docstr: Generate a list of *n* sequences of varying size between *min_size*
  and *max_size*, with *none_prob* probability of an entry being None.
  The base material for each sequence is obtained by calling
  `random_factory(<some size>)`
docstr_tok: ["Generate","a","list","of","*","n","*","sequences","of","varying","size","between","*","min_size","*","and","*","max_size","*",",","with","*","none_prob","*","probability","of","an","entry","being","None",".","The","base","material","for","each","sequence","is","obtained","by","calling","`","random_factory","(","<","some","size",">",")","`"]
code: def _generate_varying_sequences(
      self, random_factory, n, min_size, max_size, none_prob
  ):
      """
      Generate a list of *n* sequences of varying size between *min_size*
      and *max_size*, with *none_prob* probability of an entry being None.
      The base material for each sequence is obtained by calling
      `random_factory(<some size>)`
      """
      base_size = 10000
      base = random_factory(base_size + max_size)
      data = []
      for i in range(n):
          off = self.rnd.randint(base_size)
          if min_size == max_size:
              size = min_size
          else:
              size = self.rnd.randint(min_size, max_size + 1)
          data.append(base[off : off + size])
      self.sprinkle_nones(data, none_prob)
      assert len(data) == n
      return data
  
imports: import codecs
  import decimal
  from functools import partial
  import itertools
  import sys
  import unicodedata
  import numpy
  import pyarrow
label_desc: Use image node_id 9 for calling the BuiltinsGenerator obj's underlying member method code with example usage: obj._generate_varying_sequences(random_factory, n, min_size, max_size, none_prob) and returns: data