def extract_article_information_from_html(html):
"""
This methods gets a website the HTML as string and extracts the text of
the article
:param html: a HTML object from package requests
:return: the article information
"""
article_information = {}
# run with newspaper
article_newspaper = Article('')
article_newspaper.set_html(html)
article_newspaper.parse()
article_information["summary"] = article_newspaper.summary
article_information["author"] = str(article_newspaper.authors).strip('[]')
article_information["tags"] = article_newspaper.tags
article_information["title"] = article_newspaper.title
newspaper_text = article_newspaper.text
# run with newsplease
# article_newsplease = NewsPlease.from_html(html)
# newsplease_text = article_newsplease.cleaned_text
# run with goose
goose_extractor = Goose()
goose_extractor = goose_extractor.extract(raw_html=html)
article_goose = goose_extractor.cleaned_text
if len(newspaper_text.split(" ")) > len(article_goose.split(" ")):
article_information["text"] = newspaper_text
else:
article_information["text"] = article_goose
return article_information
def extract(self, item):
"""Creates an instance of Article without a Download and returns an ArticleCandidate with the results of
parsing the HTML-Code.
:param item: A NewscrawlerItem to parse.
:return: ArticleCandidate containing the recovered article data.
"""
article_candidate = ArticleCandidate()
article_candidate.extractor = self._name()
article = Article('')
article.set_html(item['spider_response'].body)
article.parse()
article_candidate.title = article.title
article_candidate.description = article.meta_description
article_candidate.text = article.text
article_candidate.topimage = article.top_image
article_candidate.author = article.authors
if article.publish_date:
try:
article_candidate.publish_date = article.publish_date.strftime(
'%Y-%m-%d %H:%M:%S')
except ValueError as exception:
self.log.debug(
'%s: Newspaper failed to extract the date in the supported format,'
'Publishing date set to None' % item['url'])
article_candidate.language = article.meta_lang
return article_candidate
def read_other_article(htmltext):
"""
Processes articles other than the ones for which specific rules have been written
:param htmltext: the htmltext of the article
:return:
"""
article = Article('') # so that you can use local files with newspaper3k
article.set_html(htmltext)
article.parse()
authors = article.authors # sometimes is extracts stuff like "Reporter for Fox News. Follow Her on Twitter.."
date = article.publish_date # TODO: date not extracted here properly
if date is not None:
date = article.publish_date.strftime('%d/%m/%Y')
text = article.text
# text = "".join(i for i in text if i != '\n')
title = article.title
publisher = 'other'
if determine_publisher(htmltext) == ArticleType.CNN:
publisher = 'cnn'
result_dict = {
'title': title,
'authors': authors,
'text': text,
'date': date,
'publisher': publisher
}
return result_dict
def check_url_get_content(url):
"""This function takes url as argument, extracts text content and other information using Article class
from newspaper library and returns result as a dictionary.
"""
result = {}
try:
# async with session.get(url, timeout=600) as resp:
with urllib.request.urlopen(url, timeout=600) as resp:
# content = await resp.read()
content = resp.read()
# if content:
article = Article(url)
article.set_html(content)
article.parse()
article.nlp()
text = article.text
keywords = article.keywords
status_code = resp.status
# else:
# text = 'none'
# keywords = 'none'
# status_code = 'none'
except Exception as e:
text = 'none'
keywords = 'none'
status_code = 'none'
result['Text'] = text
result['Keywords'] = keywords
result['status_code'] = status_code
return result
def extract(self, item):
"""Creates an instance of Article without a Download and returns an ArticleCandidate with the results of
parsing the HTML-Code.
:param item: A NewscrawlerItem to parse.
:return: ArticleCandidate containing the recovered article data.
