Merge pull request #4379 from ned2/suppress-futurewarning

handle deprecation of pandas.Series.dt.to_pydatetime() calls and suppress their FutureWarnings

Author: alexcjohnson

CHANGELOG.md

@@ -6,6 +6,7 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 
 ### Fixed
 - Repair crash on Matplotlib 3.8 related to get_offset_position [[#4372](https://github.com/plotly/plotly.py/pull/4372)],
+- Handle deprecation of `pandas.Series.dt.to_pydatetime()` calls and suppress the `FutureWarning` they currently emit. [[#4379](https://github.com/plotly/plotly.py/pull/4379)]
 
 ## [5.17.0] - 2023-09-15
 

packages/python/plotly/_plotly_utils/basevalidators.py

@@ -7,6 +7,7 @@
 import io
 import re
 import sys
+import warnings
 
 from _plotly_utils.optional_imports import get_module
 
@@ -100,7 +101,11 @@ def copy_to_readonly_numpy_array(v, kind=None, force_numeric=False):
         elif v.dtype.kind == "M":
             # Convert datetime Series/Index to numpy array of datetimes
             if isinstance(v, pd.Series):
-                v = v.dt.to_pydatetime()
+                with warnings.catch_warnings():
+                    warnings.simplefilter("ignore", FutureWarning)
+                    # Series.dt.to_pydatetime will return Index[object]
+                    # https://github.com/pandas-dev/pandas/pull/52459
+                    v = np.array(v.dt.to_pydatetime())
             else:
                 # DatetimeIndex
                 v = v.to_pydatetime()
@@ -109,7 +114,13 @@ def copy_to_readonly_numpy_array(v, kind=None, force_numeric=False):
         if dtype.kind in numeric_kinds:
             v = v.values
         elif dtype.kind == "M":
-            v = [row.dt.to_pydatetime().tolist() for i, row in v.iterrows()]
+            with warnings.catch_warnings():
+                warnings.simplefilter("ignore", FutureWarning)
+                # Series.dt.to_pydatetime will return Index[object]
+                # https://github.com/pandas-dev/pandas/pull/52459
+                v = [
+                    np.array(row.dt.to_pydatetime()).tolist() for i, row in v.iterrows()
+                ]
 
     if not isinstance(v, np.ndarray):
         # v has its own logic on how to convert itself into a numpy array

packages/python/plotly/plotly/io/_json.py

@@ -1,6 +1,7 @@
 import json
 import decimal
 import datetime
+import warnings
 from pathlib import Path
 
 from plotly.io._utils import validate_coerce_fig_to_dict, validate_coerce_output_type
@@ -535,7 +536,11 @@ def clean_to_json_compatible(obj, **kwargs):
                 return np.ascontiguousarray(obj.values)
             elif obj.dtype.kind == "M":
                 if isinstance(obj, pd.Series):
-                    dt_values = obj.dt.to_pydatetime().tolist()
+                    with warnings.catch_warnings():
+                        warnings.simplefilter("ignore", FutureWarning)
+                        # Series.dt.to_pydatetime will return Index[object]
+                        # https://github.com/pandas-dev/pandas/pull/52459
+                        dt_values = np.array(obj.dt.to_pydatetime()).tolist()
                 else:  # DatetimeIndex
                     dt_values = obj.to_pydatetime().tolist()
 

packages/python/plotly/plotly/tests/test_io/test_to_from_plotly_json.py

@@ -8,6 +8,7 @@
 import datetime
 import re
 import sys
+import warnings
 from pytz import timezone
 from _plotly_utils.optional_imports import get_module
 
@@ -194,7 +195,13 @@ def to_str(v):
     if isinstance(datetime_array, list):
         dt_values = [to_str(d) for d in datetime_array]
     elif isinstance(datetime_array, pd.Series):
-        dt_values = [to_str(d) for d in datetime_array.dt.to_pydatetime().tolist()]
+        with warnings.catch_warnings():
+            warnings.simplefilter("ignore", FutureWarning)
+            # Series.dt.to_pydatetime will return Index[object]
+            # https://github.com/pandas-dev/pandas/pull/52459
+            dt_values = [
+                to_str(d) for d in np.array(datetime_array.dt.to_pydatetime()).tolist()
+            ]
     elif isinstance(datetime_array, pd.DatetimeIndex):
         dt_values = [to_str(d) for d in datetime_array.to_pydatetime().tolist()]
     else:  # numpy datetime64 array