text: #
  # Licensed to the Apache Software Foundation (ASF) under one or more
  # contributor license agreements.  See the NOTICE file distributed with
  # this work for additional information regarding copyright ownership.
  # The ASF licenses this file to You under the Apache License, Version 2.0
  # (the "License"); you may not use this file except in compliance with
  # the License.  You may obtain a copy of the License at
  #
  #    http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  #
  from pyspark.pandas.missing import unsupported_function, unsupported_property, common
  
  
  def _unsupported_function(method_name, deprecated=False, reason=""):
      return unsupported_function(
          class_name="pd.Series", method_name=method_name, deprecated=deprecated, reason=reason
      )
  
  
  def _unsupported_property(property_name, deprecated=False, reason=""):
      return unsupported_property(
          class_name="pd.Series", property_name=property_name, deprecated=deprecated, reason=reason
      )
  
  
  class MissingPandasLikeSeries:
      # NOTE: Please update the document "Supported pandas APIs" when implementing the new API.
      # Documentation path: `python/docs/source/user_guide/pandas_on_spark/supported_pandas_api.rst`.
  
      # Functions
      asfreq = _unsupported_function("asfreq")
      combine = _unsupported_function("combine")
      convert_dtypes = _unsupported_function("convert_dtypes")
      infer_objects = _unsupported_function("infer_objects")
      reorder_levels = _unsupported_function("reorder_levels")
      resample = _unsupported_function("resample")
      searchsorted = _unsupported_function("searchsorted")
      set_axis = _unsupported_function("set_axis")
      to_hdf = _unsupported_function("to_hdf")
      to_period = _unsupported_function("to_period")
      to_sql = _unsupported_function("to_sql")
      to_timestamp = _unsupported_function("to_timestamp")
      tz_convert = _unsupported_function("tz_convert")
      tz_localize = _unsupported_function("tz_localize")
      view = _unsupported_function("view")
  
      # Deprecated functions
      slice_shift = _unsupported_function(
          "slice_shift", deprecated=True, reason="Use DataFrame/Series.shift instead."
      )
      tshift = _unsupported_function("tshift", deprecated=True, reason="Use `shift` instead.")
  
      # Properties we won't support.
      array = common.array(_unsupported_property)
      nbytes = _unsupported_property(
          "nbytes",
          reason="'nbytes' requires to compute whole dataset. You can calculate manually it, "
          "with its 'itemsize', by explicitly executing its count. Use Spark's web UI "
          "to monitor disk and memory usage of your application in general.",
      )
  
      # Functions we won't support.
      memory_usage = common.memory_usage(_unsupported_function)
      to_pickle = common.to_pickle(_unsupported_function)
      to_xarray = common.to_xarray(_unsupported_function)
      __iter__ = common.__iter__(_unsupported_function)
      ravel = _unsupported_function(
          "ravel",
          reason="If you want to collect your flattened underlying data as an NumPy array, "
          "use 'to_numpy().ravel()' instead.",
      )
  