class_docstr: Packed-argument wrapper for DataFrameIOFunction
  
  This is a private helper class for ``from_map``. This class
  ensures that packed positional arguments will be expanded
  before the underlying function (``func``) is called. This class
  also handles optional metadata enforcement and column projection
  (when ``func`` satisfies the ``DataFrameIOFunction`` protocol).
class_docstr_tok: ["Packed-argument","wrapper","for","DataFrameIOFunction","This","is","a","private","helper","class","for","``","from_map","``",".","This","class","ensures","that","packed","positional","arguments","will","be","expanded","before","the","underlying","function","(","``","func","``",")","is","called",".","This","class","also","handles","optional","metadata","enforcement","and","column","projection","(","when","``","func","``","satisfies","the","``","DataFrameIOFunction","``","protocol",")","."]
code: def __init__(
      self,
      func,
      args=None,
      kwargs=None,
      meta=None,
      packed=False,
      enforce_metadata=False,
  ):
      self.func = func
      self.args = args
      self.kwargs = kwargs
      self.meta = meta
      self.enforce_metadata = enforce_metadata
      self.packed = packed
      self.is_dataframe_io_func = isinstance(
          self.func, DataFrameIOFunction
      )
  
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 1 to create a new _PackedArgCallable object from inherited base classes: DataFrameIOFunction with example: obj = _PackedArgCallable(func, args, kwargs, meta, packed, enforce_metadata)