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: Computes similarity for two documents.
  Only minhash Jaccard similarity is implemented.
  
  >>> from textpipe.doc import Doc
  >>> doc1 = Doc('Sentence for computing the minhash')
  >>> doc2 = Doc('Sentence for computing the similarity')
  >>> doc1.similarity(doc2)
  0.7265625
docstr_tok: ["Computes","similarity","for","two","documents",".","Only","minhash","Jaccard","similarity","is","implemented",".",">",">",">","from","textpipe.doc","import","Doc",">",">",">","doc1","=","Doc","(","'Sentence","for","computing","the","minhash","'",")",">",">",">","doc2","=","Doc","(","'Sentence","for","computing","the","similarity","'",")",">",">",">","doc1.similarity","(","doc2",")","0.7265625"]
code: def similarity(
      self, other_doc, metric="jaccard", hash_method="minhash"
  ):
      """
      Computes similarity for two documents.
      Only minhash Jaccard similarity is implemented.
  
      >>> from textpipe.doc import Doc
      >>> doc1 = Doc('Sentence for computing the minhash')
      >>> doc2 = Doc('Sentence for computing the similarity')
      >>> doc1.similarity(doc2)
      0.7265625
      """
      if hash_method == "minhash" and metric == "jaccard":
          hash1 = MinHash(hashvalues=self.minhash)
          hash2 = MinHash(hashvalues=other_doc.minhash)
          return hash1.jaccard(hash2)
  
      raise NotImplementedError(
          f"Metric/hash method combination {metric}"
          f"/{hash_method} is not implemented as similarity metric"
      )
  
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 25 for calling the Doc obj's underlying member method code with example usage: obj.similarity(other_doc, metric, hash_method) and returns: hash1