class_docstr: Parameters for random dataset generation
  
  Attributes
  ----------
  num_rows : int
      Number of rows to generate
  column_parameters : List[ColumnParams]
      ColumnParams for each column
  seed : int or None, default None
      Seed for random data generation
class_docstr_tok: ["Parameters","for","random","dataset","generation","Attributes","--","--","--","--","--","num_rows",":","int","Number","of","rows","to","generate","column_parameters",":","List","[","ColumnParams","]","ColumnParams","for","each","column","seed",":","int","or","None",",","default","None","Seed","for","random","data","generation"]
code: def __init__(
      self,
      num_rows=2048,
      column_parameters=None,
      seed=None,
  ):
      self.num_rows = num_rows
      if column_parameters is None:
          column_parameters = []
      self.column_parameters = column_parameters
      self.seed = seed
  
imports: import copy
  import random
  import string
  import uuid
  from multiprocessing import Pool
  import numpy
  import pandas
  import pyarrow
  from pyarrow import parquet
  import cudf
  from cudf.utils.dtypes import np_to_pa_dtype
label_desc: Use image node_id 1 to create a new Parameters object  with example: obj = Parameters(num_rows, column_parameters, seed)