Revert changes to validator tests

packages/python/plotly/_plotly_utils/tests/validators/test_angle_validator.py

@@ -3,7 +3,6 @@
 # from ..basevalidators import AngleValidator
 from _plotly_utils.basevalidators import AngleValidator
 import numpy as np
-from plotly.tests.b64 import b64
 
 
 # Fixtures
@@ -52,14 +51,6 @@ def test_aok_acceptance(val, validator_aok):
     assert np.array_equal(validator_aok.validate_coerce(np.array(val)), np.array(val))
 
 
-# Test base64 array
-def test_aok_base64_array(validator_aok):
-    val = b64(np.array([1, 2, 3], dtype="int64"))
-    coerce_val = validator_aok.validate_coerce(val)
-    assert coerce_val["bdata"] == "AQID"
-    assert coerce_val["dtype"] == "i1"
-
-
 # ### Test coercion above 180 ###
 @pytest.mark.parametrize(
     "val,expected",

packages/python/plotly/_plotly_utils/tests/validators/test_any_validator.py

@@ -1,7 +1,6 @@
 import pytest
 from _plotly_utils.basevalidators import AnyValidator
 import numpy as np
-from plotly.tests.b64 import b64
 
 
 # Fixtures
@@ -50,10 +49,3 @@ def test_acceptance_array(val, validator_aok):
     else:
         assert coerce_val == val
         assert validator_aok.present(coerce_val) == val
-
-
-def test_base64_array(validator_aok):
-    val = b64(np.array([1, 2, 3], dtype="int64"))
-    coerce_val = validator_aok.validate_coerce(val)
-    assert coerce_val["bdata"] == "AQID"
-    assert coerce_val["dtype"] == "i1"

packages/python/plotly/_plotly_utils/tests/validators/test_basetraces_validator.py

@@ -1,7 +1,7 @@
 import pytest
 from _plotly_utils.basevalidators import BaseDataValidator
 from plotly.graph_objs import Scatter, Bar, Box
-import numpy as np
+
 
 # Fixtures
 # --------
@@ -118,19 +118,6 @@ def test_rejection_element_tracetype(validator):
     assert "Invalid element(s)" in str(validation_failure.value)
 
 
-def test_b64(validator):
-    val = [dict(type="scatter", x=np.array([1, 2, 3]))]
-    res = validator.validate_coerce(val)
-    res_present = validator.present(res)
-
-    assert isinstance(res, list)
-    assert isinstance(res_present, tuple)
-
-    assert isinstance(res_present[0], Scatter)
-    assert res_present[0].type == "scatter"
-    assert res_present[0].x == {"bdata": "AQID", "dtype": "i1"}
-
-
 def test_skip_invalid(validator_nouid):
     val = (
         dict(

packages/python/plotly/_plotly_utils/tests/validators/test_color_validator.py

@@ -1,7 +1,6 @@
 import pytest
 from _plotly_utils.basevalidators import ColorValidator
 import numpy as np
-from plotly.tests.b64 import b64
 
 
 # Fixtures
@@ -132,19 +131,6 @@ def test_acceptance_aok(val, validator_aok):
         assert coerce_val == val
 
 
-# Test that it doesn't use a base64 array
-# Numpy v2 has a StrDType but we don't want to convert it yet.
-# Change this test if you add support for it.
-def test_acceptance_aok_base64_array(validator_aok):
-    val = b64(np.array(["aliceblue", "antiquewhite", "aqua", "aquamarine", "azure"]))
-    coerce_val = validator_aok.validate_coerce(val)
-    assert coerce_val[0] == "aliceblue"
-    assert coerce_val[1] == "antiquewhite"
-    assert coerce_val[2] == "aqua"
-    assert coerce_val[3] == "aquamarine"
-    assert coerce_val[4] == "azure"
-
-
 @pytest.mark.parametrize(
     "val",
     [

packages/python/plotly/_plotly_utils/tests/validators/test_colorlist_validator.py

@@ -2,7 +2,7 @@
 import numpy as np
 
 from _plotly_utils.basevalidators import ColorlistValidator
-from plotly.tests.b64 import b64
+
 
 # Fixtures
 # --------
@@ -48,13 +48,3 @@ def test_acceptance_aok(val, validator):
     coerce_val = validator.validate_coerce(val)
     assert isinstance(coerce_val, list)
     assert validator.present(coerce_val) == tuple(val)
-
-
-# Test that it doesn't use a base64 array
-# Numpy v2 has a StrDType but we don't want to convert it yet.
-# Change this test if you add support for it.
-def test_acceptance_b64_aok(validator):
-    val = b64(np.array(["red", "rgb(255, 0, 0)"]))
-    coerce_val = validator.validate_coerce(val)
-    assert coerce_val[0] == "red"
-    assert coerce_val[1] == "rgb(255, 0, 0)"

packages/python/plotly/_plotly_utils/tests/validators/test_compoundarray_validator.py

@@ -2,6 +2,7 @@
 from _plotly_utils.basevalidators import CompoundArrayValidator
 from plotly.graph_objs.layout import Image
 
