class_docstr: Accept a Python dictionary suitable as the ``data`` attribute of a
  :class:`~bokeh.models.sources.ColumnDataSource`.
  
  This class is a specialization of ``Dict`` that handles efficiently
  encoding columns that are NumPy arrays.
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docstr: Return a list of ``ColumnDataPropertyDescriptor`` instances to
  install on a class, in order to delegate attribute access to this
  property.
  
  Args:
      base_name (str) : the name of the property these descriptors are for
  
  Returns:
      list[ColumnDataPropertyDescriptor]
  
  The descriptors returned are collected by the ``MetaHasProps``
  metaclass and added to ``HasProps`` subclasses during class creation.
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code: def make_descriptors(self, base_name):
      """Return a list of ``ColumnDataPropertyDescriptor`` instances to
      install on a class, in order to delegate attribute access to this
      property.
  
      Args:
          base_name (str) : the name of the property these descriptors are for
  
      Returns:
          list[ColumnDataPropertyDescriptor]
  
      The descriptors returned are collected by the ``MetaHasProps``
      metaclass and added to ``HasProps`` subclasses during class creation.
      """
      return [ColumnDataPropertyDescriptor(base_name, self)]
  
imports: from __future__ import annotations
  import logging
  from collections.abc import Container, Iterable, Mapping, Sequence, Sized
  from typing import TYPE_CHECKING, Any, TypeVar
  from ._sphinx import property_link, register_type_link, type_link
  from .bases import ContainerProperty, Init, Property, SingleParameterizedProperty, TypeOrInst
  from .descriptors import ColumnDataPropertyDescriptor
  from .enum import Enum
  from .numeric import Int
  from .singletons import Intrinsic, Undefined
  from .wrappers import PropertyValueColumnData, PropertyValueDict, PropertyValueList, PropertyValueSet
label_desc: Use image node_id 1 for calling the ColumnData obj's underlying member method code with example usage: obj.make_descriptors(base_name) and returns: list