code: def concat_unindexed_dataframes(dfs, ignore_order=False, **kwargs):
      name = "concat-" + tokenize(*dfs)
  
      dsk = {
          (name, i): (
              concat_and_check,
              [(df._name, i) for df in dfs],
              ignore_order,
          )
          for i in range(dfs[0].npartitions)
      }
      kwargs.update({"ignore_order": ignore_order})
      meta = methods.concat([df._meta for df in dfs], axis=1, **kwargs)
  
      graph = HighLevelGraph.from_collections(
          name, dsk, dependencies=dfs
      )
      return new_dd_object(graph, name, meta, dfs[0].divisions)
  
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 22 for calling a global function with example usage: concat_unindexed_dataframes(dfs, ignore_order) and returns: new_dd_object