"""
article_candidate = ArticleCandidate()
article_candidate.extractor = self._name()
article = Article('')
article.set_html(item['spider_response'].body)
article.parse()
article_candidate.title = article.title
article_candidate.description = article.meta_description
article_candidate.text = article.text
article_candidate.topimage = article.top_image
article_candidate.author = article.authors
if article.publish_date is not None:
try:
article_candidate.publish_date = article.publish_date.strftime('%Y-%m-%d %H:%M:%S')
except ValueError as exception:
self.log.debug('%s: Newspaper failed to extract the date in the supported format,'
'Publishing date set to None' % item['url'])
article_candidate.language = article.meta_lang
return article_candidate
def handle(task, progress):
url = task.url
progress.set_status("Requesting page...")
resp = http_downloader.page_text(url, json=False)
if not resp:
return False
config = Config()
config.memoize_articles = False
config.verbose = False
article = Article(url='', config=config)
article.download()
article.set_html(resp)
article.parse()
if not article.top_image:
return None
src = article.top_image
if 'http' not in src:
if 'https' in url:
src = 'https://' + src.lstrip('/ ').strip()
else:
src = 'http://' + src.lstrip('/ ').strip()
progress.set_status("Downloading image...")
return http_downloader.download_binary(src, task.file, prog=progress, handler_id=tag)
def parse_item(self, response):
tag = ""
for value in response.url.split("/")[3:]:
if str(value).isdigit():
continue
tag = value
break
item = EnPItem()
art_parser = Article(response.url, language='en', fetch_images=False)
# a.download()
art_parser.set_html(response.text)
art_parser.parse()
item["home"] = response.url
item["title"] = art_parser.title
item["content"] = art_parser.text
item["authors"] = art_parser.authors
try:
item["publish_date"] = art_parser.publish_date.strftime(
'%Y-%m-%d %H:%M:%S')
except:
pass
item["images"] = list(art_parser.images)
item["keywords"] = art_parser.keywords
item["meta_keywords"] = art_parser.meta_keywords
item["tags"] = tag #list(art_parser.tags)
print(item)
save_mess("%s.txt" % self.name,
json.dumps(dict(item), ensure_ascii=False))
def process_html(self, html):
# fetch page content and parse html using newspaper
article = Article(url="")
article.set_html(html)
article.parse()
return article
def generic(url):
article = Article(url)
r = requests.get(url, stream=True)
# article.download()
article.set_html(r.raw.read(MAX_DATA, decode_content=True))
article.parse()
return article
def retrieve_article(url):
try:
config = Configuration()
config.fetch_images = False
req = urllib.request.Request(
url,
headers={
'User-Agent':
"Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.0.1) Gecko/20020919"
})
con = urllib.request.urlopen(req, timeout=10)
html = ''.join([x for x in map(chr, con.read()) if ord(x) < 128])
article = Article(url='', config=config)
article.set_html(html)
article.parse()
text = ''.join([i if ord(i) < 128 else ' ' for i in str(article.text)])
if len(text) < 300:
article = Article(url='', config=config, language="id")
article.set_html(html)
article.parse()
text = ''.join(
[i if ord(i) < 128 else ' ' for i in str(article.text)])
text = text.replace('\n', ' ').replace('\r', ' ').replace('\t', ' ')
return text
except Exception as e:
print(e)
return False
def parse(cls, from_url: str, resolved_url: str, http_status: int,
html: str) -> List[model.Page]:
a = Article(resolved_url)
a.set_html(html)
a.parse()
try:
parsed = model.Parsed(keywords=[
s.strip() for s in a.meta_data['news_keywords'].split(",")
])
except:
parsed = None
return [
model.Page(
from_url=from_url,
resolved_url=resolved_url,
http_status=http_status,
article_metadata=dict(a.meta_data),
article_published_at=a.publish_date,
article_title=a.title,
article_text=a.text,
article_summary=a.meta_data['description'],
parsed=parsed,
fetched_at=datetime.datetime.now(),
