def daily_briefings_intent(companies, sectors, attributes, days):
"""
:param companies: Comma separated values in a string that specify which companies the daily briefing should contain
:param sectors: Comma separated values in a string that specify which sectors the daily briefing should contain
:param attributes: A list containing the attributes that the daily briefing should contain
:param days: An integer specifying the users' preference for how many days of news they want to see
:return: A dictionary containing the layout of the cards to be displayed
"""
scraper = Scraper.Scraper()
companies_data = []
if companies:
for company in companies.split(", "):
companies_data.append(scraper.get_company_data(company))
sectors_data = []
if sectors:
for sector in sectors.split(", "):
sectors_data.append(scraper.get_sector_data(sector))
response = replies.daily_briefings(companies_data, sectors_data,
attributes, days)
return response
def top_risers_intent(r):
"""
:param r: A JSON object received from Dialogflow
:return: A dictionary containing the layout of the card to be displayed
"""
response = {}
if r['result']['parameters']['rise_fall'] == '':
reply = {}
reply['text'] = r['result']['fulfillment']['speech']
reply['speech'] = r['result']['fulfillment']['speech']
reply['type'] = 'incomplete'
return reply
else:
scraper = Scraper.Scraper()
if r['result']['parameters']['rise_fall'] == "risers":
risers = scraper.get_top5()
response = replies.big_movers_card(risers)
elif r['result']['parameters']['rise_fall'] == "fallers":
fallers = scraper.get_top5(False)
response = replies.big_movers_card(fallers, False)
else: # get both
risers = scraper.get_top5()
fallers = scraper.get_top5(False)
risers_response = replies.big_movers_card(risers)
fallers_response = replies.big_movers_card(fallers, False)
response['speech'] = risers_response[
'speech'] + ' ' + fallers_response['speech']
response['type'] = 'risers&fallers'
response['text'] = {
'risers': risers_response['text'],
'fallers': fallers_response['text']
}
return response
def sector_query_intent(r, is_sector, days):
"""
:param r: The JSON object received from Dialogflow where the intent is either a SectorQuery or a SubSectorQuery
:param is_sector: Boolean value to specify whether query relates to a sector (True) or a sub-sector (False)
:days: An integer specifying the user's preference for how many days of news they want to see
:return: A dictionary containing the layout of the card to be displayed
"""
scraper = Scraper.Scraper()
sector = None
# if required entities have been specified get sector/sub-sector data
if is_sector: # is a SectorQuery
if r['result']['parameters']['sector'] == '' or r['result'][
'parameters']['sector_attribute'] == '':
reply = {}
reply['text'] = r['result']['fulfillment']['speech']
reply['speech'] = r['result']['fulfillment']['speech']
reply['type'] = 'incomplete'
return reply
else:
sector_name = r['result']['parameters']['sector']
sector_attribute = r['result']['parameters']['sector_attribute']
sector = scraper.get_sector_data(sector_name)
else: # is a SubSectorQuery
if r['result']['parameters']['subsector'] == '' or r['result'][
'parameters']['sector_attribute'] == '':
reply = {}
reply['text'] = r['result']['fulfillment']['speech']
reply['speech'] = r['result']['fulfillment']['speech']
reply['type'] = 'incomplete'
return reply
else:
sector_name = r['result']['parameters']['subsector']
sector_attribute = r['result']['parameters']['sector_attribute']
sector = scraper.get_sub_sector_data(sector_name)
# if query asks for news
if sector_attribute == "news":
date_period = r['result']['parameters']['date-period']
# if the user specified a news timeframe
if date_period:
# calculate number of days of news that was requested
start, end = date_period.split('/')
start_date = datetime.strptime(start, '%Y-%m-%d')
end_date = datetime.strptime(end, '%Y-%m-%d')
difference = end_date.date() - start_date.date()
return replies.news_reply(sector.news, difference.days, '')
else:
return replies.news_reply(sector.news, days, '')
else:
return replies.sector_reply(sector, sector_attribute)
def comparison_intent(r):
if r['result']['actionIncomplete']:
reply = {}
reply['text'] = r['result']['fulfillment']['speech']
reply['speech'] = r['result']['fulfillment']['speech']
reply['type'] = 'incomplete'
return reply
else:
companies = r['result']['parameters']['company']
scraper = Scraper.Scraper()
companies = list(set(companies))
company_data = []
for company in companies:
