def about():
newsapi = NewsApiClient(api_key="b0f75ce660c0466a9a98c2478f8abb62")
topheadlines = newsapi.get_top_headlines(sources="al-jazeera-english")
articles = topheadlines['articles']
desc = []
news = []
img = []
for i in range(len(articles)):
myarticles = articles[i]
news.append(myarticles['title'])
desc.append(myarticles['description'])
img.append(myarticles['urlToImage'])
mylist = zip(news, desc, img)
return render_template('about.html', context = mylist)
def news(request):
try:
queries = News.objects.all()
api = NewsApiClient(api_key='728bb1f02da34d37b4a5da9f67b87fbe')
headlines = api.get_top_headlines(sources='techcrunch')
if len(queries) == 0:
for item in headlines["articles"]:
temp = News(author=item["author"],
title=item["title"],
description=item["description"],
url=item["url"],
urlToImage=item["urlToImage"])
temp.save()
queries = News.objects.all()
args = {"queries": queries}
if headlines["status"] == "ok":
modified_queries = dicToQueries(headlines, queries)
args = {"queries": modified_queries}
else:
args = {"queries": queries}
return render(request, 'cosmos/news.html', args)
except ConnectionError:
return render(request, 'cosmos/news.html', args)
except ConnectTimeout:
return render(request, 'cosmos/news.html', args)
def bbc(request):
if request.method == 'POST':
keyword_to_search = request.POST['searchbar']
print(keyword_to_search)
if 'email' in request.session.keys():
logged_user = User.objects.get(email=request.session['email'])
searched_keyword = logged_user.searches.filter(
keyword=keyword_to_search)
print(searched_keyword)
if len(searched_keyword) == 0:
dk = Search.objects.create(keyword=keyword_to_search)
dk.user.add(logged_user)
else:
logged_user = '******'
newsapi = NewsApiClient(api_key="959759915d66465fbff7c7ec6993daf7")
topheadlines = newsapi.get_top_headlines(sources='bbc-news',
q=keyword_to_search,
language='en')
articles = topheadlines['articles']
desc = []
news = []
img = []
content = []
url = []
for i in range(len(articles)):
if True: #keyword in articles[i]['title'] or keyword in articles[i]['description']:
myarticles = articles[i]
news.append(myarticles['title'])
desc.append(myarticles['description'])
img.append(myarticles['urlToImage'])
content.append(myarticles['content'])
url.append(myarticles['url'])
mylist = zip(news, desc, img, content, url)
context = {"mylist": mylist, "curr_user": logged_user}
return render(request, 'bbc.html', context)
def blog():
page = request.args.get('page', 1, type=int)
posts = Post.query.order_by(Post.date_posted.desc()).paginate(page=page,
per_page=10)
newsapi = NewsApiClient(api_key="12692f50f97a481cb516c2d540b6dc15")
topheadlines = newsapi.get_top_headlines(
sources=
"google-news-in,the-verge,bbc-news,wired,business-insider,google-news",
page_size=10)
articles = topheadlines['articles']
desc = []
news = []
img = []
for i in range(len(articles)):
myarticles = articles[i]
img.append(myarticles['urlToImage'])
news.append(myarticles['title'])
desc.append(myarticles['description'])
mylist = zip(news, desc, img)
return render_template('blog.html', context=mylist, posts=posts)
def get_top_headlines(cls):
newsapi = NewsApiClient(api_key=settings.NEWS_API_KEY)
top_headlines = newsapi.get_top_headlines(language='en',
country='us',
page_size=100)
articles = top_headlines.get('articles', [])
news_headlines = []
batch_size = top_headlines.get('totalResults', 20)
for article in articles:
source = article['source']
source_id = source['id']
source_name = source['name']
author = article['author']
title = article['title']
description = article['description']
