code: def read_csv_without_blocksize(path, **kwargs):
      """Read entire CSV with optional compression (gzip/zip)
  
      Parameters
      ----------
      path : str
          path to files (support for glob)
      """
      if isinstance(path, list):
          filenames = path
      elif isinstance(path, str):
          filenames = sorted(glob(path))
      elif hasattr(path, "__fspath__"):
          filenames = sorted(glob(path.__fspath__()))
      else:
          raise TypeError(f"Path type not understood:{type(path)}")
  
      name = "read-csv-" + tokenize(path, **kwargs)
  
      meta_kwargs = kwargs.copy()
      if "skipfooter" in meta_kwargs:
          meta_kwargs.pop("skipfooter")
      if "nrows" in meta_kwargs:
          meta_kwargs.pop("nrows")
      # Read "head" of first file (first 5 rows).
      # Convert to empty df for metadata.
      meta = cudf.read_csv(filenames[0], nrows=5, **meta_kwargs).iloc[
          :0
      ]
  
      graph = {
          (name, i): (apply, cudf.read_csv, [fn], kwargs)
          for i, fn in enumerate(filenames)
      }
  
      divisions = [None] * (len(filenames) + 1)
  
      return dd.core.new_dd_object(graph, name, meta, divisions)
  
file_path: cudf/python/dask_cudf/dask_cudf/io/csv.py
imports: import os
  from glob import glob
  from warnings import warn
  from fsspec.utils import infer_compression
  from dask import dataframe
  from dask.base import tokenize
  from dask.dataframe.io.csv import make_reader
  from dask.utils import apply, parse_bytes
  import cudf
label_desc: Use image node_id 4 for calling a global function with example usage: read_csv_without_blocksize(path) and returns: dd