def __init__(
self,
filepath: str,
table_params: dict,
metadata: Union[dict, str, Metadata],
**kwargs,
):
"""Base class for validators. Not a useable,
but used to be inherited for other validators.
Args:
filepath (str): path to data to validate
table_params (dict): Parameters which define how data is validated.
Taken from config. metadata (dict): Standard metadata for the table
to validate.
"""
self.filepath = filepath
self.table_params = table_params
self.metadata = Metadata.from_infer(metadata)
self.metadata.set_col_type_category_from_types()
self.response = ValidatorResult(
result_dict=kwargs.get("result_dict"),
validator_valid_key_name=kwargs.get("validator_valid_key_name"),
)
def test_non_unique_column_names():
with pytest.raises(ValueError):
Metadata.from_infer({
"name":
"non_unique_column_test",
"columns": [
{
"name": "c1",
"type": "string"
},
{
"name": "c1",
"type": "int64"
},
],
})
def validate_and_enrich_metadata(metadata: Union[Metadata, dict]) -> Metadata:
m = Metadata.from_infer(metadata)
m = deepcopy(m)
m.set_col_type_category_from_types()
return m
def test_inferred_input_fails(fake_input):
with pytest.raises(TypeError):
Metadata.from_infer(fake_input)
def test_inferred_input_passes(monkeypatch, patch_out, fake_input):
monkeypatch.setattr(Metadata, patch_out, lambda x: True)
assert Metadata.from_infer(fake_input)
