class_docstr: Python impl of TextRank by Milhacea, et al., as a spaCy extension,
  used to extract the top-ranked phrases from a text document
class_docstr_tok: ["Python","impl","of","TextRank","by","Milhacea",",","et","al.",",","as","a","spaCy","extension",",","used","to","extract","the","top-ranked","phrases","from","a","text","document"]
code: def __init__(
      self,
      edge_weight=_EDGE_WEIGHT,
      logger=None,
      pos_kept=_POS_KEPT,
      scrubber=default_scrubber,
      token_lookback=_TOKEN_LOOKBACK,
  ):
      self.edge_weight = edge_weight
      self.logger = logger
      self.pos_kept = pos_kept
      self.scrubber = scrubber
      self.stopwords = defaultdict(list)
      self.token_lookback = token_lookback
  
      self.doc = None
      self.reset()
  
imports: from .base import BaseTextRank
  from .positionrank import PositionRank
  from collections import defaultdict, OrderedDict
  from math import sqrt
  from spacy.tokens import Doc
  import graphviz
  import json
  import logging
  import networkx
  import os
  import os.path
  import re
  import spacy
  import string
  import sys
  import time
  import unicodedata
label_desc: Use image node_id 1 to create a new TextRank object  with example: obj = TextRank(edge_weight, logger, pos_kept, scrubber, token_lookback)