class_docstr: NLP class for default processing.
class_docstr_tok: ["NLP","class","for","default","processing","."]
docstr: Print to screen the ``Process``es invoked upon invocation
  of ``NLP()``.
docstr_tok: ["Print","to","screen","the","``","Process","``","es","invoked","upon","invocation","of","``","NLP","(",")","``","."]
code: def _print_pipelines_for_current_lang(self):
      """Print to screen the ``Process``es invoked upon invocation
      of ``NLP()``.
      """
      processes_name: List[str] = [
          process.__name__ for process in self.pipeline.processes
      ]
      processes_name_str = "`, `".join(processes_name)  # type: str
      print(
          f"Pipeline for language '{self.language.name}' (ISO: '{self.language.iso_639_3_code}'): `{processes_name_str}`."
      )
      print("")
  
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 3 for calling the NLP obj's underlying member method code with example usage: obj._print_pipelines_for_current_lang() without return types