class_docstr: Dataset class that loads and parses graph data from CSV files.
  
  This class requires the following additional packages:
  
      - pyyaml >= 5.4.1
      - pandas >= 1.1.5
      - pydantic >= 1.9.0
  
  The parsed graph and feature data will be cached for faster reloading. If
  the source CSV files are modified, please specify ``force_reload=True``
  to re-parse from them.
  
  Parameters
  ----------
  data_path : str
      Directory which contains 'meta.yaml' and CSV files
  force_reload : bool, optional
      Whether to reload the dataset. Default: False
  verbose: bool, optional
      Whether to print out progress information. Default: True.
  ndata_parser : dict[str, callable] or callable, optional
      Callable object which takes in the ``pandas.DataFrame`` object created from
      CSV file, parses node data and returns a dictionary of parsed data. If given a
      dictionary, the key is node type and the value is a callable object which is
      used to parse data of corresponding node type. If given a single callable
      object, such object is used to parse data of all node type data. Default: None.
      If None, a default data parser is applied which load data directly and tries to
      convert list into array.
  edata_parser : dict[(str, str, str), callable], or callable, optional
      Callable object which takes in the ``pandas.DataFrame`` object created from
      CSV file, parses edge data and returns a dictionary of parsed data. If given a
      dictionary, the key is edge type and the value is a callable object which is
      used to parse data of corresponding edge type. If given a single callable
      object, such object is used to parse data of all edge type data. Default: None.
      If None, a default data parser is applied which load data directly and tries to
      convert list into array.
  gdata_parser : callable, optional
      Callable object which takes in the ``pandas.DataFrame`` object created from
      CSV file, parses graph data and returns a dictionary of parsed data. Default:
      None. If None, a default data parser is applied which load data directly and
      tries to convert list into array.
  transform : callable, optional
      A transform that takes in a :class:`~dgl.DGLGraph` object and returns
      a transformed version. The :class:`~dgl.DGLGraph` object will be
      transformed before every access.
  
  Attributes
  ----------
  graphs : :class:`dgl.DGLGraph`
      Graphs of the dataset
  data : dict
      any available graph-level data such as graph-level feature, labels.
  
  Examples
  --------
  Please refer to :ref:`guide-data-pipeline-loadcsv`.
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code: def has_cache(self):
      graph_path = os.path.join(self.save_path, self.name + ".bin")
      if os.path.exists(graph_path):
          return True
  
      return False
  
file_path: dgl/python/dgl/data/csv_dataset.py
imports: import os
  import numpy
  from ..None import backend
  from ..base import DGLError
  from .dgl_dataset import DGLDataset
  from .utils import load_graphs, save_graphs, Subset
label_desc: Use image node_id 3 for calling the CSVDataset obj's underlying member method code with example usage: obj.has_cache() and returns: False, True