def custom_eq_strategy(
pandas_dtype: pa.DataType,
strategy: st.SearchStrategy = None,
*,
value: Any,
):
return st.just(value).map(strategies.to_numpy_dtype(pandas_dtype).type)
def test_field_element_strategy(data_type, data):
"""Test strategy for generating elements in columns/indexes."""
strategy = strategies.field_element_strategy(data_type)
element = data.draw(strategy)
expected_type = strategies.to_numpy_dtype(data_type).type
assert element.dtype.type == expected_type
with pytest.raises(pa.errors.BaseStrategyOnlyError):
strategies.field_element_strategy(
data_type, strategies.pandas_dtype_strategy(data_type))
def test_pandas_dtype_strategy(data_type, data):
"""Test that series can be constructed from pandas dtype."""
strategy = strategies.pandas_dtype_strategy(data_type)
example = data.draw(strategy)
expected_type = strategies.to_numpy_dtype(data_type).type
assert example.dtype.type == expected_type
chained_strategy = strategies.pandas_dtype_strategy(data_type, strategy)
chained_example = data.draw(chained_strategy)
assert chained_example.dtype.type == expected_type
def test_check_strategy_continuous(data_type, data):
"""Test built-in check strategies can generate continuous data."""
np_dtype = strategies.to_numpy_dtype(data_type)
value = data.draw(
npst.from_dtype(
strategies.to_numpy_dtype(data_type),
allow_nan=False,
allow_infinity=False,
))
# don't overstep bounds of representation
hypothesis.assume(np.finfo(np_dtype).min < value < np.finfo(np_dtype).max)
assert data.draw(strategies.ne_strategy(data_type, value=value)) != value
assert data.draw(strategies.eq_strategy(data_type, value=value)) == value
assert (data.draw(strategies.gt_strategy(data_type, min_value=value)) >
value)
assert (data.draw(strategies.ge_strategy(data_type, min_value=value)) >=
value)
assert (data.draw(strategies.lt_strategy(data_type, max_value=value)) <
value)
assert (data.draw(strategies.le_strategy(data_type, max_value=value)) <=
value)
def test_pandas_dtype_strategy(data_type, data):
"""Test that series can be constructed from pandas dtype."""
strategy = strategies.pandas_dtype_strategy(data_type)
example = data.draw(strategy)
expected_type = strategies.to_numpy_dtype(data_type).type
if isinstance(example, pd.Timestamp):
example = example.to_numpy()
assert example.dtype.type == expected_type
chained_strategy = strategies.pandas_dtype_strategy(data_type, strategy)
chained_example = data.draw(chained_strategy)
if isinstance(chained_example, pd.Timestamp):
chained_example = chained_example.to_numpy()
assert chained_example.dtype.type == expected_type
