code: def from_delayed(
      dfs: Delayed
      | distributed.Future
      | Iterable[Delayed | distributed.Future],
      meta=None,
      divisions: tuple | Literal["sorted"] | None = None,
      prefix: str = "from-delayed",
      verify_meta: bool = True,
  ) -> DataFrame | Series:
      """Create Dask DataFrame from many Dask Delayed objects
  
      Parameters
      ----------
      dfs :
          A ``dask.delayed.Delayed``, a ``distributed.Future``, or an iterable of either
          of these objects, e.g. returned by ``client.submit``. These comprise the
          individual partitions of the resulting dataframe.
          If a single object is provided (not an iterable), then the resulting dataframe
          will have only one partition.
      $META
      divisions :
          Partition boundaries along the index.
          For tuple, see https://docs.dask.org/en/latest/dataframe-design.html#partitions
          For string 'sorted' will compute the delayed values to find index
          values.  Assumes that the indexes are mutually sorted.
          If None, then won't use index information
      prefix :
          Prefix to prepend to the keys.
      verify_meta :
          If True check that the partitions have consistent metadata, defaults to True.
      """
      from dask.delayed import Delayed
  
      if isinstance(dfs, Delayed) or hasattr(dfs, "key"):
          dfs = [dfs]
      dfs = [
          delayed(df)
          if not isinstance(df, Delayed) and hasattr(df, "key")
          else df
          for df in dfs
      ]
  
      for item in dfs:
          if not isinstance(item, Delayed):
              raise TypeError(
                  "Expected Delayed object, got %s"
                  % type(item).__name__
              )
  
      if meta is None:
          meta = delayed(make_meta)(dfs[0]).compute()
      else:
          meta = make_meta(meta)
  
      if not dfs:
          dfs = [delayed(make_meta)(meta)]
  
      if divisions is None or divisions == "sorted":
          divs: list | tuple = [None] * (len(dfs) + 1)
      else:
          divs = list(divisions)
          if len(divs) != len(dfs) + 1:
              raise ValueError(
                  "divisions should be a tuple of len(dfs) + 1"
              )
  
      name = prefix + "-" + tokenize(*dfs)
      layer = DataFrameIOLayer(
          name=name,
          columns=None,
          inputs=BlockwiseDepDict(
              {(i,): inp.key for i, inp in enumerate(dfs)},
              produces_keys=True,
          ),
          io_func=partial(
              check_meta, meta=meta, funcname="from_delayed"
          )
          if verify_meta
          else lambda x: x,
      )
      df = new_dd_object(
          HighLevelGraph.from_collections(name, layer, dfs),
          name,
          meta,
          divs,
      )
  
      if divisions == "sorted":
          from dask.dataframe.shuffle import compute_and_set_divisions
  
          return compute_and_set_divisions(df)
  
      return df
  
imports: from __future__ import annotations
  from collections.abc import Iterable
  from functools import partial
  from math import ceil
  from operator import getitem
  from threading import Lock
  from typing import TYPE_CHECKING, Literal, overload
  import numpy
  import pandas
  import dask.array
  from dask.base import is_dask_collection, tokenize
  from dask.blockwise import BlockwiseDepDict, blockwise
  from dask.dataframe._compat import is_any_real_numeric_dtype
  from dask.dataframe.backends import dataframe_creation_dispatch
  from dask.dataframe.core import DataFrame, Index, Series, _concat, _emulate, _Frame, apply_and_enforce, has_parallel_type, new_dd_object
  from dask.dataframe.dispatch import meta_lib_from_array
  from dask.dataframe.io.utils import DataFrameIOFunction
  from dask.dataframe.utils import check_meta, insert_meta_param_description, is_series_like, make_meta
  from dask.delayed import Delayed, delayed
  from dask.highlevelgraph import HighLevelGraph
  from dask.layers import DataFrameIOLayer
  from dask.utils import M, funcname, is_arraylike
label_desc: Use image node_id 13 for calling a global function with example usage: from_delayed(dfs, meta, divisions, prefix, verify_meta) and returns: df, compute_and_set_divisions