Merge pull request #4622 from bnavigator/np2

Make test suite ready for NumPy 2.0.0

Author: marthacryan

.circleci/config.yml

@@ -249,6 +249,14 @@ jobs:
       - test_optional:
           py: "312_no_numpy"
 
+  python_312_np2:
+    docker:
+      - image: cimg/python:3.12-browsers
+    steps:
+      - test_optional:
+          py: "312_np2"
+
+
   # Percy
   python_39_percy:
     docker:
@@ -607,4 +615,5 @@ workflows:
       - python_39_pandas_2_optional
       - python_39_percy
       - python_312_no_numpy
+      - python_312_np2
       - build-doc

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

@@ -1,6 +1,7 @@
 import pytest
 from _plotly_utils.basevalidators import AnyValidator
 import numpy as np
+from plotly.tests.test_optional.test_utils.test_utils import np_nan, np_inf
 
 
 # Fixtures
@@ -18,7 +19,7 @@ def validator_aok():
 # Tests
 # -----
 # ### Acceptance ###
-@pytest.mark.parametrize("val", [set(), "Hello", 123, np.inf, np.nan, {}])
+@pytest.mark.parametrize("val", [set(), "Hello", 123, np_inf(), np_nan(), {}])
 def test_acceptance(val, validator):
     assert validator.validate_coerce(val) is val
 

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

@@ -1,7 +1,6 @@
 import pytest
 from _plotly_utils.basevalidators import BooleanValidator
-import numpy as np
-
+from plotly.tests.test_optional.test_utils.test_utils import np_nan
 
 # Boolean Validator
 # =================
@@ -18,7 +17,7 @@ def test_acceptance(val, validator):
 
 
 # ### Rejection ###
-@pytest.mark.parametrize("val", [1.0, 0.0, "True", "False", [], 0, np.nan])
+@pytest.mark.parametrize("val", [1.0, 0.0, "True", "False", [], 0, np_nan()])
 def test_rejection(val, validator):
     with pytest.raises(ValueError) as validation_failure:
         validator.validate_coerce(val)

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

@@ -2,7 +2,7 @@
 import numpy as np
 import pandas as pd
 from _plotly_utils.basevalidators import EnumeratedValidator
-
+from plotly.tests.test_optional.test_utils.test_utils import np_inf
 
 # Fixtures
 # --------
@@ -42,7 +42,7 @@ def test_acceptance(val, validator):
 # ### Value Rejection ###
 @pytest.mark.parametrize(
     "val",
-    [True, 0, 1, 23, np.inf, set(), ["first", "second"], [True], ["third", 4], [4]],
+    [True, 0, 1, 23, np_inf(), set(), ["first", "second"], [True], ["third", 4], [4]],
 )
 def test_rejection_by_value(val, validator):
     with pytest.raises(ValueError) as validation_failure:
@@ -95,7 +95,7 @@ def test_acceptance_aok(val, validator_aok):
 
 
 # ### Rejection by value ###
-@pytest.mark.parametrize("val", [True, 0, 1, 23, np.inf, set()])
+@pytest.mark.parametrize("val", [True, 0, 1, 23, np_inf(), set()])
 def test_rejection_by_value_aok(val, validator_aok):
     with pytest.raises(ValueError) as validation_failure:
         validator_aok.validate_coerce(val)
@@ -105,7 +105,7 @@ def test_rejection_by_value_aok(val, validator_aok):
 
 # ### Reject by elements ###
 @pytest.mark.parametrize(
-    "val", [[True], [0], [1, 23], [np.inf, set()], ["ffirstt", "second", "third"]]
+    "val", [[True], [0], [1, 23], [np_inf(), set()], ["ffirstt", "second", "third"]]
 )
 def test_rejection_by_element_aok(val, validator_aok):
     with pytest.raises(ValueError) as validation_failure:

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

@@ -5,7 +5,7 @@
 from _plotly_utils.basevalidators import IntegerValidator
 import numpy as np
 import pandas as pd
-
+from plotly.tests.test_optional.test_utils.test_utils import np_nan, np_inf
 