company_data.append(scraper.get_company_data(company))
return replies.comparison_reply(company_data)
def footsie_intent(r, days):
"""
:param r: The JSON object received from Dialogflow where the intent is a 'Footsie Intent'
:param days: An integer specifying the user's preference for how many days of news they want to see
:return: A dictionary containing the layout of the card to be displayed
"""
# Check whether all required entities have been specified
if r['result']['actionIncomplete']:
reply = {}
reply['text'] = r['result']['fulfillment']['speech']
reply['speech'] = r['result']['fulfillment']['speech']
reply['type'] = 'incomplete'
return reply
else:
company_code = r['result']['parameters']['company']
attribute = r['result']['parameters']['attribute']
scraper = Scraper.Scraper()
# if query asks for news use replies.news_reply
if attribute == "news":
date_period = r['result']['parameters']['date-period']
# if user specified a news timeframe
positive_negative = r['result']['parameters']['positive_negative']
if date_period:
# calculate how many days of news were requested
start, end = date_period.split('/')
start_date = datetime.strptime(start, '%Y-%m-%d')
end_date = datetime.strptime(end, '%Y-%m-%d')
difference = end_date.date() - start_date.date()
return replies.news_reply(
scraper.get_financial_news_data(company_code),
difference.days, positive_negative)
else:
return replies.news_reply(
scraper.get_financial_news_data(company_code), days,
positive_negative)
elif attribute == "revenue":
company = scraper.get_company_data(company_code)
return replies.revenue_reply(
company, r['result']['parameters']['date-period'])
else:
company = scraper.get_company_data(company_code)
return replies.get_company_reply(company, attribute)
def interests(request):
"""
:param request: A HTTP request
:return: A rendering of interests.html
"""
try:
preferences = UserPreferences.objects.all().first()
except:
preferences = UserPreferences.objects.create()
preferences.save()
news_timeframe = preferences.days_old
companies = preferences.companies
sectors = preferences.sectors
scraper = Scraper.Scraper()
company_news_data = defaultdict()
company_news_data['LSE'] = list()
company_news_data['YAHOO'] = list()
#get news, data for tracked companies
company_data = list()
updated = ""
for company in companies.split(", "):
if len(company) > 0:
financial_news_data = scraper.get_financial_news_data(company)
company_data.append(scraper.get_company_data(company))
updated = "Last updated: " + company_data[-1].date
company_news_data[
'LSE'] = company_news_data['LSE'] + financial_news_data['LSE']
company_news_data['YAHOO'] = company_news_data[
'YAHOO'] + financial_news_data['YAHOO']
sector_news_data = defaultdict()
sector_news_data['LSE'] = list()
sector_news_data['YAHOO'] = list()
#get news, data for tracked sectors
for sector in sectors.split(", "):
if len(sector) > 0:
sector_data = scraper.get_sector_data(sector)
company_data = company_data + sector_data.companies
sector_news_data['LSE'] += scraper.get_sector_data(
sector).news['LSE']
sector_news_data['YAHOO'] += scraper.get_sector_data(
sector).news['YAHOO']
#merge company and sector news, sort by date and remove duplicates
all_news_data = defaultdict()
all_news_data['LSE'] = list()
all_news_data['YAHOO'] = list()
all_news_data['LSE'] = company_news_data['LSE'] + sector_news_data['LSE']
all_news_data[
'YAHOO'] = company_news_data['YAHOO'] + sector_news_data['YAHOO']
all_news_data['LSE'].sort(
key=lambda x: datetime.strptime(x.date, '%H:%M %d-%b-%Y'),
reverse=True)
all_news_data['YAHOO'].sort(
key=lambda x: datetime.strptime(x.date, '%H:%M %d-%b-%Y'),
reverse=True)
all_news_data['LSE'] = remove_duplicates(all_news_data['LSE'])
all_news_data['YAHOO'] = remove_duplicates(all_news_data['YAHOO'])
all_news = replies.news_reply(all_news_data, news_timeframe, '')
#remove duplicates from company_data
company_data.sort(key=lambda x: x.code, reverse=False)
lastc = ""
for c in company_data:
if lastc != "":
if c.code == lastc.code:
company_data.remove(c)
lastc = c
#pass data to interests template
data = {
'companies': company_data,
'all_news': all_news,
'updated': updated,
'colour_scheme': preferences.colour_scheme
}
return render(request, 'interests.html', data)
def setUp(self):
self.scraper = Scraper.Scraper()
self.company = self.scraper.get_company_data('BARC')
def sector_members(r):
scraper = Scraper.Scraper()
sector_name = r['result']['parameters']['sector']
sector = scraper.get_sector_data(sector_name)
return replies.members_reply(sector)