text: import numpy as np
  import os
  import pandas as pd
  
  from dama.abc.driver import AbsDriver
  from dama.abc.conn import AbsConn
  from dama.connexions.core import DaskDfConn
  from dama.utils.files import rm
  from dama.utils.logger import log_config
  from dama.utils.core import Chunks, Shape
  from dask.dataframe.io.csv import make_reader
  
  log = log_config(__name__)
  
  
  class CSV(AbsDriver):
      persistent = True
      ext = "csv"
      data_tag = None
      metadata_tag = "metadata"
  
      def __getitem__(self, item):
          return self.conn[item]
  
      def __setitem__(self, key, value):
          self.conn[key] = value
  
      def absconn(self):
          pass
  
      def manager(self, chunks: Chunks) -> AbsConn:
          return DaskDfConn(self.conn)
  
      def open(self):
          if self.conn is None:
              if self.mode == "r":
                  self.conn = make_reader(pd.read_csv, 'read_csv', 'CSV')(self.url)
              else:
                  raise NotImplementedError
              self.attrs = {}
          return self
  
      def close(self):
          self.conn = None
          self.attrs = None
  
      def require_dataset(self, level: str, group: str, shape: tuple, dtype: np.dtype) -> None:
          pass
  
      def destroy(self):
          rm(self.url)
  
      def exists(self):
          return os.path.exists(self.url)
  
      def set_schema(self, dtypes: np.dtype, idx: list = None, unique_key=None):
          pass
  
      def set_data_shape(self, shape):
          pass
  
      @property
      def dtypes(self) -> np.dtype:
          return np.dtype([(col, np.dtype(dtype)) for col, dtype in self.conn.dtypes.items()])
  
      def spaces(self) -> list:
          return list(self.conn.columns)
  
      def shape(self) -> Shape:
          length = self.conn.shape[0].compute()
          shape = dict([(group, (length,)) for group in self.groups])
          return Shape(shape)
  