+
 # Fixtures
 # --------
 @pytest.fixture()

packages/python/plotly/_plotly_utils/tests/validators/test_dataarray_validator.py

@@ -2,7 +2,6 @@
 from _plotly_utils.basevalidators import DataArrayValidator
 import numpy as np
 import pandas as pd
-from plotly.tests.b64 import b64
 
 # Fixtures
 # --------
@@ -34,22 +33,12 @@ def test_validator_acceptance_simple(val, validator):
 
 @pytest.mark.parametrize(
     "val",
-    [pd.Series(["a", "b", "c"])],
+    [np.array([2, 3, 4]), pd.Series(["a", "b", "c"]), np.array([[1, 2, 3], [4, 5, 6]])],
 )
 def test_validator_acceptance_homogeneous(val, validator):
     coerce_val = validator.validate_coerce(val)
     assert isinstance(coerce_val, np.ndarray)
-    assert np.array_equal(validator.present(coerce_val), b64(val))
-
-
-@pytest.mark.parametrize(
-    "val",
-    [np.array([2, 3, 4]), np.array([[1, 2, 3], [4, 5, 6]])],
-)
-def test_validator_acceptance_homogeneous(val, validator):
-    coerce_val = validator.validate_coerce(val)
-    assert isinstance(coerce_val, object)
-    assert np.array_equal(validator.present(coerce_val), b64(val))
+    assert np.array_equal(validator.present(coerce_val), val)
 
 
 # ### Rejection ###

packages/python/plotly/_plotly_utils/tests/validators/test_enumerated_validator.py

@@ -2,7 +2,6 @@
 import numpy as np
 import pandas as pd
 from _plotly_utils.basevalidators import EnumeratedValidator
-from plotly.tests.b64 import b64
 
 
 # Fixtures
@@ -95,14 +94,6 @@ def test_acceptance_aok(val, validator_aok):
         assert coerce_val == val
 
 
-# Test base64 array
-def test_aok_base64_array(validator_aok):
-    val = b64(np.array([1, 2, 3], dtype="int64"))
-    coerce_val = validator_aok.validate_coerce(val)
-    assert coerce_val["bdata"] == "AQID"
-    assert coerce_val["dtype"] == "i1"
-
-
 # ### Rejection by value ###
 @pytest.mark.parametrize("val", [True, 0, 1, 23, np.inf, set()])
 def test_rejection_by_value_aok(val, validator_aok):

packages/python/plotly/_plotly_utils/tests/validators/test_flaglist_validator.py

@@ -2,7 +2,7 @@
 import pytest
 from _plotly_utils.basevalidators import FlaglistValidator
 import numpy as np
-from plotly.tests.b64 import b64
+
 
 EXTRAS = ["none", "all", True, False, 3]
 FLAGS = ["lines", "markers", "text"]
@@ -130,14 +130,6 @@ def test_acceptance_aok_scalar_extra(extra, validator_extra_aok):
     assert validator_extra_aok.validate_coerce(extra) == extra
 
 
-# Test base64 array
-def test_acceptance_aok_scalar_base64(validator_extra_aok):
-    val = b64(np.array([1, 2, 3], dtype="int64"))
-    coerce_val = validator_extra_aok.validate_coerce(val)
-    assert coerce_val["bdata"] == "AQID"
-    assert coerce_val["dtype"] == "i1"
-
-
 # ### Acceptance (lists) ###
 def test_acceptance_aok_scalarlist_flaglist(flaglist, validator_extra_aok):
     assert np.array_equal(

packages/python/plotly/_plotly_utils/tests/validators/test_integer_validator.py

@@ -3,7 +3,6 @@
 import pytest
 from pytest import approx
 from _plotly_utils.basevalidators import IntegerValidator
-from plotly.tests.b64 import b64
 import numpy as np
 import pandas as pd
 
@@ -145,51 +144,6 @@ def test_acceptance_aok_list(val, validator_aok):
     assert np.array_equal(validator_aok.validate_coerce(val), val)
 
 
-# Test base64 encoded arrays with array_ok=True
-INT_BASE64_TEST_CASES = [
-    # Note: we decided not to support int64 in plotly.js,
-    # so the the max / min value are limited to int32 and the
-    # dtype is cast to int32 in the output
-    (
-        b64(np.array([-900000000, 900000000, 3], dtype="int64")),
-        {"bdata": "ABdbygDppDUDAAAA", "dtype": "i4"},
-    ),
-    (
-        b64(np.array([-900000000, 900000000, 3], dtype="int32")),
-        {"bdata": "ABdbygDppDUDAAAA", "dtype": "i4"},
-    ),
-    (
-        b64(np.array([32767, -32767, 3], dtype="int16")),
-        {"bdata": "/38BgAMA", "dtype": "i2"},
-    ),
-    (
-        b64(np.array([127, -127, 3], dtype="int8")),
-        {"bdata": "f4ED", "dtype": "i1"},
-    ),
-    (
-        b64(np.array([900000000, 2, 3], dtype="uint64")),
-        {"bdata": "AOmkNQIAAAADAAAA", "dtype": "u4"},
-    ),
-    (
-        b64(np.array([900000000, 2, 3], dtype="uint32")),
-        {"bdata": "AOmkNQIAAAADAAAA", "dtype": "u4"},
-    ),
-    (
-        b64(np.array([32767, 0, 3], dtype="uint16")),
-        {"bdata": "/38AAAMA", "dtype": "u2"},
-    ),
-    (
-        b64(np.array([127, 2, 3], dtype="uint8")),
-        {"bdata": "fwID", "dtype": "u1"},
-    ),
-]
-
-
-@pytest.mark.parametrize("val, expected", INT_BASE64_TEST_CASES)
-def test_acceptance_aok_base64(val, expected, validator_aok):
-    assert np.array_equal(validator_aok.validate_coerce(val), expected)
-
-
 # ### Coerce ###
 #     Coerced to general consistent numeric type
 @pytest.mark.parametrize(

