class_docstr: Interface for simple dictionary-based dataset format. The dictionary
  keys correspond to the column (i.e. dimension) names and the values
  are collections representing the values in that column.
class_docstr_tok: ["Interface","for","simple","dictionary-based","dataset","format",".","The","dictionary","keys","correspond","to","the","column","(","i.e",".","dimension",")","names","and","the","values","are","collections","representing","the","values","in","that","column","."]
code: def validate(cls, dataset, vdims=True):
      dim_types = "all" if vdims else "key"
      dimensions = dataset.dimensions(dim_types, label="name")
      not_found = [d for d in dimensions if d not in dataset.data]
      if not_found:
          raise DataError(
              "Following columns specified as dimensions "
              "but not found in data: %s" % not_found,
              cls,
          )
      lengths = [
          (
              dim,
              1
              if isscalar(dataset.data[dim])
              else len(dataset.data[dim]),
          )
          for dim in dimensions
      ]
      if len({l for d, l in lengths if l > 1}) > 1:
          lengths = ", ".join(["%s: %d" % l for l in sorted(lengths)])
          raise DataError(
              "Length of columns must be equal or scalar, "
              "columns have lengths: %s" % lengths,
              cls,
          )
  
imports: from collections import OrderedDict, defaultdict
  import numpy
  from ..None import util
  from ..dimension import dimension_name
  from ..element import Element
  from ..ndmapping import NdMapping, item_check, sorted_context
  from ..util import isscalar
  from .interface import DataError, Interface
label_desc: Use image node_id 3 for calling the DictInterface obj's underlying member method code with example usage: obj.validate(cls, dataset, vdims) without return types