sentenceExtractor.py

from urllib.request import build_opener
import bs4
from nltk.tokenize import PunktSentenceTokenizer

# Pull some text from a Wikipedia entry.
# The text could also come from a string, file or whatever.

url = "https://en.wikipedia.org/wiki/Font,_Switzerland"

opener = build_opener()
opener.addheaders = [("User-agent", "Mozilla/5.0")]
request = opener.open(url)
html = request.read()
request.close()
try:
    soup = bs4.BeautifulSoup(html)
except:
    print("[ERROR] Couldn't parse:", url)
tags = ["p", "table", "td", "li", "dfn", "dd"]
all = []
for tag in tags:
    for i in soup.find_all(tag):
        text = i.text
        if tag == "table":
            found = text.splitlines()
        else:
            found = [text]
        all.extend(found)
text = "\n".join(all)

# Extract sentences from the text.

sentences = PunktSentenceTokenizer().tokenize(text)
for sentence in sentences:
    print(sentence)