)
]
def main(argv):
if len(argv) > 1:
htmlist = argv[1]
else:
htmlist = 'htmlist'
# Our permanent config for html cleaning
config = Config()
config.language = 'id'
config.MIN_SENT_COUNT = 20
config.memoize = False
config.fetch_images = False
config.verbose= True
cleaner = Article(url='', config=config)
with open(htmlist, 'r') as f:
htmfile = f.read().split('\n')
raw = []
for htm in htmfile:
print (htm)
if not htm.endswith("rss.html"):
with open(htm, 'r') as f:
h = f.read()
cleaner.set_html(h)
cleaner.parse()
sentences = nlp.split_sentences(cleaner.text)
#raw.append(sentences])
with open('htm-out', 'a') as f:
[f.write(r + '\n') for r in sentences]
def analyse():
article = Article('')
article.set_html(html=request.data)
article.parse()
return jsonify(source_url=article.source_url,
url=article.url,
title=article.title,
top_img=article.top_img,
meta_img=article.meta_img,
imgs=list(article.imgs),
movies=article.movies,
text=article.text,
keywords=article.keywords,
meta_keywords=article.meta_keywords,
tags=list(article.tags),
authors=article.authors,
publish_date=article.publish_date,
summary=article.summary,
article_html=article.article_html,
meta_description=article.meta_description,
meta_lang=article.meta_lang,
meta_favicon=article.meta_favicon,
meta_data=article.meta_data,
canonical_link=article.canonical_link,
additional_data=article.additional_data)
def parse_content(self, response):
"""extract content of news by newspaper"""
item = response.meta['item']
is_special, content = self._handle_special_site(response)
if not is_special:
# 不是特殊网站
article = Article(item['url'], language='zh')
article.set_html(response.body)
article.is_downloaded = True
article.parse()
item['pic'] = article.top_image
item['content'] = str(article.text)
item['publish_date'] = article.publish_date
if publish_date:
item['publish_date'] = publish_date.strftime(
"%Y-%m-%d %H:%M:%S")
else:
item['publish_date'] = "null"
else:
item['pic'] = ""
item['content'] = content
# extract content failed
if item['content'] == '':
logging.error("empty content in: " + response.url)
yield item
# raw_content = response.xpath("//body//p/text()").extract()
# item['content'] = ''.join(raw_content)
item['content'] = item['content'].strip().replace(u"\xa0", "").replace(u"\u3000", "").replace("|", "")\
.replace("用微信扫码二维码分享至好友和朋友圈", "").strip("您当前的位置 ：").strip("您所在的位置：").strip("提示：点击上方").strip(">").strip()
yield item
def parse_item(self, response):
tags = response.xpath(
'//*[@id="bread-nav"]/a[position()>=1]/text()').extract()
item = EnPItem()
art_parser = Article(response.url, language='en', fetch_images=False)
# a.download()
art_parser.set_html(response.text)
art_parser.parse()
item["home"] = response.url
item["title"] = art_parser.title
item["content"] = art_parser.text
item["authors"] = art_parser.authors
try:
item["publish_date"] = art_parser.publish_date.strftime(
'%Y-%m-%d %H:%M:%S')
except:
pass
item["images"] = list(art_parser.images)
item["keywords"] = art_parser.keywords
item["meta_keywords"] = art_parser.meta_keywords
item["tags"] = tags #list(art_parser.tags)
save_mess("daly_people.txt", json.dumps(dict(item),
ensure_ascii=False))
def get_article_from_html(article_html):
# Returns a `newspaper` Article object from article HTML
article = Article('', keep_article_html=True)
article.set_html(article_html)
article.parse()
attach_links(article)
return article
def parse(self, from_url: str, resp: aiohttp.ClientResponse, html: str) -> es.Page:
article = Article(str(resp.url))
article.set_html(html)
article.parse()
if article.clean_top_node is not None:
parsed = Parsed(
keywords=article.meta_keywords,
tickers=_parse_tickers(article.clean_top_node))
article_html = etree.tostring(
article.clean_top_node, encoding='utf-8').decode('utf-8')
else:
parsed = Parsed(keywords=article.meta_keywords, tickers=[])
article_html = None
parsed = Parsed(
keywords=article.meta_keywords,
tickers=_parse_tickers(article.clean_top_node))
