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: Provided or detected language of a text
  
  >>> from textpipe.doc import Doc
  >>> Doc('Test sentence for testing text').language
  'en'
  >>> Doc('Test sentence for testing text', language='en').language
  'en'
  >>> Doc('Test', hint_language='nl').language
  'nl'
docstr_tok: ["Provided","or","detected","language","of","a","text",">",">",">","from","textpipe.doc","import","Doc",">",">",">","Doc","(","'Test","sentence","for","testing","text","'",")",".language","'en'",">",">",">","Doc","(","'Test","sentence","for","testing","text","'",",","language='en","'",")",".language","'en'",">",">",">","Doc","(","'Test","'",",","hint_language='nl","'",")",".language","'nl","'"]
code: def language(self):
      """
      Provided or detected language of a text
  
      >>> from textpipe.doc import Doc
      >>> Doc('Test sentence for testing text').language
      'en'
      >>> Doc('Test sentence for testing text', language='en').language
      'en'
      >>> Doc('Test', hint_language='nl').language
      'nl'
      """
      if not self._language:
          (
              self._is_reliable_language,
              self._language,
          ) = self.detect_language(self.hint_language)
      return self._language
  
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 2 for calling the Doc obj's underlying member method code with example usage: obj.language() and returns: self