, match=r".* 123 .*"):
myfunc()
Notes:
The
matchparameter is matched with there.search()function, so in the above examplematch='123'would have worked as well.The
matchparameter also matches against PEP-678__notes__.
Assertions about expected exception groups¶
When expecting a BaseExceptionGroup or ExceptionGroup you can use pytest.RaisesGroup:
def test_exception_in_group():
with pytest.RaisesGroup(ValueError):
raise ExceptionGroup("group msg", [ValueError("value msg")])
with pytest.RaisesGroup(ValueError, TypeError):
raise ExceptionGroup("msg", [ValueError("foo"), TypeError("bar")])
It accepts a match parameter, that checks against the group message, and a check parameter that takes an arbitrary callable which it passes the group to, and only succeeds if the callable returns True.
def test_raisesgroup_match_and_check():
with pytest.RaisesGroup(BaseException, match="my group msg"):
raise BaseExceptionGroup("my group msg", [KeyboardInterrupt()])
with pytest.RaisesGroup(
Exception, check=lambda eg: isinstance(eg.__cause__, ValueError)
):
raise ExceptionGroup("", [TypeError()]) from ValueError()
It is strict about structure and unwrapped exceptions, unlike except*, so you might want to set the flatten_subgroups and/or allow_unwrapped parameters.
def test_structure():
with pytest.RaisesGroup(pytest.RaisesGroup(ValueError)):
raise ExceptionGroup("", (ExceptionGroup("", (ValueError(),)),))
with pytest.RaisesGroup(ValueError, flatten_subgroups=True):
raise ExceptionGroup("1st group", [ExceptionGroup("2nd group", [ValueError()])])
with pytest.RaisesGroup(ValueError, allow_unwrapped=True):
raise ValueError
To specify more details about the contained exception you can use pytest.RaisesExc
def test_raises_exc():
with pytest.RaisesGroup(pytest.RaisesExc(ValueError, match="foo")):
raise ExceptionGroup("", (ValueError("foo")))
They both supply a method pytest.RaisesGroup.matches() pytest.RaisesExc.matches() if you want to do matching outside of using it as a contextmanager. This can be helpful when checking .__context__ or .__cause__.
def test_matches():
exc = ValueError()
exc_group = ExceptionGroup("", [exc])
if RaisesGroup(ValueError).matches(exc_group):
...
# helpful error is available in `.fail_reason` if it fails to match
r = RaisesExc(ValueError)
assert r.matches(e), r.fail_reason
Check the documentation on pytest.RaisesGroup and pytest.RaisesExc for more details and examples.
ExceptionInfo.group_contains()¶
Warning
This helper makes it easy to check for the presence of specific exceptions, but it is very bad for checking that the group does not contain any other exceptions. So this will pass:
class EXTREMELYBADERROR(BaseException): """This is a very bad error to miss""" def test_for_value_error(): with pytest.raises(ExceptionGroup) as excinfo: excs = [ValueError()] if very_unlucky(): excs.append(EXTREMELYBADERROR()) raise ExceptionGroup("", excs) # This passes regardless of if there's other exceptions. assert excinfo.group_contains(ValueError) # You can't simply list all exceptions you *don't* want to get here.
There is no good way of using excinfo.group_contains() to ensure you’re not getting any other exceptions than the one you expected.
You should instead use pytest.RaisesGroup, see Assertions about expected exception groups.
You can also use the excinfo.group_contains()
method to test for exceptions returned as part of an ExceptionGroup:
def test_exception_in_group():
with pytest.raises(ExceptionGroup) as excinfo:
raise ExceptionGroup(
"Group message",
[
RuntimeError("Exception 123 raised"),
],
)
assert excinfo.group_contains(RuntimeError, match=r".* 123 .*")
assert not excinfo.group_contains(TypeError)
The optional match keyword parameter works the same way as for
pytest.raises().
By default group_contains() will recursively search for a matching
exception at any level of nested ExceptionGroup instances. You can
specify a depth keyword parameter if you only want to match an
exception at a specific level; exceptions contained directly in the top
ExceptionGroup would match depth=1.
def test_exception_in_group_at_given_depth():
with pytest.raises(ExceptionGroup) as excinfo:
raise ExceptionGroup(
"Group message",
[
RuntimeError(),
ExceptionGroup(
"Nested group",
[
TypeError(),
],
),
],
)
assert excinfo.group_contains(RuntimeError, depth=1)
assert excinfo.group_contains(TypeError, depth=2)
assert not excinfo.group_contains(RuntimeError, depth=2)
assert not excinfo.group_contains(TypeError, depth=1)
Alternate pytest.raises form (legacy)¶
There is an alternate form of pytest.raises() where you pass
a function that will be executed, along with *args and **kwargs. pytest.raises()
will then execute the function with those arguments and assert that the given exception is raised:
def func(x):
if x <= 0:
raise ValueError("x needs to be larger than zero")
pytest.raises(ValueError, func, x=-1)
The reporter will provide you with helpful output in case of failures such as no exception or wrong exception.
This form was the original pytest.raises() API, developed before the with statement was
added to the Python language. Nowadays, this form is rarely used, with the context-manager form (using with)
being considered more readable.
