class_docstr: Distributor Base Class that can handle all iterable items and calculate
  a map_function on each item separately.
  
  This is done on chunks of the data, meaning, that the DistributorBaseClass classes will chunk the data into chunks,
  distribute the data and apply the map_function functions on the items separately.
  
  Dependent on the implementation of the distribute function, this is done in parallel or using a cluster of nodes.
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docstr: Constructs the DistributorBaseClass class
docstr_tok: ["Constructs","the","DistributorBaseClass","class"]
code: def __init__(self):
      """
      Constructs the DistributorBaseClass class
      """
      raise NotImplementedError
  
imports: import itertools
  import math
  import warnings
  from collections.abc import Generator, Iterable
  from functools import partial
  from itertools import islice, repeat, takewhile
  from multiprocessing import Pool
  from tqdm import tqdm
  from tsfresh.feature_extraction.data import TsData
label_desc: Use image node_id 2 to create a new IterableDistributorBaseClass object from inherited base classes: DistributorBaseClass with example: obj = IterableDistributorBaseClass()