url = article['url']
url_to_image = article['urlToImage']
published_at = datetime.datetime.strptime(article['publishedAt'],
'%Y-%m-%dT%H:%M:%SZ')
print(article)
news_article = cls(
source_id=source_id,
source_name=source_name,
author=author,
title=title,
description=description,
url=url,
url_to_image=url_to_image,
published_at=published_at,
)
news_headlines.append(news_article)
return cls.objects.bulk_create(news_headlines, batch_size)
def news(request):
# news API to show the latest news
newsapi = NewsApiClient(api_key='1aab8f2e782a4a588fc28a3292a57979')
top = newsapi.get_top_headlines(sources='cnn')
l = top['articles']
desc = []
news = []
img = []
urllink = []
for i in range(len(l)):
f = l[i]
news.append(f['title'])
desc.append(f['description'])
img.append(f['urlToImage'])
urllink.append(f['url'])
mylist = list(zip(news, desc, img, urllink))
user = get_user_type(request)
args = {
'mylist': mylist,
'obj': user['obj'],
'user_type': user['user_type']
}
return render(request, 'news.html', args)
def bbc():
newsapi = NewsApiClient(api_key)
topheadlines = newsapi.get_top_headlines(
sources=
"abc-news, al-jazeera-english, associated-press, axios, bbc-news, bloomberg, business-insider, buzzfeed, cbs-news, cnn, independent, msnbc, mtv-news, national-geographic, nbc-news, newsweek, new-york-magazine, politico, the-hill, the-huffington-post, the-wall-street-journal,the-washington-post, time, usa-today, vice-news"
)
articles = topheadlines['articles']
news = []
img = []
desc = []
url = []
source = []
for i in range(len(articles)):
myarticles = articles[i]
news.append(myarticles['title'])
img.append(myarticles['urlToImage'])
desc.append(myarticles['description'])
url.append(myarticles['url'])
source.append(myarticles['source'])
mylist = zip(news, desc, img, url, source)
return render_template('bbc.html',
title="Starbucks Sipping Hall Monitors",
context=mylist)
def busin(request):
newsapi = NewsApiClient(api_key='f776a61cf60744cf9f5473701caea44b')
top = newsapi.get_top_headlines(
sources='business-insider,cnbc,financial-post,fortune')
l = top['articles']
desc = []
news = []
img = []
link = []
published = []
author = []
for i in range(len(l)):
f = l[i]
news.append(f['title'])
desc.append(f['description'])
img.append(f['urlToImage'])
link.append(f['url'])
published.append(f['publishedAt'])
author.append(f['author'])
mylist = zip(news, desc, img, link, published, author)
return render(request, 'busin.html', context={"mylist": mylist})
def science_news(request):
newsapi = NewsApiClient(api_key='e45eba9d14604d7dabbfbe7f3db2db90')
science_headlines = newsapi.get_top_headlines(category='science',
language='en',
country='in')
context = {'articles': science_headlines.get('articles')}
return render(request, 'topnews/topnews.html', context)
def world(request):
newsapi = NewsApiClient(api_key='f776a61cf60744cf9f5473701caea44b')
top = newsapi.get_top_headlines(
sources='bbc-news,google-news,vice-news,al-jazeera-english')
l = top['articles']
desc = []
news = []
img = []
link = []
published = []
author = []
for i in range(len(l)):
f = l[i]
news.append(f['title'])
desc.append(f['description'])
img.append(f['urlToImage'])
link.append(f['url'])
published.append(f['publishedAt'])
author.append(f['author'])
mylist = zip(news, desc, img, link, published, author)
return render(request, 'world.html', context={"mylist": mylist})
def sports(request):
newsapi = NewsApiClient(api_key='f776a61cf60744cf9f5473701caea44b')
top = newsapi.get_top_headlines(
sources='espn,talksport,bbc-sport,espn-cric-info')
l = top['articles']
