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# Array not ok
# ------------
import pytest
from pytest import approx
from _plotly_utils.basevalidators import IntegerValidator
import numpy as np
import pandas as pd
# ### Fixtures ###
@pytest.fixture()
def validator():
return IntegerValidator("prop", "parent")
@pytest.fixture
def validator_min_max():
return IntegerValidator("prop", "parent", min=-1, max=2)
@pytest.fixture
def validator_min():
return IntegerValidator("prop", "parent", min=-1)
@pytest.fixture
def validator_max():
return IntegerValidator("prop", "parent", max=2)
@pytest.fixture
def validator_aok(request):
return IntegerValidator("prop", "parent", min=-2, max=10, array_ok=True)
# ### Acceptance ###
@pytest.mark.parametrize("val", [1, -19, 0, -1234])
def test_acceptance(val, validator):
assert validator.validate_coerce(val) == val
# ### Rejection by value ###
@pytest.mark.parametrize(
"val", ["hello", (), [], [1, 2, 3], set(), "34", np.nan, np.inf, -np.inf]
)
def test_rejection_by_value(val, validator):
with pytest.raises(ValueError) as validation_failure:
validator.validate_coerce(val)
assert "Invalid value" in str(validation_failure.value)
# ### With min/max ###
# min == -1 and max == 2
@pytest.mark.parametrize("val", [0, 1, -1, 2])
def test_acceptance_min_max(val, validator_min_max):
assert validator_min_max.validate_coerce(val) == approx(val)
@pytest.mark.parametrize(
"val", [-1.01, -10, 2.1, 3, np.iinfo(np.int).max, np.iinfo(np.int).min]
)
def test_rejection_min_max(val, validator_min_max):
with pytest.raises(ValueError) as validation_failure:
validator_min_max.validate_coerce(val)
assert "in the interval [-1, 2]" in str(validation_failure.value)
# ### With min only ###
# min == -1
@pytest.mark.parametrize("val", [-1, 0, 1, 23, 99999])
def test_acceptance_min(val, validator_min):
assert validator_min.validate_coerce(val) == approx(val)
@pytest.mark.parametrize("val", [-2, -123, np.iinfo(np.int).min])
def test_rejection_min(val, validator_min):
with pytest.raises(ValueError) as validation_failure:
validator_min.validate_coerce(val)
assert "in the interval [-1, 9223372036854775807]" in str(validation_failure.value)
# ### With max only ###
# max == 2
@pytest.mark.parametrize("val", [1, 2, -10, -999999, np.iinfo(np.int32).min])
def test_acceptance_max(val, validator_max):
assert validator_max.validate_coerce(val) == approx(val)
@pytest.mark.parametrize("val", [3, 10, np.iinfo(np.int32).max])
def test_rejection_max(val, validator_max):
with pytest.raises(ValueError) as validation_failure:
validator_max.validate_coerce(val)
assert "in the interval [-9223372036854775808, 2]" in str(validation_failure.value)
# Array ok
# --------
# min=-2 and max=10
# ### Acceptance ###
@pytest.mark.parametrize("val", [-2, 1, 0, 1, 10])
def test_acceptance_aok_scalars(val, validator_aok):
assert validator_aok.validate_coerce(val) == val
@pytest.mark.parametrize("val", [[1, 0], [1], [-2, 1, 8], np.array([3, 2, -1, 5])])
def test_acceptance_aok_list(val, validator_aok):
assert np.array_equal(validator_aok.validate_coerce(val), val)
# ### Coerce ###
# Coerced to general consistent numeric type
@pytest.mark.parametrize(
"val,expected",
[
([1, 0], (1, 0)),
((1, -1), (1, -1)),
(np.array([-1, 0, 5.0], dtype="int16"), [-1, 0, 5]),
(np.array([1, 0], dtype=np.int64), [1, 0]),
(pd.Series([1, 0], dtype=np.int64), [1, 0]),
(pd.Index([1, 0], dtype=np.int64), [1, 0]),
],
)
def test_coercion_aok_list(val, expected, validator_aok):
v = validator_aok.validate_coerce(val)
if isinstance(val, (np.ndarray, pd.Series, pd.Index)):
assert v.dtype == val.dtype
assert np.array_equal(
validator_aok.present(v), np.array(expected, dtype=np.int32)
)
else:
assert isinstance(v, list)
assert validator_aok.present(v) == expected
# ### Rejection ###
#
@pytest.mark.parametrize("val", [["a", 4], [[], 3, 4]])
def test_integer_validator_rejection_aok(val, validator_aok):
with pytest.raises(ValueError) as validation_failure:
validator_aok.validate_coerce(val)
assert "Invalid element(s)" in str(validation_failure.value)
# ### Rejection by element ###
@pytest.mark.parametrize(
"val",
[[-1, 11], [1.5, -3], [0, np.iinfo(np.int32).max], [0, np.iinfo(np.int32).min]],
)
def test_rejection_aok_min_max(val, validator_aok):
with pytest.raises(ValueError) as validation_failure:
validator_aok.validate_coerce(val)
assert "in the interval [-2, 10]" in str(validation_failure.value)
|
