class_docstr: Create a doc instance of text, obtain cleaned, readable text and
  metadata from this doc.
  
  Properties:
  raw: incoming, unedited text
  language: 2-letter code for the language of the text
  is_detected_language: is the language detected or specified beforehand
  is_reliable_language: is the language specified or was it reliably detected
  hint_language: language you expect your text to be
  _spacy_nlps: nested dictionary {lang: {model_id: model}} with loaded spacy language modules
docstr: Loads the default spacy doc or creates one if necessary
  
  >>> from textpipe.doc import Doc
  >>> doc = Doc('Test sentence for testing text')
  >>> type(doc._spacy_doc)
  <class 'spacy.tokens.doc.Doc'>
docstr_tok: ["Loads","the","default","spacy","doc","or","creates","one","if","necessary",">",">",">","from","textpipe.doc","import","Doc",">",">",">","doc","=","Doc","(","'Test","sentence","for","testing","text","'",")",">",">",">","type","(","doc._spacy_doc",")","<","class","'spacy.tokens.doc.Doc","'",">"]
code: def _spacy_doc(self):
      """
      Loads the default spacy doc or creates one if necessary
  
      >>> from textpipe.doc import Doc
      >>> doc = Doc('Test sentence for testing text')
      >>> type(doc._spacy_doc)
      <class 'spacy.tokens.doc.Doc'>
      """
      lang = (
          self.language
          if self.is_reliable_language
          else self.hint_language
      )
  
      return self._load_spacy_doc(lang)
  
imports: import functools
  import re
  import unicodedata
  from collections import Counter
  from urllib.parse import urlparse
  import cld2
  import numpy
  import spacy
  import spacy.matcher
  import textacy
  import textacy.ke
  import textacy.text_utils
  from bs4 import BeautifulSoup
  from datasketch import MinHash
  from gensim.models.keyedvectors import KeyedVectors
  from gensim.summarization.summarizer import summarize
  from textpipe.data.emoji import EMOJI_TO_UNICODE_NAME, EMOJI_TO_SENTIMENT
  from textpipe.wrappers import RedisKeyedVectors
  from textpipe.util import getattr_
label_desc: Use image node_id 5 for calling the Doc obj's underlying member method code with example usage: obj._spacy_doc() and returns: self