How to do assert almost equal
with py.test for floats without resorting to something like:
assert x - 0.00001 <= y <= x + 0.00001
More specifically it will be useful to know a neat solution for quickly compare pairs of float, without unpacking them:
assert (1.32, 2.4) == i_return_tuple_of_two_floats()
I noticed that this question specifically asked about py.test. py.test 3.0 includes an approx()
function (well, really class) that is very useful for this purpose.
import pytest
assert 2.2 == pytest.approx(2.3)
# fails, default is ± 2.3e-06
assert 2.2 == pytest.approx(2.3, 0.1)
# passes
# also works the other way, in case you were worried:
assert pytest.approx(2.3, 0.1) == 2.2
# passes
The documentation is here.
You will have to specify what is "almost" for you:
assert abs(x-y) < 0.0001
to apply to tuples (or any sequence):
def almost_equal(x,y,threshold=0.0001):
return abs(x-y) < threshold
assert all(map(almost_equal, zip((1.32, 2.4), i_return_tuple_of_two_floats())
x - d <= y <= x+d
, seems like that's what OP meant as well. If you don't wish to explicitly specify the threshold for 'almost', see @jiffyclub's answer.
pytest.approx
. Writing your own approximate function is a bad idea. (The one in this answer isn't even as good as the included one.)
If you have access to NumPy it has great functions for floating point comparison that already do pairwise comparison with numpy.testing
.
Then you can do something like:
numpy.testing.assert_allclose(i_return_tuple_of_two_floats(), (1.32, 2.4))
These answers have been around for a long time, but I think the easiest and also most readable way is to use unittest for it's many nice assertions without using it for the testing structure.
Get assertions, ignore rest of unittest.TestCase
(based on this answer)
import unittest
assertions = unittest.TestCase('__init__')
Make some assertions
x = 0.00000001
assertions.assertAlmostEqual(x, 0) # pass
assertions.assertEqual(x, 0) # fail
# AssertionError: 1e-08 != 0
Implement original questions' auto-unpacking test
Just use * to unpack your return value without needing to introduce new names.
i_return_tuple_of_two_floats = lambda: (1.32, 2.4)
assertions.assertAlmostEqual(*i_return_tuple_of_two_floats()) # fail
# AssertionError: 1.32 != 2.4 within 7 places
Something like
assert round(x-y, 5) == 0
That is what unittest does
For the second part
assert all(round(x-y, 5) == 0 for x,y in zip((1.32, 2.4), i_return_tuple_of_two_floats()))
Probably better to wrap that in a function
def tuples_of_floats_are_almost_equal(X, Y):
return all(round(x-y, 5) == 0 for x,y in zip(X, Y))
assert tuples_of_floats_are_almost_equal((1.32, 2.4), i_return_tuple_of_two_floats())
If you want something that works not only with floats but for example Decimals you can use python's math.isclose():
# - rel_tol=0.01` is 1% difference tolerance.
assert math.isclose(actual_value, expected_value, rel_tol=0.01)
I'd use nose.tools. It plays well with py.test runner and have other equally useful asserts - assert_dict_equal(), assert_list_equal(), etc.
from nose.tools import assert_almost_equals
assert_almost_equals(x, y, places=7) #default is 7
Could just use round()
a, b = i_return_tuple_of_two_floats()
assert (1.32, 2.4) == round(a,2), round(b,1)
Success story sharing
assert [0.1 + 0.2, 0.2 + 0.4] == pytest.approx([0.3, 0.6])
assert {'a': 0.1+0.2} == pytest.approx({'a': 0.3})
assert [[0.1 + 0.2], [0.2 + 0.4]] == pytest.approx([[0.3], [0.6]])
leads to aTypeError
. If found that Numpy'snp.testing.assert_allclose([[0.1 + 0.2], [0.2 + 0.4]], [[0.3], [0.6]])
(see answer below) did work for this case.0.2 == pytest.approx(0.3, 0.1) # returns false; 0.2 == pytest.approx(0.3, abs=0.1) # returns true
def approx(expected, rel=None, abs=None, nan_ok: bool = False) -> ApproxBase: