class_docstr: The definition of an operation.
  
  This class contains all the information needed to run an operation, except
  the number of inputs and their values.  A subclass should document
  
    - How many inputs it expects, and what they should contain.
    - What it outputs, as a function of its inputs.
  
  An OperationDef is just a specification and does not contain the actual
  computation.
docstr: If True, means that this operation can be applied on partitioned data.
  
  Being able to be applied on partitioned data means that partitioning the
  data, running this operation on each of the data subsets independently, and
  then having the next operation get the flattened results as inputs would be
  equivalent to running this operation on the entire data and passing the
  result to the next operation.
  
  Returns:
    A bool indicating whether or not this operation is partitionable.
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code: def is_partitionable(self) -> bool:
      """If True, means that this operation can be applied on partitioned data.
  
      Being able to be applied on partitioned data means that partitioning the
      data, running this operation on each of the data subsets independently, and
      then having the next operation get the flattened results as inputs would be
      equivalent to running this operation on the entire data and passing the
      result to the next operation.
  
      Returns:
        A bool indicating whether or not this operation is partitionable.
      """
      return False
  
imports: import abc
  import collections
  import dataclasses
  from typing import Any, Collection, Dict, List, Optional, Tuple
  import pydot
label_desc: Use image node_id 4 for calling the OperationDef obj's underlying member method code with example usage: obj.is_partitionable() and returns: False