class_docstr: CSV Function-Wrapper Class
  Reads CSV data from disk to produce a partition (given a key).
class_docstr_tok: ["CSV","Function-Wrapper","Class","Reads","CSV","data","from","disk","to","produce","a","partition","(","given","a","key",")","."]
code: def __init__(
      self,
      full_columns,
      columns,
      colname,
      head,
      header,
      reader,
      dtypes,
      enforce,
      kwargs,
  ):
      self.full_columns = full_columns
      self._columns = columns
      self.colname = colname
      self.head = head
      self.header = header
      self.reader = reader
      self.dtypes = dtypes
      self.enforce = enforce
      self.kwargs = kwargs
  
imports: from __future__ import annotations
  import os
  from collections.abc import Mapping
  from io import BytesIO
  from warnings import catch_warnings, simplefilter, warn
  import numpy
  import pandas
  from fsspec.compression import compr
  from fsspec.core import get_fs_token_paths
  from fsspec.core import open
  from fsspec.core import open_files
  from fsspec.utils import infer_compression
  from pandas.api.types import CategoricalDtype, is_datetime64_any_dtype, is_float_dtype, is_integer_dtype, is_object_dtype
  from dask.base import tokenize
  from dask.bytes import read_bytes
  from dask.core import flatten
  from dask.dataframe.backends import dataframe_creation_dispatch
  from dask.dataframe.io.io import from_map
  from dask.dataframe.io.utils import DataFrameIOFunction
  from dask.dataframe.utils import clear_known_categories
  from dask.delayed import delayed
  from dask.utils import asciitable, parse_bytes
  from dask.dataframe.core import _Frame
label_desc: Use image node_id 1 to create a new CSVFunctionWrapper object from inherited base classes: DataFrameIOFunction with example: obj = CSVFunctionWrapper(full_columns, columns, colname, head, header, reader, dtypes, enforce, kwargs)