desc = []
news = []
img = []
link = []
published = []
author = []
for i in range(len(l)):
f = l[i]
news.append(f['title'])
desc.append(f['description'])
img.append(f['urlToImage'])
link.append(f['url'])
published.append(f['publishedAt'])
author.append(f['author'])
mylist = zip(news, desc, img, link, published, author)
return render(request, 'sports.html', context={"mylist": mylist})
def ente(request):
newsapi = NewsApiClient(api_key='f776a61cf60744cf9f5473701caea44b')
top = newsapi.get_top_headlines(
sources='buzzfeed,entertainment-weekly,ign,mashable,mtv-news')
l = top['articles']
desc = []
news = []
img = []
link = []
published = []
author = []
for i in range(len(l)):
f = l[i]
news.append(f['title'])
desc.append(f['description'])
img.append(f['urlToImage'])
link.append(f['url'])
published.append(f['publishedAt'])
author.append(f['author'])
mylist = zip(news, desc, img, link, published, author)
return render(request, 'ente.html', context={"mylist": mylist})
def updateLDA():
api_file="./newsapi.key"
categories=['business', 'entertainment', 'general', 'health', 'science', 'sports', 'technology']
with open(api_file,"r") as apikey:
newsapi=NewsApiClient(api_key=apikey.read().strip())
headlines={cat:newsapi.get_top_headlines(category=cat, language='en', country='in') for cat in categories}
pp_docs=[]
for category in headlines:
for article in headlines[category]['articles']:
#print(lemma_pp(article['title']))
pp_docs.append(lemma_pp(article['title']))
if os.path.exists(MODEL_DIR+"corpus_dict.model"):
corp_d=Dictionary.load(MODEL_DIR+"corpus_dict.model")
corp_d.add_documents(pp_docs)
else:
corp_d = Dictionary(pp_docs)
corp_d.filter_extremes(no_below=2, no_above=0.5)
dtm=[corp_d.doc2bow(doc) for doc in pp_docs]
tfidf=TfidfModel(dtm)
corp_tfidf=tfidf[dtm]
lda = LdaMulticore(corp_tfidf, num_topics=5, id2word=corp_d, passes=60, workers=3)
print(lda.print_topics(num_topics=5, num_words=5))
checkdir(MODEL_DIR)
corp_d.save(MODEL_DIR+"corpus_dict.model")
#corp_tfidf.save(MODEL_DIR+"corpus_tfidf.model")
lda.save(MODEL_DIR+"lda.model")
def wordcloud():
newsapi = NewsApiClient(api_key='fd4c0e4b873343a3a0a7b50168a89e9a')
top_headlines = newsapi.get_top_headlines(language='en', page_size=60)
articles = top_headlines["articles"]
file1 = open('myfile.txt', 'r')
Lines = file1.readlines()
sw = set()
for line in Lines:
sw.add(line.strip())
x = set()
mydic = collections.defaultdict(int)
for article in articles:
headline = article["title"]
words = headline.split()
#print("words is ", words)
for word in words:
word = word.lower()
if word.isalpha() and word not in sw:
mydic[word] += 1
mywords = []
mykeys = sorted(mydic, key=lambda k: mydic[k])
mykeys = mykeys[::-1]
#print(mykeys)
for key in mykeys:
e = dict()
e["word"] = key
e["size"] = mydic[key]
mywords.append(e)
#print(mywords)
mywords = mywords[:30]
return jsonify(cloudwords=mywords)
def index(request):
newsapi = NewsApiClient(api_key='93ec2510842647889c3913445b754c83')
# /v2/top-headlines
top_headlines = newsapi.get_top_headlines(sources='bbc-news,the-verge')
# category='health',
# language='en',
# country='us')
all_articles = top_headlines['articles']
desc = []
news = []
img = []
url = []
for i in range(len(all_articles)):
my_articles = all_articles[i]
news.append(my_articles['title'])
desc.append(my_articles['description'])
url.append(my_articles['url'])
img.append(my_articles['urlToImage'])
mylist = zip(news, desc, url, img)
return render(request, 'index.html', context={'mylist': mylist})
def search_top_publication_by_keywords(q, country, language, page_size, page):
