class_docstr: Tokenizer that uses SpaCy.
class_docstr_tok: ["Tokenizer","that","uses","SpaCy","."]
docstr: Components that should be included in the pipeline before this component.
docstr_tok: ["Components","that","should","be","included","in","the","pipeline","before","this","component","."]
code: def required_components(cls) -> List[Type]:
      """Components that should be included in the pipeline before this component."""
      return [SpacyNLP]
  
file_path: rasa/rasa/nlu/tokenizers/spacy_tokenizer.py
imports: import typing
  from typing import Dict, Text, List, Any, Optional, Type
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.nlu.utils.spacy_utils import SpacyNLP
  from rasa.nlu.tokenizers.tokenizer import Token, Tokenizer
  from rasa.nlu.constants import SPACY_DOCS
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 1 for calling the SpacyTokenizer obj's underlying member method code with example usage: obj.required_components(cls) and returns: list