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Remove HTML markup from the given string.

:param html: the HTML string to be cleaned
:type html: str
:rtype: str

        def clean_html(html):
    """
    Remove HTML markup from the given string.

    :param html: the HTML string to be cleaned
    :type html: str
    :rtype: str
    """

    # First we remove inline JavaScript/CSS:
    cleaned = re.sub(r"(?is)<(script|style).*?>.*?()", "", html.strip())
    # Then we remove html comments. This has to be done before removing regular
    # tags since comments can contain '>' characters.
    cleaned = re.sub(r"(?s)[\n]?", "", cleaned)
    # Next we can remove the remaining tags:
    cleaned = re.sub(r"(?s)<.*?>", " ", cleaned)
    # Finally, we deal with whitespace
    cleaned = re.sub(r" ", " ", cleaned)
    cleaned = re.sub(r"  ", " ", cleaned)
    cleaned = re.sub(r"  ", " ", cleaned)
    return cleaned.strip()
        


src/n/l/nltk-examples-HEAD/src/book/ch03.py   nltk-examples(Download)
  html = f.read()
  f.close()
  raw = nltk.clean_html(html)
  tokens = nltk.word_tokenize(raw)
  text = nltk.Text(tokens[96:399])
  content = post.content[0].value
  print "title,countent...=", post.title, content[:70]
  tokens = nltk.word_tokenize(nltk.clean_html(content))
  print "tokens=", tokens
 

src/t/r/trivial_pursuit-HEAD/old/starter_code.py   trivial_pursuit(Download)
def getTokens(urls):
    combinedtokens = []
    for url in urls:
        html = urlopen(url).read()
        raw = nltk.clean_html(html)

src/s/o/sotumachine-HEAD/speechgen/train_all_presidents.py   sotumachine(Download)
def parse_transcript(transcript_filename):
    speech = []
    with open(transcript_filename) as transcript:
        for line in transcript:
            raw = nltk.clean_html(line.strip())
            while not raw:
                line = transcript.readline()
                raw = nltk.clean_html(line.strip())
            print raw+'\n'
    raw_input('\nTo continue press enter')
                for line in speech:
                    sent_count = 0
                    line = nltk.clean_html(line.strip())
                    if line:
                        para_count += 1

src/t/r/trivial_pursuit-HEAD/trivialpursuitfunctions.py   trivial_pursuit(Download)
        # req = urllib2.Request(url,None,headers)
        # html = urlopen(req).read()
        raw = nltk.clean_html(html)
        combinedtokens += nltk.word_tokenize(raw)
    # may need to adjust 0 value here

src/w/i/wiki-network-HEAD/countwords-groups-sender.py   wiki-network(Download)
def freq_dist(cls, msg):
    global fd
 
    tokens = tokenizer.tokenize(nltk.clean_html(msg.lower()))
 

src/t/r/trivial_pursuit-HEAD/old/fpnlp.py   trivial_pursuit(Download)
        for url in urls:
            html = urlopen(url).read()
            raw = nltk.clean_html(html)
            combinedtokens += nltk.word_tokenize(raw)
        combinedtokens = [t for t in combinedtokens if len(t) > 1 and t.lower() not in ignored_words]

src/t/r/trivial_pursuit-HEAD/old/fpnlp1125921draft.py   trivial_pursuit(Download)
    for url in urls:
        html = urlopen(url).read()
        raw = nltk.clean_html(html)
        combinedtokens += nltk.word_tokenize(raw)
    combinedtokens = [t for t in combinedtokens if len(t) > 2 and t.lower() not in ignored_words]

src/w/i/wiki-network-HEAD/word_frequency.py   wiki-network(Download)
            ## this tag is empty
            return
        tokens = self.tokenizer.tokenize(nltk.clean_html(text.lower()))
 
        ##TODO: togliere questo limite sulla lunghezza?

src/n/l/NLP_GDGCairo2013-HEAD/wikianalysis.py   NLP_GDGCairo2013(Download)
    fd = opener.open(url)
    wiki_html = fd.read()
    wiki_text = nltk.clean_html(wiki_html)
    wiki_text = removeNonAscii(wiki_text)
    wiki_text = wiki_text.lower() 

src/s/o/sotumachine-HEAD/speechgen/models.py   sotumachine(Download)
        else:
            text = random.choice(self._stats['preambles'])
            p = nltk.word_tokenize(nltk.clean_html(text))
            p.append('~SENT~')
            return p

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