pytest-compare 0.1.0

pytest plugin for comparing call arguments.

python-compare

Waht is it?

The pytest-compare helps validate method call arguments when testing python code.

pytest-compare is designed to work with assert methods. While python native variables can be easily compared, a more complicated structures sometimes do not. For example validating a pd.DataFrame will raise an exception. This is where pytest-compare comes in. It allows this kind of structures to be easily compared.

How to install

To install pytest-compare from PyPi, run the commmand:

pip install pytest-compare

Dependencies

The only dependency is pytest.

Optional dependencies

Some of the compare modules may require additional packages to be installed.

Pandas

To compare pandas module, add the pandas option to the installation:

pip install pytest-compare[pandas]

How to use

The comparation modules are design to be used with assert methods. When validating patched method call arguments

df = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})

with patch.object(ProductionClass, 'method', return_value=None) as mock_method:
    thing = ProductionClass()
    thing.method(df)

# will raise an exception
mock_method.assert_called_once_with(df)

# the correct way
mock_method.assert_called_once_with(CompareDataFrame(df))

Multiple arguments in a call

When a method is called using multiple arguments, all of them must be addresed in the test. while python native varibles can be easily compared, pytest-compare is designed to compare a more complicated structures and do custom compares.

with patch.object(ProductionClass, 'method', return_value=None) as mock_method:
    thing = ProductionClass()
    thing.method(1, "str", df1, df2)
    
# the correct way
mock_method.assert_called_once_with(1, "str", CompareDataFrame(df1), CompareDataFrame(df2))

Args and Kwargs

When validating the call, the expected values must be passed in the exact same mix of args and kwargs as when they were called.

with patch.object(ProductionClass, 'method', return_value=None) as mock_method:
    thing = ProductionClass()
    thing.method(df1, dataframe=df2)
    
# the correct way
mock_method.assert_called_once_with(CompareDataFrame(df1), dataframe=CompareDataFrame(df2))

Actual and Expected convention

• actual: The values that the method was originally called with.
• expected: Test values to see if the method was called with.

For example here, arg_actual is the actual value while arg_expected is the expected value.

mock_method = Mock()

mock_method(arg_actual)
mock_method.assert_called_once_with(arg_expected)

If arg_actual is not equal to arg_expected, an exception will be raised.