class_docstr: NLP class for default processing.
class_docstr_tok: ["NLP","class","for","default","processing","."]
docstr: Returns an instance of a process from a memoized hash.
  An un-instantiated process is created and stashed in the cache.
docstr_tok: ["Returns","an","instance","of","a","process","from","a","memoized","hash",".","An","un-instantiated","process","is","created","and","stashed","in","the","cache","."]
code: def _get_process_object(
      self, process_object: Type[Process]
  ) -> Process:
      """
      Returns an instance of a process from a memoized hash.
      An un-instantiated process is created and stashed in the cache.
      """
      with NLP.process_lock:
          a_process = NLP.process_objects.get(process_object, None)
          if a_process:
              return a_process
          else:
              a_process = process_object(self.language.iso_639_3_code)
              NLP.process_objects[process_object] = a_process
              return a_process
  
file_path: cltk/src/cltk/nlp.py
imports: from threading import Lock
  from typing import List, Type
  import cltk
  from cltk.core.data_types import Doc, Language, Pipeline, Process
  from cltk.core.exceptions import UnimplementedAlgorithmError
  from cltk.languages.pipelines import AkkadianPipeline, ArabicPipeline, AramaicPipeline, ChinesePipeline, CopticPipeline, GothicPipeline, GreekPipeline, HindiPipeline, LatinPipeline, MiddleEnglishPipeline, MiddleFrenchPipeline, MiddleHighGermanPipeline, OCSPipeline, OldEnglishPipeline, OldFrenchPipeline, OldNorsePipeline, PaliPipeline, PanjabiPipeline, SanskritPipeline
  from cltk.languages.utils import get_lang
label_desc: Use image node_id 6 for calling the NLP obj's underlying member method code with example usage: obj._get_process_object(process_object) and returns: a_process, a_process