code: def single_partition_join(left, right, **kwargs):
      # if the merge is performed on_index, divisions can be kept, otherwise the
      # new index will not necessarily correspond with the current divisions
  
      meta = left._meta_nonempty.merge(right._meta_nonempty, **kwargs)
  
      use_left = kwargs.get(
          "right_index"
      ) or right._contains_index_name(kwargs.get("right_on"))
      use_right = kwargs.get("left_index") or left._contains_index_name(
          kwargs.get("left_on")
      )
  
      if len(meta) == 0:
          if use_left:
              meta.index = meta.index.astype(left.index.dtype)
          elif use_right:
              meta.index = meta.index.astype(right.index.dtype)
          else:
              meta.index = meta.index.astype("int64")
  
      kwargs["result_meta"] = meta
  
      if right.npartitions == 1 and kwargs["how"] in allowed_left:
          if use_left:
              divisions = left.divisions
          elif use_right and len(right.divisions) == len(
              left.divisions
          ):
              divisions = right.divisions
          else:
              divisions = [None for _ in left.divisions]
  
      elif left.npartitions == 1 and kwargs["how"] in allowed_right:
          if use_right:
              divisions = right.divisions
          elif use_left and len(left.divisions) == len(right.divisions):
              divisions = left.divisions
          else:
              divisions = [None for _ in right.divisions]
      else:
          raise NotImplementedError(
              "single_partition_join has no fallback for invalid calls"
          )
  
      joined = map_partitions(
          merge_chunk,
          left,
          right,
          meta=meta,
          enforce_metadata=False,
          transform_divisions=False,
          align_dataframes=False,
          **kwargs,
      )
      joined.divisions = tuple(divisions)
      return joined
  
imports: from __future__ import annotations
  import math
  import pickle
  import warnings
  from functools import partial, wraps
  import numpy
  import pandas
  from pandas.api.types import is_dtype_equal
  from tlz import merge_sorted, unique
  from dask.base import is_dask_collection, tokenize
  from dask.dataframe import methods
  from dask.dataframe.core import DataFrame, Index, Series, _concat, _deprecated_kwarg, _Frame, _maybe_from_pandas, is_broadcastable, map_partitions, new_dd_object, prefix_reduction, suffix_reduction
  from dask.dataframe.dispatch import group_split_dispatch, hash_object_dispatch
  from dask.dataframe.io import from_pandas
  from dask.dataframe.shuffle import partitioning_index, rearrange_by_divisions, shuffle, shuffle_group
  from dask.dataframe.utils import asciitable, check_meta, is_dataframe_like, is_series_like, make_meta, strip_unknown_categories
  from dask.highlevelgraph import HighLevelGraph
  from dask.layers import BroadcastJoinLayer
  from dask.utils import M, apply, get_default_shuffle_method
label_desc: Use image node_id 7 for calling a global function with example usage: single_partition_join(left, right) and returns: joined