class_docstr: Reads LUIS training data.
class_docstr_tok: ["Reads","LUIS","training","data","."]
code: def _extract_regex_features(
      js: Dict[Text, Any]
  ) -> List[Dict[Text, Any]]:
      regex_features: List[Dict[Text, Any]] = []
  
      for r in js.get("regex_features", []):
          if r.get("activated", False):
              regex_features.append(
                  {"name": r.get("name"), "pattern": r.get("pattern")}
              )
  
      # LUIS removed `regex_features` and exports regular expressions in `
      # regex_entities` now:
      # https://stackoverflow.com/questions/48170631/what-happened-to-the-regex-features # noqa: E501
      for r in js.get("regex_entities", []):
          regex_features.append(
              {"name": r.get("name"), "pattern": r.get("regexPattern")}
          )
  
      return regex_features
  
file_path: rasa/rasa/shared/nlu/training_data/formats/luis.py
imports: import logging
  from typing import Any, Dict, List, Text
  from rasa.shared.nlu.constants import TEXT, INTENT, ENTITIES, ENTITY_ATTRIBUTE_TYPE, ENTITY_ATTRIBUTE_ROLE, ENTITY_ATTRIBUTE_VALUE, ENTITY_ATTRIBUTE_START, ENTITY_ATTRIBUTE_END, NO_ENTITY_TAG
  from rasa.shared.nlu.training_data.formats.readerwriter import JsonTrainingDataReader
  import rasa.shared.utils.io
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 1 for calling the LuisReader obj's underlying member method code with example usage: obj._extract_regex_features(js) and returns: regex_features