 # ### Fixtures ###
 @pytest.fixture()
@@ -53,7 +53,7 @@ def test_acceptance(val, validator):
 
 # ### Rejection by value ###
 @pytest.mark.parametrize(
-    "val", ["hello", (), [], [1, 2, 3], set(), "34", np.nan, np.inf, -np.inf]
+    "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:

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

@@ -4,6 +4,7 @@
 from _plotly_utils.basevalidators import NumberValidator
 import numpy as np
 import pandas as pd
+from plotly.tests.test_optional.test_utils.test_utils import np_nan, np_inf
 
 # Fixtures
 # --------
@@ -36,7 +37,7 @@ def validator_aok():
 # ------------
 # ### Acceptance ###
 @pytest.mark.parametrize(
-    "val", [1.0, 0.0, 1, -1234.5678, 54321, np.pi, np.nan, np.inf, -np.inf]
+    "val", [1.0, 0.0, 1, -1234.5678, 54321, np.pi, np_nan(), np_inf(), -np_inf()]
 )
 def test_acceptance(val, validator):
     assert validator.validate_coerce(val) == approx(val, nan_ok=True)
@@ -57,7 +58,7 @@ 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, 234, -np.inf, np.nan, np.inf])
+@pytest.mark.parametrize("val", [-1.01, -10, 2.1, 234, -np_inf(), np_nan(), np_inf()])
 def test_rejection_min_max(val, validator_min_max):
     with pytest.raises(ValueError) as validation_failure:
         validator_min_max.validate_coerce(val)
@@ -66,12 +67,12 @@ def test_rejection_min_max(val, validator_min_max):
 
 
 # ### With min only ###
-@pytest.mark.parametrize("val", [0, 0.0, -0.5, 99999, np.inf])
+@pytest.mark.parametrize("val", [0, 0.0, -0.5, 99999, np_inf()])
 def test_acceptance_min(val, validator_min):
     assert validator_min.validate_coerce(val) == approx(val)
 
 
-@pytest.mark.parametrize("val", [-1.01, -np.inf, np.nan])
+@pytest.mark.parametrize("val", [-1.01, -np_inf(), np_nan()])
 def test_rejection_min(val, validator_min):
     with pytest.raises(ValueError) as validation_failure:
         validator_min.validate_coerce(val)
@@ -80,12 +81,12 @@ def test_rejection_min(val, validator_min):
 
 
 # ### With max only ###
-@pytest.mark.parametrize("val", [0, 0.0, -np.inf, -123456, np.pi / 2])
+@pytest.mark.parametrize("val", [0, 0.0, -np_inf(), -123456, np.pi / 2])
 def test_acceptance_max(val, validator_max):
     assert validator_max.validate_coerce(val) == approx(val)
 
 
-@pytest.mark.parametrize("val", [2.01, np.inf, np.nan])
+@pytest.mark.parametrize("val", [2.01, np_inf(), np_nan()])
 def test_rejection_max(val, validator_max):
     with pytest.raises(ValueError) as validation_failure:
         validator_max.validate_coerce(val)
@@ -142,7 +143,13 @@ def test_rejection_aok(val, validator_aok):
 # ### Rejection by element ###
 @pytest.mark.parametrize(
     "val",
-    [[-1.6, 0.0], [1, 1.5, 2], [-0.1234, 0.41, np.nan], [0, np.inf], [0, -np.inf]],
+    [
+        [-1.6, 0.0],
+        [1, 1.5, 2],
+        [-0.1234, 0.41, np_nan()],
+        [0, np_inf()],
+        [0, -np_inf()],
+    ],
 )
 def test_rejection_aok_min_max(val, validator_aok):
     with pytest.raises(ValueError) as validation_failure:

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

@@ -2,6 +2,7 @@
 
 from _plotly_utils.basevalidators import StringValidator
 import numpy as np
+from plotly.tests.test_optional.test_utils.test_utils import np_nan
 