Nonetheless, this form is fully supported and not deprecated in any way.
xfail mark and pytest.raises¶
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:
def f():
raise IndexError()
@pytest.mark.xfail(raises=IndexError)
def test_f():
f()
This will only “xfail” if the test fails by raising IndexError or subclasses.
Using pytest.mark.xfail with the
raisesparameter is probably better for something like documenting unfixed bugs (where the test describes what “should” happen) or bugs in dependencies.Using
pytest.raises()is likely to be better for cases where you are testing exceptions your own code is deliberately raising, which is the majority of cases.
You can also use pytest.RaisesGroup:
def f():
raise ExceptionGroup("", [IndexError()])
@pytest.mark.xfail(raises=RaisesGroup(IndexError))
def test_f():
f()
Assertions about expected warnings¶
You can check that code raises a particular warning using pytest.warns.
Making use of context-sensitive comparisons¶
pytest has rich support for providing context-sensitive information
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:
$ pytest test_assert2.py
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-9.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 1 item
test_assert2.py F [100%]
================================= FAILURES =================================
___________________________ test_set_comparison ____________________________
def test_set_comparison():
set1 = set("1308")
set2 = set("8035")
> assert set1 == set2
E AssertionError: assert {'0', '1', '3', '8'} == {'0', '3', '5', '8'}
E
E Extra items in the left set:
E '1'
E Extra items in the right set:
E '5'
E
E Full diff:
E {
E '0',
E + '1',
E '3',
E - '5',
E '8',
E }
test_assert2.py:4: AssertionError
========================= short test summary info ==========================
FAILED test_assert2.py::test_set_comparison - AssertionError: assert {'0', '1', '3', '8'} == {'0', '3', '5', '8'}
Extra items in the left set:
'1'
Extra items in the right set:
'5'
Full diff:
{
'0',
+ '1',
'3',
- '5',
'8',
}
============================ 1 failed in 0.12s =============================
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
See the reporting demo for many more examples.
Defining your own explanation for failed assertions¶
It is possible to add your own detailed explanations by implementing
the pytest_assertrepr_compare hook.
- pytest_assertrepr_compare(config, op, left, right)[source]
Return explanation for comparisons in failing assert expressions.
Return None for no custom explanation, otherwise return a list of strings. The strings will be joined by newlines but any newlines in a string will be escaped. Note that all but the first line will be indented slightly, the intention is for the first line to be a summary.
- Parameters:
Use in conftest plugins¶
Any conftest file can implement this hook. For a given item, only conftest files in the item’s directory and its parent directories are consulted.
As an example consider adding the following hook in a conftest.py
file 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 == "==":
return [
"Comparing Foo instances:",
f" vals: {left.val} != {right.val}",
]
now, given this test module:
# content of test_foocompare.py
class Foo:
def __init__(self, val):
self.val = val
def __eq__(self, other):
return self.val == other.val
def test_compare():
f1 = Foo(1)
f2 = Foo(2)
assert f1 == f2
you can run the test module and get the custom output defined in the conftest file:
$ pytest -q test_foocompare.py
F [100%]
================================= FAILURES =================================
_______________________________ test_compare _______________________________
def test_compare():
f1 = Foo(1)
f2 = Foo(2)
> assert f1 == f2
E assert Comparing Foo instances:
E vals: 1 != 2
test_foocompare.py:12: AssertionError
========================= short test summary info ==========================
FAILED test_foocompare.py::test_compare - assert Comparing Foo instances:
vals: 1 != 2
1 failed in 0.12s
Returning non-None value in test functions¶
A pytest.PytestReturnNotNoneWarning is emitted when a test function returns a value other than None.
This helps prevent a common mistake made by beginners who assume that returning a bool (e.g., True or False) will determine whether a test passes or fails.
Example:
@pytest.mark.parametrize(
["a", "b", "result"],
[
[1, 2, 5],
[2, 3, 8],
[5, 3, 18],
],
)
def test_foo(a, b, result):
return foo(a, b) == result # Incorrect usage, do not do this.
Since pytest ignores return values, it might be surprising that the test will never fail based on the returned value.
The correct fix is to replace the return statement with an assert:
@pytest.mark.parametrize(
["a", "b", "result"],
[
[1, 2, 5],
[2, 3, 8],
[5, 3, 18],
],
)
def test_foo(a, b, result):
assert foo(a, b) == result
Assertion introspection details¶
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
modules directly discovered by its test collection process, so asserts in
supporting modules which are not themselves test modules will not be rewritten.
You can manually enable assertion rewriting for an imported module by calling
register_assert_rewrite
before you import it (a good place to do that is in your root conftest.py).
For further information, Benjamin Peterson wrote up Behind the scenes of pytest’s new assertion rewriting.
Assertion rewriting caches files on disk¶
pytest will write back the rewritten modules to disk for caching. You can disable
this behavior (for example to avoid leaving stale .pyc files around in projects that
move files around a lot) by adding this to the top of your conftest.py file:
import sys
sys.dont_write_bytecode = True
Note that you still get the benefits of assertion introspection, the only change is that
the .pyc files won’t be cached on disk.
Additionally, rewriting will silently skip caching if it cannot write new .pyc files,
e.g. 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.
However, if you are working with the import machinery yourself, the import hook may
interfere.
If this is the case you have two options:
Disable rewriting for a specific module by adding the string
PYTEST_DONT_REWRITEto its docstring.Disable rewriting for all modules by using
--assert=plain.