Only attempt to import np/pd once in basevalidators

Use get_module to import numpy and pandas once at the load of basevalidators

Significantly speeds up graph rendering when using large (10K entry)
pandas dataframe columns.

Graph rendering time changed from 1200-1500ms to 240-350ms by avoiding
many (~10K) calls to get_module().

Author: Zack Cornelius

Diff for: packages/python/plotly/_plotly_utils/basevalidators.py

@@ -14,6 +14,9 @@
 
 from _plotly_utils.optional_imports import get_module
 
+np = get_module("numpy")
+pd = get_module("pandas")
+
 
 # back-port of fullmatch from Py3.4+
 def fullmatch(regex, string, flags=0):
@@ -35,8 +38,6 @@ def to_scalar_or_list(v):
     # Python native scalar type ('float' in the example above).
     # We explicitly check if is has the 'item' method, which conventionally
     # converts these types to native scalars.
-    np = get_module("numpy")
-    pd = get_module("pandas")
     if np and np.isscalar(v) and hasattr(v, "item"):
         return v.item()
     if isinstance(v, (list, tuple)):
@@ -73,8 +74,6 @@ def copy_to_readonly_numpy_array(v, kind=None, force_numeric=False):
     np.ndarray
         Numpy array with the 'WRITEABLE' flag set to False
     """
-    np = get_module("numpy")
-    pd = get_module("pandas")
     assert np is not None
 
     # ### Process kind ###
@@ -166,8 +165,6 @@ def is_homogeneous_array(v):
     """
     Return whether a value is considered to be a homogeneous array
     """
-    np = get_module("numpy")
-    pd = get_module("pandas")
     if (
         np
         and isinstance(v, np.ndarray)
@@ -739,7 +736,6 @@ def validate_coerce(self, v):
             # Pass None through
             pass
         elif self.array_ok and is_homogeneous_array(v):
-            np = get_module("numpy")
             try:
                 v_array = copy_to_readonly_numpy_array(v, force_numeric=True)
             except (ValueError, TypeError, OverflowError):
@@ -867,7 +863,6 @@ def validate_coerce(self, v):
             # Pass None through
             pass
         elif self.array_ok and is_homogeneous_array(v):
-            np = get_module("numpy")
             v_array = copy_to_readonly_numpy_array(
                 v, kind=("i", "u"), force_numeric=True
             )
@@ -1030,7 +1025,6 @@ def validate_coerce(self, v):
                     self.raise_invalid_elements(invalid_els)
 
             if is_homogeneous_array(v):
-                np = get_module("numpy")
 
                 # If not strict, let numpy cast elements to strings
                 v = copy_to_readonly_numpy_array(v, kind="U")