page = es.Page(
from_url=from_url,
resolved_url=str(resp.url),
http_status=resp.status,
article_metadata=json.dumps(article.meta_data),
article_published_at=article.publish_date,
article_title=article.title,
article_text=article.text,
article_html=article_html,
parsed=json.dumps(dataclasses.asdict(parsed)),
fetched_at=datetime.datetime.now(),)
page.save()
def parse_item(self, response):
tags = response.xpath(
'//*[@class="row-fluid crumbs"]//text()').extract()
item = EnPItem()
art_parser = Article(response.url, language='en', fetch_images=False)
# a.download()
art_parser.set_html(response.text)
art_parser.parse()
item["home"] = response.url
item["title"] = art_parser.title
item["content"] = art_parser.text
item["authors"] = art_parser.authors
try:
item["publish_date"] = art_parser.publish_date.strftime(
'%Y-%m-%d %H:%M:%S')
except:
pass
item["images"] = list(art_parser.images)
item["keywords"] = art_parser.keywords
item["meta_keywords"] = art_parser.meta_keywords
item["tags"] = tags #list(art_parser.tags)
print(item)
save_mess("%s.txt" % self.name,
json.dumps(dict(item), ensure_ascii=False))
def extract(results):
try:
config = Configuration()
config.fetch_images = False
req = urllib.request.Request(
results["url"],
headers={
'User-Agent':
"Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.0.1) Gecko/20020919"
})
con = urllib.request.urlopen(req, timeout=10)
html = ''.join([x for x in map(chr, con.read()) if ord(x) < 128])
article = Article(url='', config=config)
article.set_html(html)
article.parse()
text = ''.join([i if ord(i) < 128 else ' ' for i in str(article.text)])
if len(text) < 300:
article = Article(url='', config=config, language="id")
article.set_html(html)
article.parse()
text = ''.join(
[i if ord(i) < 128 else ' ' for i in str(article.text)])
text = text.replace('\n', ' ').replace('\r', ' ').replace('\t', ' ')
print("=", end='', flush=True)
return (results["url"], results["title"], text, article.publish_date)
except Exception as e:
print(e)
return (results["url"], results["title"], None, None)
def scrap(self):
url = self.get_url()
print("retrieve page: {}".format(url))
# check if we are allowed to crawl this page
if not self.is_allowed():
print("Retrieval is not allowed by robots.txt")
return False
# Get page content and headers
try:
response = requests.get(url, headers={'User-Agent': settings.USER_AGENT})
except (requests.ConnectTimeout, requests.HTTPError, requests.ReadTimeout, requests.Timeout, requests.ConnectionError):
return
self.content_type = response.headers['content-type'] if 'content-type' in response.headers else "" # usually "text/html"
# don't store page content if it's not html
self.raw_content = response.text
if self.content_type.find("text/html") == -1:
print("we don't process none html pages yet.")
return False
# store article title and content
article = Article(url)
article.set_html(self.raw_content)
article.parse()
self.article_title = article.title
self.article_content = article.text
self.article_top_image = article.top_image
article.nlp()
self.article_excerpt = article.summary
self.article_keywords = article.keywords
# parse html page
soup = BeautifulSoup(self.raw_content, "html5lib")
# Images
for img in soup.findAll("img"):
img_url = img.get('src', '')
img_alt = img.get('alt', '')
img_title = img.get('title', '')
image_site_url, image_path = get_site_path(img_url)
if self.site.site_url == image_site_url:
img_site = self.site
else:
img_site = Site.objects.get_or_create(site_url=image_site_url)[0]
# get image object
image = Image.objects.get_or_create(path=image_path, site=img_site)[0]
img_detail = ImageDetail.objects.get_or_create(image=image, page=self)[0]
img_detail.title = img_title
img_detail.alt = img_alt
img_detail.save()
# HTML Title
self.page_title = soup.title.string
self.save()
return soup # for crawling
def extract_with_newspaper(self, html):
'''Parses HTML using Newspaper.'''
