Let black reformat the code...

This commit is contained in:
Kale Kundert 2018-07-31 11:23:23 -07:00
parent cd2085ee71
commit 032db159c9
No known key found for this signature in database
GPG Key ID: C6238221D17CAFAE
2 changed files with 44 additions and 29 deletions

View File

@ -31,8 +31,13 @@ def _cmp_raises_type_error(self, other):
"Comparison operators other than == and != not supported by approx objects"
)
def _non_numeric_type_error(value):
return TypeError("cannot make approximate comparisons to non-numeric values, e.g. {}".format(value))
return TypeError(
"cannot make approximate comparisons to non-numeric values, e.g. {}".format(
value
)
)
# builtin pytest.approx helper
@ -85,10 +90,10 @@ class ApproxBase(object):
"""
Raise a TypeError if the expected value is not a valid type.
"""
# This is only a concern if the expected value is a sequence. In every
# other case, the approx() function ensures that the expected value has
# a numeric type. For this reason, the default is to do nothing. The
# classes that deal with sequences should reimplement this method to
# This is only a concern if the expected value is a sequence. In every
# other case, the approx() function ensures that the expected value has
# a numeric type. For this reason, the default is to do nothing. The
# classes that deal with sequences should reimplement this method to
# raise if there are any non-numeric elements in the sequence.
pass
@ -107,10 +112,8 @@ class ApproxNumpy(ApproxBase):
else:
return f(x)
list_scalars = recursive_map(
self._approx_scalar,
self.expected.tolist())
list_scalars = recursive_map(self._approx_scalar, self.expected.tolist())
return "approx({!r})".format(list_scalars)
if sys.version_info[0] == 2:
@ -149,7 +152,7 @@ class ApproxNumpy(ApproxBase):
class ApproxMapping(ApproxBase):
"""
Perform approximate comparisons where the expected value is a mapping with
Perform approximate comparisons where the expected value is a mapping with
numeric values (the keys can be anything).
"""
@ -171,14 +174,18 @@ class ApproxMapping(ApproxBase):
def _check_type(self):
for x in self.expected.values():
if isinstance(x, type(self.expected)):
raise TypeError("pytest.approx() does not support nested dictionaries, e.g. {}".format(self.expected))
raise TypeError(
"pytest.approx() does not support nested dictionaries, e.g. {}".format(
self.expected
)
)
elif not isinstance(x, Number):
raise _non_numeric_type_error(self.expected)
class ApproxSequence(ApproxBase):
"""
Perform approximate comparisons where the expected value is a sequence of
Perform approximate comparisons where the expected value is a sequence of
numbers.
"""
@ -201,7 +208,11 @@ class ApproxSequence(ApproxBase):
def _check_type(self):
for x in self.expected:
if isinstance(x, type(self.expected)):
raise TypeError("pytest.approx() does not support nested data structures, e.g. {}".format(self.expected))
raise TypeError(
"pytest.approx() does not support nested data structures, e.g. {}".format(
self.expected
)
)
elif not isinstance(x, Number):
raise _non_numeric_type_error(self.expected)
@ -325,6 +336,7 @@ class ApproxDecimal(ApproxScalar):
"""
Perform approximate comparisons where the expected value is a decimal.
"""
DEFAULT_ABSOLUTE_TOLERANCE = Decimal("1e-12")
DEFAULT_RELATIVE_TOLERANCE = Decimal("1e-6")
@ -485,17 +497,17 @@ def approx(expected, rel=None, abs=None, nan_ok=False):
# Delegate the comparison to a class that knows how to deal with the type
# of the expected value (e.g. int, float, list, dict, numpy.array, etc).
#
# The primary responsibility of these classes is to implement ``__eq__()``
# and ``__repr__()``. The former is used to actually check if some
# "actual" value is equivalent to the given expected value within the
# allowed tolerance. The latter is used to show the user the expected
# The primary responsibility of these classes is to implement ``__eq__()``
# and ``__repr__()``. The former is used to actually check if some
# "actual" value is equivalent to the given expected value within the
# allowed tolerance. The latter is used to show the user the expected
# value and tolerance, in the case that a test failed.
#
# The actual logic for making approximate comparisons can be found in
# ApproxScalar, which is used to compare individual numbers. All of the
# other Approx classes eventually delegate to this class. The ApproxBase
# class provides some convenient methods and overloads, but isn't really
# essential.
# The actual logic for making approximate comparisons can be found in
# ApproxScalar, which is used to compare individual numbers. All of the
# other Approx classes eventually delegate to this class. The ApproxBase
# class provides some convenient methods and overloads, but isn't really
# essential.
if isinstance(expected, Decimal):
cls = ApproxDecimal

View File

@ -60,15 +60,18 @@ class TestApprox(object):
)
def test_repr_nd_array(self, plus_minus):
# Make sure that arrays of all different dimensions are repr'd
# Make sure that arrays of all different dimensions are repr'd
# correctly.
np = pytest.importorskip("numpy")
examples = [
(np.array(5.), 'approx(5.0 {pm} 5.0e-06)'),
(np.array([5.]), 'approx([5.0 {pm} 5.0e-06])'),
(np.array([[5.]]), 'approx([[5.0 {pm} 5.0e-06]])'),
(np.array([[5., 6.]]), 'approx([[5.0 {pm} 5.0e-06, 6.0 {pm} 6.0e-06]])'),
(np.array([[5.], [6.]]), 'approx([[5.0 {pm} 5.0e-06], [6.0 {pm} 6.0e-06]])'),
(np.array(5.), "approx(5.0 {pm} 5.0e-06)"),
(np.array([5.]), "approx([5.0 {pm} 5.0e-06])"),
(np.array([[5.]]), "approx([[5.0 {pm} 5.0e-06]])"),
(np.array([[5., 6.]]), "approx([[5.0 {pm} 5.0e-06, 6.0 {pm} 6.0e-06]])"),
(
np.array([[5.], [6.]]),
"approx([[5.0 {pm} 5.0e-06], [6.0 {pm} 6.0e-06]])",
),
]
for np_array, repr_string in examples:
assert repr(approx(np_array)) == repr_string.format(pm=plus_minus)
@ -442,7 +445,7 @@ class TestApprox(object):
)
@pytest.mark.parametrize(
'x', [None, 'string', ['string'], [[1]], {'key': 'string'}, {'key': {'key': 1}}]
"x", [None, "string", ["string"], [[1]], {"key": "string"}, {"key": {"key": 1}}]
)
def test_expected_value_type_error(self, x):
with pytest.raises(TypeError):