class_docstr: A factory class that provides the document with its instance of
  `BiasedTextRank`
      
class_docstr_tok: ["A","factory","class","that","provides","the","document","with","its","instance","of","`","BiasedTextRank","`"]
docstr: Set the extension attributes on a `spaCy` [`Doc`](https://spacy.io/api/doc)
  document to create a *pipeline component* for `BiasedTextRank` as
  a stateful component, invoked when the document gets processed.
  
  See: <https://spacy.io/usage/processing-pipelines#pipelines>
  
      doc:
  a document container, providing the annotations produced by earlier stages of the `spaCy` pipeline
          
docstr_tok: ["Set","the","extension","attributes","on","a","`","spaCy","`","[","`","Doc","`","]","(","https",":","\/\/spacy.io\/api\/doc",")","document","to","create","a","*","pipeline","component","*","for","`","BiasedTextRank","`","as","a","stateful","component",",","invoked","when","the","document","gets","processed",".","See",":","<","https",":","\/\/spacy.io\/usage\/processing-pipelines","#","pipelines",">","doc",":","a","document","container",",","providing","the","annotations","produced","by","earlier","stages","of","the","`","spaCy","`","pipeline"]
code: def __call__(
      self,
      doc: Doc,
  ) -> Doc:
      """
      Set the extension attributes on a `spaCy` [`Doc`](https://spacy.io/api/doc)
      document to create a *pipeline component* for `BiasedTextRank` as
      a stateful component, invoked when the document gets processed.
  
      See: <https://spacy.io/usage/processing-pipelines#pipelines>
  
          doc:
      a document container, providing the annotations produced by earlier stages of the `spaCy` pipeline
      """
      Doc.set_extension("textrank", force=True, default=None)
      Doc.set_extension("phrases", force=True, default=[])
  
      doc._.textrank = BiasedTextRank(
          doc,
          edge_weight=self.edge_weight,
          pos_kept=self.pos_kept,
          token_lookback=self.token_lookback,
          scrubber=self.scrubber,
          stopwords=self.stopwords,
      )
  
      doc._.phrases = doc._.textrank.calc_textrank()
      return doc
  
file_path: pytextrank/pytextrank/biasedrank.py
imports: import typing
  from spacy.tokens import Doc, Token
  from .base import BaseTextRankFactory, BaseTextRank, Lemma, Phrase
label_desc: Use image node_id 1 for calling the BiasedTextRankFactory obj's underlying member method code with example usage: obj.__call__(doc) and returns: doc