article = Article(self.url)
article.set_html(html)
filterwarnings('ignore', category=DeprecationWarning)
with catch_warnings():
article.parse()
return article.__dict__
def parse(response):
print type(response)
# print response.body
article = Article(url=response.url, language="es")
article.set_html(response.body)
# article = self.articleProcessor.extractAll(response.body)
print article.title
print article.publish_date
print response.url
def parse_article_page(response):
article = Article(url=response.request.url)
article.set_html(response.text)
article.parse()
if article.title and article.text:
item = NewsArticle()
item['title'] = article.title
item['text'] = article.text
yield item
def parse_article_page(response):
article = Article(url=response.request.url)
article.set_html(response.text)
article.parse()
if article.title and article.text:
item = NewsArticle()
item['title'] = article.title
item['text'] = article.text
yield item
def load_and_parse_full_article_text_and_image(url: str) -> Article:
config = Config()
config.MAX_SUMMARY_SENT = 8
article = Article(url, config=config)
article.set_html(load_page_safe(url)) # safer than article.download()
article.parse()
return article
def handle(url, data, log):
try:
log.out(0, 'Downloading article...')
resp = requests.get(url, headers={'User-Agent': data['user_agent']})
if resp.status_code != 200:
return False #!cover
config = Config()
config.memoize_articles = False
config.verbose = False
article = Article(url='', config=config)
log.out(0, 'Parsing article...')
article.download()
article.set_html(resp.text)
article.parse()
if article.top_image:
src = article.top_image
if 'http' not in src: #!cover
if 'https' in url:
src = 'https://' + src.lstrip('/ ').strip()
else:
src = 'http://' + src.lstrip('/ ').strip()
log.out(0, 'Newspaper located image: %s' % src)
r = requests.get(src,
headers={'User-Agent': data['user_agent']},
stream=True)
if r.status_code == 200:
content_type = r.headers['content-type']
ext = mimetypes.guess_extension(content_type)
if not ext or ext == '': #!cover
log.out(
1, 'NewsPaper Error locating file MIME Type: %s' % url)
return False
if '.jp' in ext:
ext = '.jpg' #!cover
path = data['single_file'] % ext
if not os.path.isfile(path):
if not os.path.isdir(data['parent_dir']): #!cover
log.out(1, ("+Building dir: %s" % data['parent_dir']))
os.makedirs(
data['parent_dir']
) # Parent dir for the full filepath is supplied already.
with open(path, 'wb') as f:
r.raw.decode_content = True
shutil.copyfileobj(r.raw, f)
return path
else: #!cover
log.out(
0, ('\t\tError Reading Image: %s responded with code %i!' %
(url, r.status_code)))
return False
except Exception as e:
log.out(0, ('"Newspaper" Generic handler failed. ' + (str(e).strip())))
return False #!cover
class ParserNewsPaper(Parser):
_extractor = None
def parse_news_text(self, page_html: str, url: str) -> dict:
if self._extractor is None:
self._extractor = Article("", language="en")
self._extractor.set_html(page_html)
self._extractor.parse()
news_text = re.sub(r'\s+', r' ', self._extractor.text)
return {'url': url, 'text': news_text}
def get_body_from_html(url, html, cache=False):
if cache:
dc = DownloadCache(url)
if not dc.is_cached():
dc.cache(html)
narticle = NArticle(url, fetch_images=False)
narticle.set_html(html)
narticle.parse()
return narticle.text
def top_image_from_html(url, html):
try:
article = Article(url=url)
article.set_html(html)
article.parse()
return article.top_image
except Exception as e:
logger.error("error reading article " + url)
return {}
def clean(html_content):
config = Configuration()
config.fetch_images = False
# TODO: allow URL passing
article = Article("http://example.com", config=config)
article.set_html(html_content)
article.is_downloaded = True
article.parse()
return article.text
def get_article(driver, url):
driver.get(url)
article = Article("")
article.set_html(driver.page_source)
article.parse()
text = article.text
text = re.sub(r"[\n ]+", " ", text, flags=re.M)
return text
def parse_article(url) -> Tuple[str, List[str]]:
"""Parse article using newspaper3k to get summary and keywords."""
