How to run all PyTest assertions even if some of them fail?

Question

I am looking for a way to run all of the assertions in my unit tests in PyTest, even if some of them fail. I know there must be a simple way to do this. I checked the CLi options and looked through this site for similar questions/answers but didn't see anything. Sorry if this has already been answered.

For example, consider the following code snippet, with PyTest code alongside it:

def parrot(i):
    return i

def test_parrot():
    assert parrot(0) == 0
    assert parrot(1) == 1
    assert parrot(2) == 1
    assert parrot(2) == 2

By default, the execution stops at the first failure:

$ python -m pytest fail_me.py 
=================== test session starts ===================
platform linux2 -- Python 2.7.10, pytest-2.9.1, py-1.4.31, pluggy-0.3.1
rootdir: /home/npsrt/Documents/repo/codewars, inifile: 
collected 1 items 

fail_me.py F

=================== FAILURES ===================
___________________ test_parrot ___________________

    def test_parrot():
        assert parrot(0) == 0
        assert parrot(1) == 1
>       assert parrot(2) == 1
E       assert 2 == 1
E        +  where 2 = parrot(2)

fail_me.py:7: AssertionError
=================== 1 failed in 0.05 seconds ===================

What I'd like to do is to have the code continue to execute even after PyTest encounters the first failure.

Answer 1

As others already mentioned, you'd ideally write multiple tests and only have one assertion in each (that's not a hard limit, but a good guideline).

The @pytest.mark.parametrize decorator makes this easy:

import pytest

def parrot(i):
    return i

@pytest.mark.parametrize('inp, expected', [(0, 0), (1, 1), (2, 1), (2, 2)])
def test_parrot(inp, expected):
    assert parrot(inp) == expected

When running it with -v:

parrot.py::test_parrot[0-0] PASSED
parrot.py::test_parrot[1-1] PASSED
parrot.py::test_parrot[2-1] FAILED
parrot.py::test_parrot[2-2] PASSED

=================================== FAILURES ===================================
_______________________________ test_parrot[2-1] _______________________________

inp = 2, expected = 1

    @pytest.mark.parametrize('inp, expected', [(0, 0), (1, 1), (2, 1), (2, 2)])
    def test_parrot(inp, expected):
>       assert parrot(inp) == expected
E       assert 2 == 1
E        +  where 2 = parrot(2)

parrot.py:8: AssertionError
====================== 1 failed, 3 passed in 0.01 seconds ======================

Answer 2

It ran all of your tests. You only wrote one test, and that test ran!

If you want nonfatal assertions, where a test will keep going if an assertion fails (like Google Test's EXPECT macros), try pytest-expect, which provides that functionality. Here's the example their site gives:

def test_func(expect):
    expect('a' == 'b')
    expect(1 != 1)
    a = 1
    b = 2
    expect(a == b, 'a:%s b:%s' % (a,b))

You can see that expectation failures don't stop the test, and all failed expectations get reported:

$ python -m pytest test_expect.py
================ test session starts =================
platform darwin -- Python 2.7.9 -- py-1.4.26 -- pytest-2.7.0
rootdir: /Users/okken/example, inifile: 
plugins: expect
collected 1 items 

test_expect.py F

====================== FAILURES ======================
_____________________ test_func ______________________
>    expect('a' == 'b')
test_expect.py:2
--------
>    expect(1 != 1)
test_expect.py:3
--------
>    expect(a == b, 'a:%s b:%s' % (a,b))
a:1 b:2
test_expect.py:6
--------
Failed Expectations:3
============== 1 failed in 0.01 seconds ==============

Answer 3

The pytest plugin pytest-check is a rewrite of pytest-expect (which was recommended here previously but has gone stale). It will let you do a "soft" assert like so:

An example from the GitHub repo:

import pytest_check as check

def test_example():
    a = 1
    b = 2
    c = [2, 4, 6]
    check.greater(a, b)
    check.less_equal(b, a)
    check.is_in(a, c, "Is 1 in the list")
    check.is_not_in(b, c, "make sure 2 isn't in list")

Answer 4

You should be able to control this with the --maxfail argument. I believe the default is to not stop for failures, so I'd check any py.test config files you might have for a place that's overriding it.