 
 # Fixtures
@@ -53,7 +54,7 @@ def validator_no_blanks_aok():
 # Not strict
 # ### Acceptance ###
 @pytest.mark.parametrize(
-    "val", ["bar", 234, np.nan, "HELLO!!!", "world!@#$%^&*()", "", "\u03BC"]
+    "val", ["bar", 234, np_nan(), "HELLO!!!", "world!@#$%^&*()", "", "\u03BC"]
 )
 def test_acceptance(val, validator):
     expected = str(val) if not isinstance(val, str) else val
@@ -108,7 +109,7 @@ def test_acceptance_strict(val, validator_strict):
 
 
 # ### Rejection by value ###
-@pytest.mark.parametrize("val", [(), [], [1, 2, 3], set(), np.nan, np.pi, 23])
+@pytest.mark.parametrize("val", [(), [], [1, 2, 3], set(), np_nan(), np.pi, 23])
 def test_rejection_strict(val, validator_strict):
     with pytest.raises(ValueError) as validation_failure:
         validator_strict.validate_coerce(val)

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

@@ -1,6 +1,6 @@
 import pytest
 from _plotly_utils.basevalidators import SubplotidValidator
-import numpy as np
+from plotly.tests.test_optional.test_utils.test_utils import np_nan, np_inf
 
 
 # Fixtures
@@ -19,7 +19,7 @@ def test_acceptance(val, validator):
 
 
 # ### Rejection by type ###
-@pytest.mark.parametrize("val", [23, [], {}, set(), np.inf, np.nan])
+@pytest.mark.parametrize("val", [23, [], {}, set(), np_inf(), np_nan()])
 def test_rejection_type(val, validator):
     with pytest.raises(ValueError) as validation_failure:
         validator.validate_coerce(val)

packages/python/plotly/plotly/tests/test_optional/test_figure_factory/test_figure_factory.py

@@ -6,6 +6,7 @@
 
 import plotly.figure_factory as ff
 from plotly.tests.test_optional.optional_utils import NumpyTestUtilsMixin
+from plotly.tests.test_optional.test_utils.test_utils import np_nan, np_inf
 
 import numpy as np
 from plotly.tests.utils import TestCaseNoTemplate
@@ -975,10 +976,10 @@ def test_default_dendrogram(self):
             ],
             layout=go.Layout(
                 autosize=False,
-                height=np.inf,
+                height=np_inf(),
                 hovermode="closest",
                 showlegend=False,
-                width=np.inf,
+                width=np_inf(),
                 xaxis=go.layout.XAxis(
                     mirror="allticks",
                     rangemode="tozero",
@@ -1062,10 +1063,10 @@ def test_dendrogram_random_matrix(self):
             ],
             layout=go.Layout(
                 autosize=False,
-                height=np.inf,
+                height=np_inf(),
                 hovermode="closest",
                 showlegend=False,
-                width=np.inf,
+                width=np_inf(),
                 xaxis=go.layout.XAxis(
                     mirror="allticks",
                     rangemode="tozero",
@@ -1217,10 +1218,10 @@ def test_dendrogram_colorscale(self):
             ],
             layout=go.Layout(
                 autosize=False,
-                height=np.inf,
+                height=np_inf(),
                 hovermode="closest",
                 showlegend=False,
-                width=np.inf,
+                width=np_inf(),
                 xaxis=go.layout.XAxis(
                     mirror="allticks",
                     rangemode="tozero",
@@ -4118,25 +4119,25 @@ def test_full_choropleth(self):
                 -88.02432999999999,
                 -88.04504299999999,
                 -88.053375,
-                np.nan,
+                np_nan(),
                 -88.211209,
                 -88.209999,
                 -88.208733,
                 -88.209559,
                 -88.211209,
-                np.nan,
+                np_nan(),
                 -88.22511999999999,
                 -88.22128099999999,
                 -88.218694,
                 -88.22465299999999,
                 -88.22511999999999,
-                np.nan,
+                np_nan(),
                 -88.264659,
                 -88.25782699999999,
                 -88.25947,
                 -88.255659,
                 -88.264659,
-                np.nan,
+                np_nan(),
                 -88.327302,
                 -88.20146799999999,
                 -88.141143,
@@ -4146,13 +4147,13 @@ def test_full_choropleth(self):
                 -88.10665399999999,
                 -88.149812,
                 -88.327302,
-                np.nan,
+                np_nan(),
                 -88.346745,
                 -88.341235,
                 -88.33288999999999,
                 -88.346823,
                 -88.346745,
-                np.nan,
+                np_nan(),
                 -88.473227,
                 -88.097888,
                 -88.154617,