"""
Функция предоставляет последние топовые публикации по ключевым словам
"""
try:
page = int(page)
except ValueError:
print('Номер страницы не может быть нулевым или являться строкой')
page = int(input('Введите номер страницы заново: '))
except TypeError:
print('Номер страницы не может являться строкой')
page = int(input('Введите номер страницы заново: '))
try:
page_size = int(page_size)
except ValueError:
print(
'Размер страницы не может быть нулевым, быть больше 25 или являться строкой'
)
page_size = int(input('Введите размер страница заново: '))
except TypeError:
print('Размер страницы не может являться строкой')
page_size = int(input('Введите размер страницы заново: '))
res = NewsApiClient(api_key='5ec9e95dabaa4e25a0877794212d9b55')
top_headlines = res.get_top_headlines(q=q,
country=country,
language=language,
page_size=int(page_size),
page=int(page))
print(top_headlines)
def search(request):
query = request.GET['query']
newsapi = NewsApiClient(api_key='f2d21efaf1e4456db37ccaefbb14a4c2')
top = newsapi.get_top_headlines(q=(str(query)), language='en')
l = top['articles']
for i in range(len(l)):
f = l[i]
f['publishedAt'] = f['publishedAt'][0:10]
if not newslist.objects.filter(title=f['title']).exists():
newslist(title=f['title'],
description=f['description'],
image=f['urlToImage'],
author=f['author'],
url=f['url'],
publishedAt=f['publishedAt'],
content=f['content']).save()
if len(query) > 100:
allPosts = []
else:
allPosts = (newslist.objects.filter(
title__icontains=query).order_by('-post_id')
or Newscountrywise.objects.filter(
title__icontains=query).order_by('-post_id')
or Newscatwise.objects.filter(
title__icontains=query).order_by('-post_id'))
if not allPosts:
messages.error(request, "Please enter valid search")
params = {'allPosts': allPosts, 'query': query}
return render(request, 'newsapp/search.html', params)
def run(self, dispatcher, tracker, domain):
from newsapi import NewsApiClient
# Init
newsapi = NewsApiClient(api_key='f908755783e34e738776e64eeacfbd17')
print(tracker.get_slot('country'))
country = tracker.get_slot('country')
country_iso2 = coco.convert(names=country, to='ISO2', not_found=None)
print(country_iso2)
country_iso2_low = country_iso2.lower()
# /v2/top-headlines
top_headlines = newsapi.get_top_headlines(#q=country,
#sources='bbc-news,the-verge',
country=country_iso2_low)
news_json = json.dumps(top_headlines)
list_articles = json.loads(news_json)
for articles in list_articles['articles']:
print('Author: ' + str(articles['author']))
print('Source: ' + str(articles['source']['name']))
print('Title: ' + str(articles['title']))
print('URL: ' + str(articles['url']) + "\n")
print("############################################################")
dispatcher.utter_message('**Source:** ' + str(articles['source']['name']) + '\n **Title:** ' + str(articles['title']) + '\n **URL:** ' + str(articles['url']) + '\n')
def news(news_source: str = 'fox') -> None:
"""Says news around the user's location.
Args:
news_source: Source from where the news has to be fetched. Defaults to ``fox``.
"""
if not env.news_api:
logger.warning("News apikey not found.")
support.no_env_vars()
return
sys.stdout.write(f'\rGetting news from {news_source} news.')
news_client = NewsApiClient(api_key=env.news_api)
try:
all_articles = news_client.get_top_headlines(
sources=f'{news_source}-news')
except newsapi_exception.NewsAPIException:
speaker.speak(
text=f"I wasn't able to get the news {env.title}! "
"I think the News API broke, you may try after sometime.")
return
speaker.speak(text="News around you!")
