Typeset testing

To test a typeset we typically apply it to a collection of series and assess the type that is detected matches the one that is expected. Visions contains a collection of utility functions that can help you test your typeset. Additionally, you can reuse the extensive collection of series that visions uses internally.

The name of the series is used as identifier:

testable_series = [
    pd.Series([1,2,3], name='numeric_series'),
    pd.Series([1,2,3,np.nan], name='numeric_series_missing'),

There are currently three kind of test cases that can be automatically generated to easily test the typeset: contains, inference and conversion. The test cases are generated based on an easily defined mapping specific to the type of test.

Testing contains

Defining your own test cases for the “contains” relation requires a simple mapping from each type to a set of series identifiers. All series in the provided list of series should be included the the mapping. If not, get_contains_cases will kindly tell you which ones are missing. The example below shows a minimal example.

import pytest
from visions.test.series import get_series
from visions.test.utils import contains, get_contains_cases

# Mapping from type to series identifier
typeset = YourTypeset()

contains_map = {
    YourType1: {"int_series", "int_range",},
    YourType2: {"path_series_linux", "path_series_linux_missing", "path_series_windows"},
    YourType3: {"url_series", "url_nan_series", "url_none_series"},
    # (...)

# Generating the test cases
@pytest.mark.parametrize(**get_contains_cases(contains_map, typeset))
def test_contains(series, type, member):
    """Test the generated combinations for "series in type"

        series: the series to test
        type: the type to test against
        member: the result
    result, message = contains(series, type, member)
    assert result, message

Testing inference and conversion

For the other tests, please see visions’ tests. The directory tests/typesets/ contains visions’ own typeset tests. For instance, the CompleteSet with all default types is tested in test_complete_set.py and can be used as guiding template.