packages/python/plotly/plotly/tests/test_optional/test_px/test_imshow.py

@@ -7,6 +7,7 @@
 import base64
 import datetime
 from plotly.express.imshow_utils import rescale_intensity
+from plotly.tests.test_optional.test_utils.test_utils import np_nan
 
 img_rgb = np.array([[[255, 0, 0], [0, 255, 0], [0, 0, 255]]], dtype=np.uint8)
 img_gray = np.arange(100, dtype=float).reshape((10, 10))
@@ -111,7 +112,7 @@ def test_nan_inf_data(binary_string):
     zmaxs = [1, 255]
     for zmax, img in zip(zmaxs, imgs):
         img[0] = 0
-        img[10:12] = np.nan
+        img[10:12] = np_nan()
         # the case of 2d/heatmap is handled gracefully by the JS trace but I don't know how to check it
         fig = px.imshow(
             np.dstack((img,) * 3),
@@ -341,7 +342,7 @@ def test_imshow_source_dtype_zmax(dtype, contrast_rescaling):
             assert (
                 np.abs(
                     np.max(decode_image_string(fig.data[0].source))
-                    - 255 * img.max() / np.iinfo(dtype).max
+                    - np.int64(255) * img.max() / np.iinfo(dtype).max
                 )
                 < 1
             )

packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py

@@ -3,6 +3,7 @@
 import pandas as pd
 import pytest
 from datetime import datetime
+from plotly.tests.test_optional.test_utils.test_utils import np_nan
 
 
 @pytest.mark.parametrize(
@@ -65,7 +66,7 @@ def test_trendline_enough_values(mode, options):
     assert len(fig.data) == 2
     assert fig.data[1].x is None
     fig = px.scatter(
-        x=[0, 1], y=np.array([0, np.nan]), trendline=mode, trendline_options=options
+        x=[0, 1], y=np.array([0, np_nan()]), trendline=mode, trendline_options=options
     )
     assert len(fig.data) == 2
     assert fig.data[1].x is None
@@ -75,8 +76,8 @@ def test_trendline_enough_values(mode, options):
     assert len(fig.data) == 2
     assert fig.data[1].x is None
     fig = px.scatter(
-        x=np.array([0, 1, np.nan]),
-        y=np.array([0, np.nan, 1]),
+        x=np.array([0, 1, np_nan()]),
+        y=np.array([0, np_nan(), 1]),
         trendline=mode,
         trendline_options=options,
     )
@@ -88,8 +89,8 @@ def test_trendline_enough_values(mode, options):
     assert len(fig.data) == 2
     assert len(fig.data[1].x) == 2
     fig = px.scatter(
-        x=np.array([0, 1, np.nan, 2]),
-        y=np.array([1, np.nan, 1, 2]),
+        x=np.array([0, 1, np_nan(), 2]),
+        y=np.array([1, np_nan(), 1, 2]),
         trendline=mode,
         trendline_options=options,
     )
@@ -112,7 +113,7 @@ def test_trendline_enough_values(mode, options):
 def test_trendline_nan_values(mode, options):
     df = px.data.gapminder().query("continent == 'Oceania'")
     start_date = 1970
-    df["pop"][df["year"] < start_date] = np.nan
+    df["pop"][df["year"] < start_date] = np_nan()
     fig = px.scatter(
         df,
         x="year",