pytest plugin for comparing call arguments.
Project description
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.
Project details
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