115 lines
2.9 KiB
Python
115 lines
2.9 KiB
Python
import re
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from collections.abc import Iterator
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import bs4
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HTML_TAGS_MOSTLY_CONTENTLESS: set[str] = {
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'style',
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'svg',
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'link',
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'br',
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'math',
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'canvas',
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}
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HTML_TAGS_WITH_LITTLE_CONTENT: set[str] = {
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'head',
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'script',
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'meta',
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} | HTML_TAGS_MOSTLY_CONTENTLESS
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def normalize_text(text: str) -> bytes:
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text = text.replace('\t', ' ')
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text = text.replace('\r', '')
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text = re.sub(r'\s*\n\s*\n\s*', '\n\n', text)
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text = re.sub(r' +', ' ', text)
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text = re.sub(r'^\s+', '', text)
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text = re.sub(r'\s+$', '', text)
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return text.encode('utf-8')
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def normalize_soup_bs4(soup: bs4.BeautifulSoup) -> bs4.BeautifulSoup:
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for comment in soup(text=lambda text: isinstance(text, bs4.Comment)):
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comment.extract()
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del comment
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for element_name in HTML_TAGS_WITH_LITTLE_CONTENT:
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for script_elements in soup(element_name):
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script_elements.decompose()
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del element_name
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soup.smooth()
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return soup
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def normalize_soup_lxml(soup):
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for element_name in HTML_TAGS_WITH_LITTLE_CONTENT:
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for script_elements in soup.cssselect(element_name):
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script_elements.drop_tree()
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del script_elements
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del element_name
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return soup
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def normalize_soup(soup) -> bytes:
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if isinstance(soup, bs4.BeautifulSoup):
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text = normalize_soup_bs4(soup).get_text()
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else:
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text = normalize_soup_lxml(soup).text_content()
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return normalize_text(text)
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def data_attributes_of_element(e) -> Iterator[str]:
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for attr_key in list(e.attrs.keys()):
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if attr_key.startswith('data-'):
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yield attr_key
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def has_data_attribute(e) -> bool:
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for _ in data_attributes_of_element(e):
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return True
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return False
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def normalize_soup_slightly(
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soup: bs4.BeautifulSoup,
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classes=True,
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scripts=True,
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comments=True,
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data_attributes=True,
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) -> bs4.BeautifulSoup:
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"""Perform soup normalization."""
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# Little if any content
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for tag in HTML_TAGS_MOSTLY_CONTENTLESS:
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for e in soup.select(tag):
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e.decompose()
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if classes:
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for e in soup.find_all(class_=True):
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del e['class']
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for e in soup.find_all('script', src=True):
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e.decompose()
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for e in soup.find_all(style=True):
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del e['style']
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for e in soup.select('a'):
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del e['height'], e['target'], e['rel'], e['onclick']
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for e in soup.select('a[href=""]'):
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del e['href']
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if scripts:
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for e in soup.find_all('script'):
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e.decompose()
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if comments:
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for c in soup.find_all(string=lambda text: isinstance(text, bs4.Comment)):
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c.extract()
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if data_attributes:
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for e in soup.find_all(has_data_attribute):
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for attr_key in data_attributes_of_element(e):
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del e[attr_key], attr_key
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del e
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soup.smooth()
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return soup
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