def test_field_name():
assert FieldTypes.list().name == 'List'
assert FieldTypes.list(FieldTypes.int64, FieldTypes.float32).name == 'List[Int64, Float32]'
assert FieldTypes.tuple(FieldTypes.int8, ...).name == 'Tuple[Int8, ...]'
assert FieldTypes.tuple(FieldTypes.int8).name == 'Tuple[Int8, ...]'
assert FieldTypes.dict().name == 'Dict'
assert FieldTypes.dict(FieldTypes.int8, FieldTypes.float64).name == 'Dict[Int8, Float64]'
[FieldTypes.bytes, [b'abc', np.bytes_('abc')], ['abc']],
[FieldTypes.string, ['abc', np.str_('abc')], [b'abc']],
[FieldTypes.ndarray, [np.array([1, 2, 3])], [object()]],
[FieldTypes.dtype, [np.dtype(np.int32), pd.StringDtype()], [object()]],
[FieldTypes.key, [MyClass()], [object()]],
[FieldTypes.slice, [slice(1, 10), slice('a', 'b')], [object()]],
[FieldTypes.datetime, [datetime.now(), pd.Timestamp(0)], [object()]],
[FieldTypes.timedelta, [timedelta(days=1), pd.Timedelta(days=1)], [object()]],
[FieldTypes.tzinfo, [timezone.utc], [object()]],
[FieldTypes.index, [pd.RangeIndex(10), pd.Index([1, 2])], [object()]],
[FieldTypes.series, [pd.Series([1, 2, 3])], [object()]],
[FieldTypes.dataframe, [pd.DataFrame({'a': [1, 2]})], [object()]],
[FieldTypes.interval_array, [pd.arrays.IntervalArray([])], [object()]],
[FieldTypes.function, [MyClass.my_func], [object()]],
[FieldTypes.namedtuple, [my_named_tuple(a=1, b=2)], [tuple()]],
[FieldTypes.reference(MyClass), [MyClass()], [object()]],
[FieldTypes.tuple(FieldTypes.int64, ...), [tuple(), tuple([1, 2])], [list(), tuple([1, 2.])]],
[FieldTypes.list(FieldTypes.int64, FieldTypes.float64), [[1, 1.]], [tuple(), [1, 1]]],
[FieldTypes.dict(FieldTypes.string, FieldTypes.int64), [{'a': 1}], [{1: 'a'}, {'a': 1.}]],
[FieldTypes.any, [object()], []],
]
@pytest.mark.parametrize(
'field_type, valid_values, invalid_values',
fields_values
)
def test_field_type(field_type, valid_values, invalid_values):
assert isinstance(field_type.type_name, str)
assert isinstance(field_type.name, str)
def test_collction_field_error():
with pytest.raises(ValueError):
FieldTypes.tuple(FieldTypes.int64, FieldTypes.float32).validate(tuple([1, 3., 3.]))
pd.StringDtype()], [object()]],
[FieldTypes.key, [MyClass()], [object()]],
[FieldTypes.slice, [slice(1, 10), slice('a', 'b')], [object()]],
[FieldTypes.datetime, [datetime.now(), pd.Timestamp(0)], [object()]],
[
FieldTypes.timedelta, [timedelta(days=1),
pd.Timedelta(days=1)], [object()]
],
[FieldTypes.tzinfo, [timezone.utc], [object()]],
[FieldTypes.index, [pd.RangeIndex(10), pd.Index([1, 2])], [object()]],
[FieldTypes.series, [pd.Series([1, 2, 3])], [object()]],
[FieldTypes.dataframe, [pd.DataFrame({'a': [1, 2]})], [object()]],
[FieldTypes.interval_array, [pd.arrays.IntervalArray([])], [object()]],
[FieldTypes.function, [MyClass.my_func], [object()]],
[FieldTypes.namedtuple, [my_named_tuple(a=1, b=2)], [tuple()]],
[FieldTypes.reference(MyClass), [MyClass()], [object()]],
[
FieldTypes.tuple(FieldTypes.int64, ...), [tuple(),
tuple([1, 2])],
[list(), tuple([1, 2.])]
],
[
FieldTypes.list(FieldTypes.int64, FieldTypes.float64), [[1, 1.]],
[tuple(), [1, 1]]
],
[
FieldTypes.dict(FieldTypes.string, FieldTypes.int64), [{
'a': 1
}], [{
1: 'a'
}, {