speaker.speak(text=' '.join(
[article['title'] for article in all_articles['articles']]))
if shared.called_by_offline:
return
if shared.called['report'] or shared.called['time_travel']:
speaker.speak(run=True)
def sport():
newsapi = NewsApiClient(api_key='b92cb162f8064f81964d4268970377c1')
top_headlines = newsapi.get_top_headlines(category='sports',
language='en',
country='in')
articles = top_headlines['articles']
print(len(articles))
desc = []
news = []
img = []
link = []
for i in range(len(articles)):
myarticle = articles[i]
news.append(myarticle['title'])
desc.append(myarticle['description'])
img.append(myarticle['urlToImage'])
link.append(myarticle['url'])
mylist = zip(news, desc, img, link)
return render_template('sports.html', context=mylist)
def rightwing():
newsapi = NewsApiClient(api_key)
rightwing = newsapi.get_top_headlines(
sources=
"breitbart-news, fox-news, national-review, the-american-conservative, the-hill, the-jerusalem-post, the-washington-times"
)
articles = rightwing['articles']
news = []
img = []
desc = []
url = []
source = []
for i in range(len(articles)):
myarticles = articles[i]
news.append(myarticles['title'])
img.append(myarticles['urlToImage'])
desc.append(myarticles['description'])
url.append(myarticles['url'])
source.append(myarticles['source'])
mylist = zip(news, desc, img, url, source)
return render_template('right-wing-news.html',
title="Mountain Dew Lovin' Far Right Extremists",
context=mylist)
def download_basic_news(self):
"""
:return:
"""
columns = [
'id_source', 'name', 'author', 'title', 'description', 'url',
'urlToImage', 'publishedAt', 'content'
]
request_number = self.NUM_NEWS_TO_SCRAP
# DATA PREPARATION
# Building and executing the request to newsapi.org
newsapi = NewsApiClient(api_key='a11cabb5333f4ade87a27e20f28bb568')
all_articles = newsapi.get_top_headlines(sources=self.m_source_name,
language='en',
page_size=request_number)
# DATA FORMATTING
data = pd.DataFrame.from_dict(all_articles)
data = data['articles'].apply(pd.Series)
new_news = pd.concat(
[data.drop(['source'], axis=1), data['source'].apply(pd.Series)],
axis=1)
new_news = new_news[[
'id', 'name', 'author', 'title', 'description', 'url',
'urlToImage', 'publishedAt'
]]
new_news.rename(columns={'id': 'id_source'}, inplace=True)
return new_news
def index_page():
global is_auth, current_user_logged_id
if request.method == 'POST':
if is_auth == 0:
print(str(current_user_logged_id))
return redirect(url_for('user_login'))
if 'player' in request.form:
print('Goes to All music Here with ' + str(is_auth) +
" and user id is " + str(current_user_logged_id))
return redirect(url_for('all_music'))
if 'profile' in request.form:
return redirect(url_for('profile', u_id=current_user_logged_id))
if 'logout' in request.form:
return redirect(url_for('log_out'))
news_client = NAC_client(api_key='f8fd249bda5f49c1b1ed79d08e99440d')
try:
all_news = news_client.get_top_headlines(q='music')
except:
all_news = None
all_users = User.query.all()
all_songs = Music.query.all()
all_albums = Album.query.all()
all_artists = Artist.query.all()
dashboard_data = dashboard_wrapper(all_users, all_songs, all_albums,
all_artists)
news_list = []
if all_news == None:
news_list = 'No Internet Error Encountered while Fetching News'
else:
for news_obj in all_news['articles']:
news_list.append(news_obj)
return render_template("index.html",
news_data=news_list,
dash_data=dashboard_data,
is_auth=is_auth)
def Index(request):
newsapi = NewsApiClient(api_key="3261097a702947809aad72c0ab3c2291")
topheadlines = newsapi.get_top_headlines(country="in")
articles = topheadlines['articles']
desc = []
news = []
img = []
for i in range(len(articles)):
myarticles = articles[i]
news.append(myarticles['title'])
desc.append(myarticles['description'])
img.append(myarticles['urlToImage'])
mylist = zip(news, desc, img)
return render(request, 'mainpage.html', context={"mylist":mylist,})
