Simple library to extract parts of HTML file, by tags names. Alternative to Beautiful Soup for simple usages. Useful to process big files or a lot of files (web scraping). The selection is only possible by tag type.
Python 2 and Python 3
html = """
<!DOCTYPE html>
<html>
<body>
<h1>Title 1</h1>
<p>Paragraph 1<br/></p>
<p>Paragraph <b>2</b></p>
<!-- <p>Paragraph in comment</p> -->
</body>
</html>
"""
html_by_tags = fastHtmlExtract.extract(html, ['p', 'h1'])
print(html_by_tags)Output :
{
'p': [
'<p>Paragraph 1<br/></p>',
'<p>Paragraph <b>2</b></p>'
],
'h1': [
'<h1>Title 1</h1>'
]
}
html = """
<!DOCTYPE html>
<html>
<body>
<h1>Title 1</h1>
<p>Paragraph 1<br/></p>
<p>Paragraph <b>2</b></p>
<!-- <p>Paragraph in comment</p> -->
</body>
</html>
"""
count_by_tags = fastHtmlExtract.count(html, ['p', 'h1'])
print(count_by_tags)Output :
{
'p': 2,
'h1': 1
}
html = """
<!DOCTYPE html>
<html>
<body>
<h1>Title 1</h1>
<p>Paragraph 1<br/></p>
<p>Paragraph <b>2</b></p>
<!-- <p>Paragraph in comment</p> -->
</body>
</html>
"""
text = fastHtmlExtract.get_text(html)
print(text)Output :
Title 1 Paragraph 1 Paragraph 2
html = """
<!DOCTYPE html>
<html>
<body>
<h1>Title 1</h1>
<p>Paragraph 1<br/></p>
<p>Paragraph <b>2</b></p>
<!-- <p>Paragraph in comment</p> -->
</body>
</html>
"""
html_elements = fastHtmlExtract.extract(html, ['p'])
paragraphs = html_elements['p']
for p in paragraphs:
text = fastHtmlExtract.get_text(p)
print(text)Output :
Paragraph 1
Paragraph 2
import fastHtmlExtract
import urllib
import re
from bs4 import BeautifulSoup
import timeit
def fast_extract_titles(html):
titles = []
html_elements = fastHtmlExtract.extract(html, ['h1', 'h2', 'h3'])
titles_html = html_elements['h1'] + html_elements['h2'] + html_elements['h3']
for title_html in titles_html:
text = fastHtmlExtract.get_text(title_html)
titles.append(text)
return titles
def beautiful_soup_extract_titles(html):
titles = []
soup = BeautifulSoup(html, 'html.parser')
titles_bf = soup.find_all(re.compile(r'(h1|h2|h3)'))
for title_bf in titles_bf:
text = title_bf.get_text(' ').encode('utf8')
titles.append(text)
return titles
if __name__ == "__main__":
url = 'https://en.wikipedia.org/wiki/List_of_j%C5%8Dy%C5%8D_kanji'
html = urllib.urlopen(url).read()
# Compare result
titles_1 = fast_extract_titles(html)
titles_2 = beautiful_soup_extract_titles(html)
print(titles_1)
# ['List of j\xc5\x8dy\xc5\x8d kanji', 'Contents', 'List of characters [ edit ]', 'See also [ edit ]', 'Notes [ edit ]', 'External links [ edit ]', 'Navigation menu', 'Personal tools', 'Namespaces', 'Variants', 'Views', 'More', 'Search', 'Navigation', 'Interaction', 'Tools', 'Print/export', 'In other projects', 'Languages']
print(titles_2)
# ['List of j\xc5\x8dy\xc5\x8d kanji', 'Contents', 'List of characters [ edit ]', 'See also [ edit ]', 'Notes [ edit ]', 'External links [ edit ]', 'Navigation menu', 'Personal tools', 'Namespaces', '\n Variants \n', 'Views', 'More', '\n Search \n', 'Navigation', 'Interaction', 'Tools', 'Print/export', 'In other projects', 'Languages']
# Compare performances
print(timeit.timeit('fast_extract_titles(html)', number=1000, setup="from __main__ import fast_extract_titles, html"))
# 2.17549295306
print(timeit.timeit('beautiful_soup_extract_titles(html)', number=1000, setup="from __main__ import beautiful_soup_extract_titles, html"))
# 23.444286399In this case, for a simple extraction, fast_extract_titles is 10 times faster.