code: def clean_page(
      page: PageFeatures,
      citation_regex,
      counter_inc_fn=None,
      min_words_per_line=_MIN_WORDS_PER_LINE,
      min_num_sentences=_MIN_NUM_SENTENCES,
      max_word_length=_MAX_WORD_LENGTH,
      line_delimiter="\n",
  ) -> Iterable[PageFeatures]:
      """Cleans a CommonCrawl page, yielding nothing if it should be skipped.
  
      Cleaning removes lines with no end marks or with too few words. After line
      filtering, pages are filtered out if they have too few sentences based on a
      simple count of end marks.
  
      Args:
        page: the features of the page.
        citation_regex: Regex to use for finding Wikipedia-like citations to filter.
        counter_inc_fn: function, a function taking the name of a counter to be
          incremented and the (optional) amount. Defaults to a beam Metric counter.
        min_words_per_line: int, the minimum number of words a line needs to not be
          removed.
        min_num_sentences: int, the minimum number of sentences a page needs to not
          be skipped.
        max_word_length: int, the maximum number of characters allowed in a word.
          Lines containing a word with too many characters are removed.
        line_delimiter: str, the delimiter used to separate and join lines.
  
      Yields:
        The url and cleaned text for the page.
      """
      text = page.text
  
      if not counter_inc_fn:
          counter_inc_fn = get_counter_inc_fn("clean-page")
  
      lines = text.splitlines()
      valid_lines = []
      num_sentences = 0
  
      def line_has_too_long_word(line):
          for word in line.split():
              if len(word) > max_word_length:
                  return True
          return False
  
      for line in lines:
          line = line.strip()
          if line_has_too_long_word(line):
              counter_inc_fn("line-filtered:too_long_word")
              continue
          line = citation_regex.sub("", line)
          if not line.endswith(_END_MARKS) or line.endswith(_ELLIPSIS):
              counter_inc_fn("line-filtered:no_endmark")
              continue
          if len(line.split()) < min_words_per_line:
              counter_inc_fn("line-filtered:too_short")
              continue
          line_lower = line.lower()
          # Remove documents which contain lorem ipsum
          if "lorem ipsum" in line_lower:
              counter_inc_fn("filtered:loremipsum")
              return
          # Remove "javascript must be enabled" notices
          if "javascript" in line_lower:
              counter_inc_fn("line-filtered:javascript")
              continue
          # Remove docs which probably contain javascript code
          if "{" in line:
              counter_inc_fn("filtered:squigglybracket")
              return
          # Remove policy lines
          if any(p in line_lower for p in _POLICY_SUBSTRINGS):
              counter_inc_fn("line-filtered:policy")
              continue
          num_sentences += len(_get_sentences(line))
          valid_lines.append(line)
          counter_inc_fn("line-passed")
  
      if num_sentences < min_num_sentences:
          counter_inc_fn("filtered:too_few_sentences")
          return
      counter_inc_fn("passed")
      yield dataclasses.replace(
          page, text=line_delimiter.join(valid_lines).strip()
      )
  
imports: import dataclasses
  import functools
  import gzip
  import hashlib
  import heapq
  import io
  import re
  import threading
  from typing import Collection, Iterable, Mapping, Optional, Sequence, Tuple
  from absl import logging
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 8 for calling a global function with example usage: clean_page(page, citation_regex, counter_inc_fn, min_words_per_line, min_num_sentences, max_word_length, line_delimiter) and returns: False, True