packages/python/plotly/_plotly_utils/tests/validators/test_number_validator.py

@@ -4,7 +4,6 @@
 from _plotly_utils.basevalidators import NumberValidator
 import numpy as np
 import pandas as pd
-from plotly.tests.b64 import b64
 
 # Fixtures
 # --------
@@ -109,14 +108,6 @@ def test_acceptance_aok_list(val, validator_aok):
     )
 
 
-# Test base64 array
-def test_acceptance_aok_base64(validator_aok):
-    val = b64(np.array([1, 2, 3], dtype="int64"))
-    coerce_val = validator_aok.validate_coerce(val)
-    assert coerce_val["bdata"] == "AQID"
-    assert coerce_val["dtype"] == "i1"
-
-
 # ### Coerce ###
 #     Coerced to general consistent numeric type
 @pytest.mark.parametrize(

packages/python/plotly/_plotly_utils/tests/validators/test_pandas_series_input.py

@@ -9,8 +9,6 @@
     ColorValidator,
 )
 
-from plotly.tests.b64 import _b64
-
 
 @pytest.fixture
 def data_array_validator(request):
@@ -93,7 +91,7 @@ def test_numeric_validator_numeric_pandas(number_validator, numeric_pandas):
     res = number_validator.validate_coerce(numeric_pandas)
 
     # Check type
-    assert isinstance(res, object)
+    assert isinstance(res, np.ndarray)
 
     # Check dtype
     assert res.dtype == numeric_pandas.dtype
@@ -106,7 +104,7 @@ def test_integer_validator_numeric_pandas(integer_validator, numeric_pandas):
     res = integer_validator.validate_coerce(numeric_pandas)
 
     # Check type
-    assert isinstance(res, object)
+    assert isinstance(res, np.ndarray)
 
     # Check dtype
     if numeric_pandas.dtype.kind in ("u", "i"):
@@ -124,12 +122,10 @@ def test_data_array_validator(data_array_validator, numeric_pandas):
     res = data_array_validator.validate_coerce(numeric_pandas)
 
     # Check type
-    assert isinstance(res, object)
-
-    numeric_pandas = _b64(numeric_pandas)
+    assert isinstance(res, np.ndarray)
 
     # Check dtype
-    assert res["dtype"] == numeric_pandas["dtype"]
+    assert res.dtype == numeric_pandas.dtype
 
     # Check values
     np.testing.assert_array_equal(res, numeric_pandas)

packages/python/plotly/_plotly_utils/tests/validators/test_string_validator.py

@@ -3,8 +3,6 @@
 from _plotly_utils.basevalidators import StringValidator
 import numpy as np
 
-from plotly.tests.b64 import b64
-
 
 # Fixtures
 # --------
@@ -147,17 +145,6 @@ def test_acceptance_aok_list(val, validator_aok):
         assert coerce_val == val
 
 
-# Test that it doesn't use a base64 array
-# Numpy v2 has a StrDType but we don't want to convert it yet.
-# Change this test if you add support for it.
-def test_aok_base64_array(validator_aok):
-    val = b64(np.array(["a", "b", "c"]))
-    coerce_val = validator_aok.validate_coerce(val)
-    assert coerce_val[0] == "a"
-    assert coerce_val[1] == "b"
-    assert coerce_val[2] == "c"
-
-
 # ### Rejection by type ###
 @pytest.mark.parametrize("val", [["foo", ()], ["foo", 3, 4], [3, 2, 1]])
 def test_rejection_aok(val, validator_aok_strict):

packages/python/plotly/_plotly_utils/tests/validators/test_xarray_input.py

@@ -9,8 +9,6 @@
     ColorValidator,
 )
 
-from plotly.tests.b64 import _b64
-
 
 @pytest.fixture
 def data_array_validator(request):
@@ -101,12 +99,10 @@ def test_data_array_validator(data_array_validator, numeric_xarray):
     res = data_array_validator.validate_coerce(numeric_xarray)
 
     # Check type
-    assert isinstance(res, object)
-
-    numeric_xarray = _b64(numeric_xarray)
+    assert isinstance(res, np.ndarray)
 
     # Check dtype
-    assert res["dtype"] == numeric_xarray["dtype"]
+    assert res.dtype == numeric_xarray.dtype
 
     # Check values
     np.testing.assert_array_equal(res, numeric_xarray)