class_docstr: Holds the output of a `FingerprintComponent` and is used to prune the graph.
  
  Attributes:
      output_fingerprint: A fingerprint of the node's output value.
      is_hit: `True` if node's fingerprint key exists in the cache, `False` otherwise.
docstr: Returns the internal fingerprint.
  
  If there is no fingerprint returns a random string that will never match.
docstr_tok: ["Returns","the","internal","fingerprint",".","If","there","is","no","fingerprint","returns","a","random","string","that","will","never","match","."]
code: def fingerprint(self) -> Text:
      """Returns the internal fingerprint.
  
      If there is no fingerprint returns a random string that will never match.
      """
      return self.output_fingerprint or uuid.uuid4().hex
  
imports: from __future__ import annotations
  from typing import Any, Dict, Optional, Text, Type
  import dataclasses
  import uuid
  from rasa.engine.caching import Cacheable, TrainingCache
  from rasa.engine.graph import ExecutionContext, GraphComponent, SchemaNode
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.engine.training import fingerprinting
label_desc: Use image node_id 1 for calling the FingerprintStatus obj's underlying member method code with example usage: obj.fingerprint() and returns: unknown