if not url:
return "", []
article = Article(url)
html_content = load_page_safe(url)
if not html_content:
return "", []
article.set_html(html_content)
article.parse()
article.nlp()
return article.summary, list(set(article.keywords))
def main(argv):
try:
r = redis.StrictRedis('localhost', 6379, 0)
article = Article(url='', fetch_images=False, language='fr')
article.set_html(r.get('scraped'))
article.parse()
print(json.dumps(article.text))
except Exception:
print(json.dumps(None))
def read_nyt_article(htmltext):
"""
uses the string of the new york times article which is passed to it to extract the important information
:param htmltext: a string which contains the html of the new york times article
:return: returns a dict which stores the extracted result
"""
soup = BeautifulSoup(htmltext, 'lxml')
title = soup.html.head.title.text # extracts the title
ps = soup.body.find_all('p')
i = 0
article = Article('') # so that you can use local files with newspaper3k
article.set_html(htmltext)
article.parse()
authors = article.authors
date = article.publish_date # TODO: date not extracted here properly
if date is not None:
date = article.publish_date.strftime('%d/%m/%Y')
# used to find where the article text start - it always starts with a '-'
while '—' not in ps[i].text:
i += 1
ps = ps[i:]
# gets rid of useless sections
ps = [i for i in ps if i.text != '']
ps = [i for i in ps if i.text != 'Advertisement']
ps = [i for i in ps if 'Now in print:' not in i.text]
ps = [i for i in ps if 'And here\'s our email' not in i.text]
ps = [i for i in ps if 'The Times is committed' not in i.text]
ps = [i for i in ps if 'We\'d like to hear' not in i.text]
ps = [i for i in ps if 'Follow The New York Times' not in i.text]
ps = [i for i in ps if 'on Twitter: @' not in i.text]
ps = [i for i in ps if 'on Twitter at' not in i.text]
ps = [i for i in ps if 'contributed reporting' not in i.text]
ps = [i for i in ps if 'contributed research' not in i.text]
text = "\n ".join([" ".join(i.text.split()) for i in ps])
result_dict = {
'title': title,
'authors': authors,
'text': text,
'date': date,
'publisher': 'nytimes'
}
return result_dict
async def enrich(self, result):
# none of the following lines will work if we couldn't make soup
if not self.soup:
return result
sanitized = sanitize_html(self.response.body)
if not sanitized:
return result
article = Article(self.url, config=FixedArticleConfig())
article.config.fetch_images = False
article.set_html(sanitized)
article.parse()
result.set('title', article.title, 2, 'textlength')
if len(article.meta_description) > 0:
result.set('subtitle', article.meta_description, 2, 'textlength')
if len(article.article_html) > 0:
sanitized = sanitize_html(article.article_html)
result.set('content', sanitized, 0, 'textlength')
elif article.top_node is not None:
sanitized = sanitize_html(tostring(article.top_node))
result.set('content', sanitized, 2)
if article.authors:
result.set('authors', article.authors, 2)
if article.publish_date and len(str(article.publish_date)) > 0:
result.set('published_at', article.publish_date, 2)
result.add('keywords', list(article.keywords))
result.add('keywords', list(article.tags))
result.add('_candidate_images', list(article.imgs))
# Primary image guess is actually pretty crappy
if article.top_image:
result.add('_candidate_images', [article.top_img])
text = ""
for paragraph in article.text.split("\n"):
paragraph = paragraph.strip()
# this is done to get rid of cases where a stray heading
# like "Photographs" ends up as a paragraph
if Summarizer.has_sentence(paragraph):
text += " " + paragraph
if len(text) > 0:
result.set('_text', text, 2)
return result
def _parse_article(self, key, url):
a = Article('')
html = Google().cache(url)
a.set_html(html)
a.parse()
a.nlp()
article = {"summary":a.summary,
"publish_date":a.publish_date,
"images":a.images,
"top_image":a.top_image,
"title":a.title,
"authors":a.authors,
"keywords":a.keywords,
"text":a.text}
# update
#conn = r.connect(db="clearspark")
conn = r.connect(**rethink_conn.conn())
def clean_source(url, source):
""" Parse a pre-downloaded article using newspaper.
Args:
url (str): The url where the article was sourced (necessary for the
newspaper API).
source (str): Html source of the article page.
