Writing easy assertions in tests
============================================

assert with the ``assert`` statement
---------------------------------------------------------

``py.test`` allows to use the standard python ``assert`` for verifying
expectations and values in Python tests.  For example, you can write the
following in your tests::

    # content of test_assert1.py
    def f():
        return 3

    def test_function():
        assert f() == 4

to state that your object has a certain ``attribute``. In case this
assertion fails you will see the value of ``x``::

    $ py.test test_assert1.py
    =========================== test session starts ============================
    platform linux2 -- Python 2.6.5 -- pytest-2.0.0dev0
    test path 1: test_assert1.py
    
    test_assert1.py F
    
    ================================= FAILURES =================================
    ______________________________ test_function _______________________________
    
        def test_function():
    >       assert f() == 4
    E       assert 3 == 4
    E        +  where 3 = f()
    
    test_assert1.py:5: AssertionError
    ========================= 1 failed in 0.02 seconds =========================

Reporting details about the failing assertion is achieved by re-evaluating
the assert expression and recording intermediate values.

Note: 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 for this issue is reading from a file and comparing in one
line::

        assert f.read() != '...'

This might fail but when re-interpretation comes along it might pass.
You can rewrite this (and any other expression with side effects) easily, though:

        content = f.read()
        assert content != '...'

assertions about expected exceptions
------------------------------------------

In order to write assertions about raised exceptions, you can use
``py.test.raises`` as a context manager like this::

    with py.test.raises(ZeroDivisionError):
        1 / 0

and if you need to have access to the actual exception info you may use::

    with py.test.raises(RuntimeError) as excinfo:
        def f():
            f()
        f()

    # do checks related to excinfo.type, excinfo.value, excinfo.traceback

If you want to write test code that works on Python2.4 as well,
you may also use two other ways to test for an expected exception::

    py.test.raises(ExpectedException, func, *args, **kwargs)
    py.test.raises(ExpectedException, "func(*args, **kwargs)")

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*.

Making use of context-sensitive comparisons
-------------------------------------------------

.. versionadded:: 2.0

py.test has rich support for providing context-sensitive informations
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
    =========================== test session starts ============================
    platform linux2 -- Python 2.6.5 -- pytest-2.0.0dev0
    test path 1: test_assert2.py
    
    test_assert2.py F
    
    ================================= FAILURES =================================
    ___________________________ test_set_comparison ____________________________
    
        def test_set_comparison():
            set1 = set("1308")
            set2 = set("8035")
    >       assert set1 == set2
    E       assert set(['0', '1', '3', '8']) == set(['0', '3', '5', '8'])
    E         Extra items in the left set:
    E         '1'
    E         Extra items in the right set:
    E         '5'
    
    test_assert2.py:5: AssertionError
    ========================= 1 failed in 0.02 seconds =========================

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

.. 
    Defining your own comparison
    ----------------------------------------------