def test_load_spec_noparams():
spec = {
'name':
'ballet.validation.feature_acceptance.validator.AlwaysAccepter', # noqa
}
expected_class = AlwaysAccepter
cls, params = load_spec(spec)
assert cls is expected_class
def test_load_spec_params():
threshold = 0.88
spec = {
'name':
'ballet.validation.feature_acceptance.validator.RandomAccepter', # noqa
'params': {
'threshold': threshold
}
}
expected_class = RandomAccepter
cls, params = load_spec(spec)
assert cls is expected_class
assert params['threshold'] == threshold
def __init__(self, *args, agg='all', specs: List[dict] = []):
super().__init__(*args)
self._agg = agg
self._specs = specs
if not self._specs:
raise ValueError('Missing list of accepter specs!')
self.accepters = []
for spec in self._specs:
cls, params = load_spec(spec)
self.accepters.append(cls(*args, **params))
if self._agg == 'all':
self.agg = all
elif self._agg == 'any':
self.agg = any
else:
raise ValueError(
f'Unsupported value for parameter agg: {self._agg}')
def _load_validator_class_params(project: Project,
config_key: str) -> Callable:
"""Load validator class according to config_key with optional params
At the provided key, the config should show an entry in one of two forms:
1. The fully-qualified class name of the validator (str)
2. A yaml hash with the key `name` mapping to the fully-qualified class
name of the validator, and optionally, the key `params` mapping to hash
of keyword arguments to be passed to the validator class.
If `params` is provided, then they are partially applied to the
validator class ``__init__`` method such that calls to create an
instance of the validator class have the given params set as keyword
arguments.
For example, if the yaml file looks like::
foo:
bar:
validation:
feature_accepter:
name: baz.qux.MyFeatureAccepter
params:
key1: value1
Then::
make_validator = _load_validator_class_params(project, 'foo.bar.validation.feature_accepter')
would result in the following equivalence::
make_validator(arg)
baz.qux.MyFeatureAccepter(arg, key1=value1)
""" # noqa E501
spec = project.config.get(config_key)
cls, params = load_spec(spec)
return func_partial(cls, **params)
def test_load_spec_from_name(caplog):
spec = 'ballet.validation.project_structure.validator.ProjectStructureValidator' # noqa
expected_class = ProjectStructureValidator
cls, params = load_spec(spec)
assert cls is expected_class
assert isinstance(params, dict)