Returns:
Dictionary providing cleaned article and extracted content
(see `construct_result`), or `None` if newspaper could not extract
the article.
"""
article = Article(url)
article.set_html(source)
article.parse()
if article.top_node is None:
return None
return construct_result(article)
import sys, json
from newspaper import Article
htmlStr = ""
for line in sys.stdin:
htmlStr = htmlStr + line
#obj = json.loads(jsonStr)
article = Article('')
article.set_html(htmlStr);
article.parse()
article.nlp()
ret = json.dumps(article.keywords)
print ret
def extract_data(fname, loadp, savep):
######################
# initialize process #
######################
stream = GzipFile(loadp + fname)
protocol = TBinaryProtocol.TBinaryProtocol(TTransport.TBufferedTransport(stream))
data = {'data': []}
count = 0
####################
# begin extraction #
####################
while True:
page = WikiLinkItem()
try:
page.read(protocol)
count += 1
except:
stream.close()
break
print '- processing FILE {0} ENTRY # {1}'.format(fname, count)
print '\t $ URL: {0}'.format(page.url)
#####################
# initial filtering #
#####################
if page.url[:3] == 'ftp':
print '\t\t ###### Ftp prefix detected (ignore) ###### \n'
continue
if page.url[len(page.url) - 4:] != 'html':
print '\t\t ###### Non-html suffix detected (ignore) ###### \n'
continue
if page.content.dom == None:
print '\t\t ###### Empty dom detected (ignore) ###### \n'
continue
#######################
# secondary filtering #
#######################
entities = extract_entities(page.mentions)
if len(entities) < 2:
print '\t\t ###### Single entity found (discard) ###### \n'
continue
print '\t $ # Entities:', len(entities)
#########################
# alignment and parsing #
#########################
html = mark_dom(page.content.dom, entities)
news = Article(page.url, language = 'en')
try:
news.set_html(html)
news.parse()
except:
print '\t\t ###### Parsing failed (discard) ###### \n'
continue
################
# tokenization #
################
text = None
try:
text = ftfy.fix_text(news.text)
text = text.encode('ascii', 'ignore')
text = seperate_delimiter(word_tokenize(text))
except:
print '\t\t ###### Tokenization failed (discard) ###### \n'
continue
#######################
# save processed data #
#######################
print '\t $ Entry # {0} Saved \n'.format(count)
data['data'].append({'text': text, 'dict': entities})
#####################
# save as json file #
#####################
print '****** {0}.json saved ******\n'.format(fname[:3])
f = open(savep + '{0}.json'.format(fname[:3]), 'w')
json.dump(data, f, indent = 4)
f.close()
def prepare(self, response):
article = Article(url=response.url)
article.set_html(response.text)
article.parse()
return article
def parser_nlp(fname, html):
Ts = timeit.default_timer()
raw_html = html
# basic info
fid = int(fname.split('_')[0].split('/')[1])
pm = parse_machine()
html = pm.fix_html(html)
link_stats = pm.parse_links(html)
link_factors = [t for t in list(set(" ".join(link_stats.keys()).lower().split())) if (len(t) > 3)]
doc = db.articles(
fid = fid,
html = html,
html_cnt = len(html),
link_stats = link_stats,
link_factors = link_factors,
rand = random.random(),
# extra
lines = raw_html.count('\n'),
spaces = raw_html.count(' '),
tabs = raw_html.count('\t'),
braces = raw_html.count('{'),
brackets = raw_html.count('['),
quesmarks = raw_html.count('?'),
exclamarks = raw_html.count('!'),
words = len(re.split('\s+', raw_html)),
)
# check empty
if ((doc.html == None) | (len(doc.html.replace(r'\s', '')) < 10)):
doc.empty = True
return doc
try:
# if True:
pd = Article('', fetch_images=False)
pd.set_html(doc.html)
