text: # *****************************************************************************
  # Copyright (c) 2020, Intel Corporation All rights reserved.
  #
  # Redistribution and use in source and binary forms, with or without
  # modification, are permitted provided that the following conditions are met:
  #
  #     Redistributions of source code must retain the above copyright notice,
  #     this list of conditions and the following disclaimer.
  #
  #     Redistributions in binary form must reproduce the above copyright notice,
  #     this list of conditions and the following disclaimer in the documentation
  #     and/or other materials provided with the distribution.
  #
  # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
  # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
  # THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
  # PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
  # CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
  # EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
  # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
  # OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
  # WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
  # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
  # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
  # *****************************************************************************
  
  import pandas as pd
  
  from numba import typeof
  from numba import types
  from numba import objmode
  
  from ..categorical.pdimpl import _reconstruct_CategoricalDtype
  
  
  def _reconstruct_Series(data, dtype):
      values_list = [v.literal_value for v in data]
      dtype = _reconstruct_CategoricalDtype(dtype)
      return pd.Series(data=values_list, dtype=dtype)
  
  
  def _Series_category(data=None, index=None, dtype=None, name=None, copy=False, fastpath=False):
      """
      Implementation of constructor for pandas Series via objmode.
      """
      # TODO: support other parameters (only data and dtype now)
  
      ty = typeof(_reconstruct_Series(data, dtype))
  
      from textwrap import dedent
      text = dedent(f"""
      def impl(data=None, index=None, dtype=None, name=None, copy=False, fastpath=False):
          with objmode(series="{ty}"):
              series = pd.Series(data, index, dtype, name, copy, fastpath)
          return series
      """)
      globals, locals = {'objmode': objmode, 'pd': pd}, {}
      exec(text, globals, locals)
      impl = locals['impl']
      return impl
  