class_docstr: HDF5 Function-Wrapper Class
  
  Reads HDF5 data from disk to produce a partition (given a key).
class_docstr_tok: ["HDF5","Function-Wrapper","Class","Reads","HDF5","data","from","disk","to","produce","a","partition","(","given","a","key",")","."]
code: def __init__(self, columns, dim, lock, common_kwargs):
      self._columns = columns
      self.lock = lock
      self.common_kwargs = common_kwargs
      self.dim = dim
      if columns and dim > 1:
          self.common_kwargs = merge(
              common_kwargs, {"columns": columns}
          )
  
imports: from __future__ import annotations
  import os
  import uuid
  from fnmatch import fnmatch
  from glob import glob
  from warnings import warn
  import pandas
  from fsspec.utils import build_name_function, stringify_path
  from tlz import merge
  from dask import config
  from dask.base import compute_as_if_collection, get_scheduler, named_schedulers, tokenize
  from dask.dataframe.backends import dataframe_creation_dispatch
  from dask.dataframe.core import DataFrame, Scalar
  from dask.dataframe.io.io import _link, from_map
  from dask.dataframe.io.utils import DataFrameIOFunction, SupportsLock
  from dask.highlevelgraph import HighLevelGraph
  from dask.utils import get_scheduler_lock
  from dask.dataframe.core import _Frame
label_desc: Use image node_id 1 to create a new HDFFunctionWrapper object from inherited base classes: DataFrameIOFunction with example: obj = HDFFunctionWrapper(columns, dim, lock, common_kwargs)