pd.parse()
pd.nlp()
except Exception as e:
print("-"*60)
print("[parser_nlp %s]: %s" % (doc.fid, e))
print(doc.html[:500])
print("-"*60)
return doc #"%s: %s" % (e, doc.id)
# select cleaned_text
cleaned_text = " ".join(pd.text.lower().split())
if (len(cleaned_text) < 140):
soup = bs(doc.html)
if soup.body:
cleaned_text = soup.body.text
if (len(cleaned_text) < 140):
cleaned_text = soup.text
cleaned_text = sanitize_txt(cleaned_text, lower=True)
bow = nlp.nlp().txt2words(cleaned_text or '', False)
# save results
try:
opengraph = pd.meta_data.get('og', {}) if pd.meta_data else {}
top_image = opengraph.get('image') or (pd.top_image if pd.top_image else None)
if isinstance(top_image, dict): top_image = top_image.get('identifier')
if isinstance(opengraph.get('locale'), dict): opengraph['locale'] = opengraph.get('locale').get('identifier')
publish_date = pm.process_date(opengraph.get('updated_time') or pd.publish_date)
# canonical_link & domain
domain = canonical_link = str(opengraph.get('url') or pd.canonical_link)
if '//' in domain: domain = domain.split('//')[1]
if '?' in domain: domain = domain.split('?')[0]
domain = '/'.join(domain.split('/')[0:1])
# update
# doc.update(
doc = db.articles(
fid = doc.fid,
html = doc.html,
link_stats = doc.link_stats,
link_factors = doc.link_factors,
rand = doc.rand,
html_cnt = doc.html_cnt,
#
lines = doc.lines,
spaces = doc.spaces,
tabs = doc.tabs,
braces = doc.braces,
brackets = doc.brackets,
quesmarks = doc.quesmarks,
exclamarks = doc.exclamarks,
words = doc.words,
#
title = str(opengraph.get('title') or pd.title)[:500],
# cleaned_text = str(cleaned_text),
bow = bow,
tags = [t.lower() for t in pd.tags],
# opengraph = {sanitize_txt(k): sanitize_txt(v) for k,v in opengraph.items()},
# summary = str(pd.summary),
keywords = pd.keywords,
top_image = str(top_image),
movies = pd.movies,
publish_date = publish_date,
meta_site_name = str(opengraph.get('site_name')),
meta_lang = str(opengraph.get('locale') or pd.meta_lang),
meta_description = str(opengraph.get('description') or pd.meta_description),
meta_keywords = pd.meta_keywords,
canonical_link = canonical_link,
domain = domain,
authors = [n.lower().replace(' ', '_') for n in pd.authors],
)
except Exception as e:
print("-"*60)
print("[Error] while [%s] in parser_nlp: %s" % (doc.id, e))
data = {
"title" : str(opengraph.get('title') or pd.title)[:500],
"text" : cleaned_text[:140],
"tags" : [t.lower() for t in pd.tags],
"opengraph" : opengraph,
"summary" : str(pd.summary),
"keywords" : pd.keywords,
"top_image" : str(top_image),
"movies" : pd.movies,
"date" : publish_date, #opengraph.get('updated_time') or pd.publish_date,
"site_name" : str(opengraph.get('site_name')),
"locale" : str(opengraph.get('locale') or pd.meta_lang),
"desc" : str(opengraph.get('description') or pd.meta_description),
"keywords" : pd.meta_keywords,
"url" : canonical_link,
"authors" : pd.authors,
}
for k,v in data.items():
print(k, v, v.__class__)
print("-"*60)
return doc
# -*- coding: utf-8 -*-
from newspaper import Article
from goose import Goose
import requests
import json
import sys
article = Article(sys.argv[1])
article.download()
if not article.html:
r = requests.get(sys.argv[1], verify=False, headers={ 'User-Agent': 'Mozilla/5.0' })
article.set_html(r.text)
article.parse()
article.nlp()
published = ''
if article.publish_date:
published = article.publish_date.strftime("%Y-%m-%d %H:%M:%S")
# Get body with goose
g = Goose()
goose_article = g.extract(raw_html=article.html)
body = goose_article.cleaned_text
summary = goose_article.meta_description
# Maybe use https://github.com/xiaoxu193/PyTeaser
if not summary:
summary = article.summary
