code: def timedelta_range(
      start: Union[str, Any] = None,
      end: Union[str, Any] = None,
      periods: Optional[int] = None,
      freq: Optional[Union[str, DateOffset]] = None,
      name: Optional[str] = None,
      closed: Optional[str] = None,
  ) -> TimedeltaIndex:
      """
      Return a fixed frequency TimedeltaIndex, with day as the default frequency.
  
      Parameters
      ----------
      start : str or timedelta-like, optional
          Left bound for generating timedeltas.
      end : str or timedelta-like, optional
          Right bound for generating timedeltas.
      periods : int, optional
          Number of periods to generate.
      freq : str or DateOffset, default 'D'
          Frequency strings can have multiples, e.g. '5H'.
      name : str, default None
          Name of the resulting TimedeltaIndex.
      closed : {None, 'left', 'right'}, optional
          Make the interval closed with respect to the given frequency to
          the 'left', 'right', or both sides (None, the default).
  
      Returns
      -------
      TimedeltaIndex
  
      Notes
      -----
      Of the four parameters ``start``, ``end``, ``periods``, and ``freq``,
      exactly three must be specified. If ``freq`` is omitted, the resulting
      ``TimedeltaIndex`` will have ``periods`` linearly spaced elements between
      ``start`` and ``end`` (closed on both sides).
  
      To learn more about the frequency strings, please see `this link
      <https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.
  
      Examples
      --------
      >>> ps.timedelta_range(start='1 day', periods=4)  # doctest: +NORMALIZE_WHITESPACE
      TimedeltaIndex(['1 days', '2 days', '3 days', '4 days'], dtype='timedelta64[ns]', freq=None)
  
      The closed parameter specifies which endpoint is included.
      The default behavior is to include both endpoints.
  
      >>> ps.timedelta_range(start='1 day', periods=4, closed='right')
      ... # doctest: +NORMALIZE_WHITESPACE
      TimedeltaIndex(['2 days', '3 days', '4 days'], dtype='timedelta64[ns]', freq=None)
  
      The freq parameter specifies the frequency of the TimedeltaIndex.
      Only fixed frequencies can be passed, non-fixed frequencies such as ‘M’ (month end) will raise.
  
      >>> ps.timedelta_range(start='1 day', end='2 days', freq='6H')
      ... # doctest: +NORMALIZE_WHITESPACE
      TimedeltaIndex(['1 days 00:00:00', '1 days 06:00:00', '1 days 12:00:00',
                      '1 days 18:00:00', '2 days 00:00:00'],
                     dtype='timedelta64[ns]', freq=None)
  
      Specify start, end, and periods; the frequency is generated automatically (linearly spaced).
  
      >>> ps.timedelta_range(start='1 day', end='5 days', periods=4)
      ... # doctest: +NORMALIZE_WHITESPACE
      TimedeltaIndex(['1 days 00:00:00', '2 days 08:00:00', '3 days 16:00:00',
                      '5 days 00:00:00'],
                     dtype='timedelta64[ns]', freq=None)
      """
      assert freq not in ["N", "ns"], "nanoseconds is not supported"
  
      return cast(
          TimedeltaIndex,
          ps.from_pandas(
              pd.timedelta_range(
                  start=start,
                  end=end,
                  periods=periods,
                  freq=freq,
                  name=name,
                  closed=closed,
              )
          ),
      )
  
imports: from typing import Any, Callable, Dict, List, Optional, Set, Sized, Tuple, Type, Union, cast, no_type_check
  from collections.abc import Iterable
  from datetime import tzinfo
  from functools import reduce
  from io import BytesIO
  import json
  import warnings
  import numpy
  import pandas
  from pandas.api.types import is_datetime64_dtype, is_list_like
  from pandas.tseries.offsets import DateOffset
  import pyarrow
  import pyarrow.parquet
  from pyspark.sql import functions, Column
  from pyspark.sql.functions import pandas_udf
  from pyspark.sql.types import ByteType, ShortType, IntegerType, LongType, FloatType, DoubleType, BooleanType, TimestampType, TimestampNTZType, DecimalType, StringType, DateType, StructType, DataType
  from pyspark.sql.dataframe import DataFrame
  from pyspark import pandas
  from pyspark.pandas._typing import Axis, Dtype, Label, Name
  from pyspark.pandas.base import IndexOpsMixin
  from pyspark.pandas.utils import align_diff_frames, default_session, is_name_like_tuple, is_name_like_value, name_like_string, same_anchor, scol_for, validate_axis, log_advice
  from pyspark.pandas.frame import DataFrame, _reduce_spark_multi
  from pyspark.pandas.internal import InternalFrame, DEFAULT_SERIES_NAME, HIDDEN_COLUMNS, SPARK_INDEX_NAME_FORMAT
  from pyspark.pandas.series import Series, first_series
  from pyspark.pandas.spark.utils import as_nullable_spark_type, force_decimal_precision_scale
  from pyspark.pandas.indexes import Index, DatetimeIndex, TimedeltaIndex
  from pyspark.pandas.indexes.multi import MultiIndex
  from pyspark.sql.utils import get_column_class
label_desc: Use image node_id 18 for calling a global function with example usage: timedelta_range(start, end, periods, freq, name, closed) and returns: cast