def getNews():
# Init
newsapi = NewsApiClient(api_key='input your key')
top_headlines = newsapi.get_top_headlines(language='en') # country='us'
articles = top_headlines['articles']
return articles
def newsapi_client(stock, company):
"""
Using NewsApiClient object -
Note that NewsApiClient uses underscores in parameter names:
exclude_domains, sort_by, page_size, api_key
"""
# Init
newsapi = NewsApiClient(api_key=API_KEY)
# /v2/top-headlines
top_headlines = newsapi.get_top_headlines(q=stock,
sources='bbc-news,the-verge',
language='en')
save_data.save_json(top_headlines, "top_headlines")
# /v2/everything
everything = newsapi.get_everything(q=company,
from_param='2021-01-01',
to='2021-01-07',
language='en',
sort_by='relevancy',
page_size=3,
page=1)
save_data.save_json(everything, "everything")
# /v2/sources
sources = newsapi.get_sources(language="en")
save_data.save_json(sources, "sources")
def technology_news():
connect = MongoClient()
db = connect.newsapi
collection = db.newsapi_data
headers = {'Authorization': '7cb11b15c84a4ff1af515df4c4dbaf47'}
top_headlines_url = 'https://newsapi.org/v2/top-headlines'
everything_news_url = 'https://newsapi.org/v2/everything'
sources_url = 'https://newsapi.org/v2/sources'
newsapi = NewsApiClient(api_key="7cb11b15c84a4ff1af515df4c4dbaf47")
topheadlines = newsapi.get_top_headlines(country="us",
category="technology")
articles = topheadlines['articles']
desc = []
news = []
img = []
for i in range(len(articles)):
myarticles = articles[i]
news.append(myarticles['title'])
desc.append(myarticles['description'])
img.append(myarticles['urlToImage'])
document = {'title': news, 'description': desc, 'urlToImage': img}
collection.insert_one(document)
print('data has been entered')
def newsJutsu():
newsapi = NewsApiClient(api_key=NEWSAPI_KEY)
top_headlines = newsapi.get_top_headlines(language='en')
articles = top_headlines['articles']
# Rate of speech
rate = engine.getProperty('rate')
engine.setProperty('rate', 220)
for i in range(0, len(articles)):
if i > 5:
speak("Hey, are you still listening?")
response = "None"
while response == "None":
response = takeCommand(mode="inside_skill")
if "yes" in response:
pass
else:
return "Alright"
if(articles[i]['title'] != None and articles[i]['description'] != None):
# Either title or description
speak(articles[i]['description'])
# description = articles[i]['description'].replace("\n"," ")
speak("Coming up next...")
return "That's all for now"
# Rate of speech
rate = engine.getProperty('rate')
engine.setProperty('rate', 195)
def getNews(self):
# Creating News API object
newsapi = NewsApiClient(api_key=self.news_api_key)
top_headlines = newsapi.get_top_headlines(
sources=
'bbc-news,the-verge,the-wall-street-journal,bloomberg,the-economist,wired'
)
articles = top_headlines['articles']
if len(articles) > 10:
articles = articles[0:10]
'''
count = 1
for article in articles:
print(article['title'])
print(article['url'])
print(article['publishedAt'])
print(article['source']['name'])
print('-'*60)
command = 'say "Number %s: %s writes %s"' % (str(count), article['source']['name'].encode('utf-8'), article['title'].encode('utf-8'))
count += 1
try:
os.system(command)
except KeyboardInterrupt:
print("Interupted! How rude!")
finally:
sys.exit()
'''
return articles
def espn():
'''
view page function that returns espn page
'''
newsapi = NewsApiClient(api_key = 'e7f56e932284432c89095aa5928310c7' )
topheadlines = newsapi.get_top_headlines(sources="espn")
articles = topheadlines['articles']
desc = []
news = []
date = []
link = []
for i in range(len(articles)):
myarticles = articles[i]
news.append(myarticles['title'])
desc.append(myarticles['description'])
date.append(myarticles['publishedAt'])
link.append(myarticles['url'])
mylist = zip(news, desc, date,link)
title = 'Home - Welcome to newshub'
return render_template('espn.html', title = title,context= mylist)
