class_docstr: Describes a schema of a data structure which can be rendered as native schema/data-types objects
  in several different python libraries. Currently supported are pyspark, tensorflow, and numpy.
docstr: Creates an instance of a Unischema object.
  
  :param name: name of the schema
  :param fields: a list of ``UnischemaField`` instances describing the fields. The element order in the list
      represent the schema field order.
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code: def __init__(self, name, fields):
      """Creates an instance of a Unischema object.
  
      :param name: name of the schema
      :param fields: a list of ``UnischemaField`` instances describing the fields. The element order in the list
          represent the schema field order.
      """
      self._name = name
      if _UNISCHEMA_FIELD_ORDER.lower() == "alphabetical":
          fields = sorted(fields, key=lambda t: t.name)
  
      self._fields = OrderedDict([(f.name, f) for f in fields])
      # Generates attributes named by the field names as an access syntax sugar.
      for f in fields:
          if not hasattr(self, f.name):
              setattr(self, f.name, f)
          else:
              warnings.warn(
                  (
                      "Can not create dynamic property {} because it conflicts with an existing property of "
                      "Unischema"
                  ).format(f.name)
              )
  
imports: import copy
  import re
  import sys
  import warnings
  from collections import namedtuple, OrderedDict
  from decimal import Decimal
  from typing import Dict, Any, Tuple, Optional, NamedTuple
  import numpy
  import pyarrow
  import six
  from pyarrow.lib import ListType
  from pyarrow.lib import StructType
  from six import string_types
label_desc: Use image node_id 1 to create a new Unischema object from inherited base classes: object with example: obj = Unischema(name, fields)