def handle(self, *args, **options):
print 'starting script'
today_date = datetime.today().date()
tomorrow_date = (datetime.today() + timedelta(days=1)).date()
tickers_reporting_today = Ticker.objects.filter(earnings_announcement=today_date)
tickers_reporting_tomorrow = Ticker.objects.filter(earnings_announcement=tomorrow_date)
message_snippets = []
message_snippets.append("*Companies reporting earnings today:*")
if not tickers_reporting_today:
message_snippets.append("_none_")
else:
for t in tickers_reporting_today:
message_snippets.append(" - %s (*%s*) : _%s_" % (t.company_name, t.ticker_symbol, t.services_for_ticker))
message_snippets.append("*Companies reporting earnings tomorrow* (%s):" % tomorrow_date.strftime("%a, %b %d, %Y"))
if not tickers_reporting_tomorrow:
message_snippets.append("_none_")
else:
for t in tickers_reporting_tomorrow:
message_snippets.append(" - %s (*%s*) : _%s_" % (t.company_name, t.ticker_symbol, t.services_for_ticker))
message_to_post = "\n".join(message_snippets)
post_message_to_slack(message_to_post)
print message_to_post
def handle(self, *args, **options):
print 'starting script'
yesterday = (datetime.today() - timedelta(days=1)).date()
articles_published_yesterday = Article.objects.filter(date_pub__year=yesterday.year,date_pub__month=yesterday.month, date_pub__day=yesterday.day)
unique_urls = set([a.url for a in articles_published_yesterday])
article_count = len(unique_urls)
message_snippets = []
message_snippets.append("*Articles recap for %s *" % yesterday.strftime('%a, %b %d, %Y')) # eg: Tue, May 12, 2015
message_snippets.append("articles published: %d" % article_count)
if article_count > 0:
ticker_symbols_list = [a.ticker.ticker_symbol for a in articles_published_yesterday]
tickers_count = len(set(ticker_symbols_list))
# which tickers received the most coverage, across yesterday's articles?
# use python's Counter to do the counting for us. https://docs.python.org/dev/library/collections.html#counter-objects
most_common_tickers = []
tickers_frequency_counter = Counter(ticker_symbols_list)
most_common = tickers_frequency_counter.most_common(15) # we'll pick at most the top 15
for ticker_popularity in most_common:
ticker_symbol = ticker_popularity[0]
count = ticker_popularity[1]
# if count == 1, then this isn't so interesting. let's not bother including it
if count==1:
break
most_common_tickers.append("%s (%d)" % (ticker_symbol, count))
most_common_tickers = ', '.join(most_common_tickers) # eg: AVAV (3), FB (2), AAPL (2)
article_count_by_service = ''
for s in Service.objects.all().order_by('pretty_name'):
articles_for_service = [a for a in articles_published_yesterday if a.service==s]
num_articles_for_service = len(set([a.url for a in articles_for_service]))
if num_articles_for_service > 0:
tickers_in_service_articles = set([a.ticker.ticker_symbol for a in articles_for_service])
tickers_in_service_articles = list(tickers_in_service_articles)
tickers_in_service_articles.sort()
article_count_by_service += "\n - %s : %d (%s)" % (s.pretty_name, num_articles_for_service, ', '.join(tickers_in_service_articles))
message_snippets.append("```tickers covered: %d" % tickers_count)
if most_common_tickers:
message_snippets.append("tickers with the most coverage: %s" % most_common_tickers)
message_snippets.append('--------------')
message_snippets.append("articles by service: %s" % article_count_by_service)
message_snippets.append('```')
message_to_post = "\n".join(message_snippets)
post_message_to_slack(message_to_post)
def process_rules():
# find tickers that newly satisfy the threshold value
# alert subscribers that follow any of those tickers
# find tickers that satisfy the threshold value
tickers_with_big_movement = Ticker.objects.filter( Q(daily_percent_change__gt=INTRADAY_THRESHOLD) | Q(daily_percent_change__lt=-1*INTRADAY_THRESHOLD)).order_by('ticker_symbol')
# filter down to the ones that have hit the threshold for the first time today
# create a receipt for each of these newly-detected big movers
new_movers_receipts = []
for t in tickers_with_big_movement:
matches_for_today = IntradayBigMovementReceipt.objects.filter(ticker=t, timestamp__gt=timezone.now().date())
if not matches_for_today:
new_movers_receipts.append(IntradayBigMovementReceipt.create(t, t.daily_percent_change))
print 'newly-detected big movers: %d (%s)' % (len(new_movers_receipts), ', '.join([nmr.ticker.ticker_symbol for nmr in new_movers_receipts]))
if len(new_movers_receipts) == 0:
return
# for each active subscriber, figure out which of the newly-detected big movers match his interests
for subscriber in NotificationSubscriber.objects.filter(is_active=True):
tickers_for_subscriber = [t.strip() for t in subscriber.tickers_csv.upper().split(',')]
subscriber_services = [s.pretty_name.strip() for s in subscriber.services.all()]
messages_for_subscriber = []
for r in new_movers_receipts:
if r.ticker.ticker_symbol in tickers_for_subscriber:
messages_for_subscriber.append(r.message)
elif r.ticker.services_for_ticker:
ticker_services = [s.strip() for s in r.ticker.services_for_ticker.split(',')]
if set(subscriber_services) & set(ticker_services):
messages_for_subscriber.append(r.message)
if messages_for_subscriber:
message_text = '```' + '\n'.join(messages_for_subscriber) + '```'
post_message_to_slack(message_text=message_text, channel=subscriber.slack_handle, username='******', icon_emoji=':boom:')
print 'alerted %s: %s' % (subscriber.slack_handle, message_text)
def handle(self, *args, **options):
print 'starting script'
# create a dictionary, keys = service pretty name, values = a list of tickers in that service
tickers_by_service_pretty_name = {}
# prime the dictionary: insert keys for the service pretty names, set the values to an empty list
for s in Service.objects.all():
tickers_by_service_pretty_name[s.pretty_name] = []
# populate the values
for ticker in Ticker.objects.all():
if not ticker.services_for_ticker:
continue
# convert the string of services into a list, one element per service name
services_associated_with_ticker = ticker.services_for_ticker.split(",")
# strip whitespace from each element in the list
services_associated_with_ticker = [s.strip() for s in services_associated_with_ticker]
for service_associated_with_ticker in services_associated_with_ticker:
tickers_by_service_pretty_name[service_associated_with_ticker].append(ticker)
# by this point, we've iterated over all tickers and via our dictionary know
# all that are associated to any service
# we'll now compile text summaries, one per service
text_summaries = []
service_pretty_names = tickers_by_service_pretty_name.keys()
service_pretty_names.sort()
for service_pretty_name in service_pretty_names:
print 'processing tickers for service ', service_pretty_name
tickers_for_this_service = tickers_by_service_pretty_name[service_pretty_name]
ticker_count_for_this_service = len(tickers_for_this_service)
print 'how many tickers?', ticker_count_for_this_service
if ticker_count_for_this_service == 0:
continue
tickers_for_this_service = sorted(tickers_for_this_service, key=lambda x: x.daily_percent_change, reverse=True)
top_gainers = tickers_for_this_service[:3]
top_losers = tickers_for_this_service[-3:]
top_losers.reverse() # so that this smaller list is ordered from worst performance to less bad performance
tickers_with_positive_movement = [t for t in tickers_for_this_service if t.daily_percent_change > 0.0]
count_tickers_with_positive_movement = len(tickers_with_positive_movement)
# we've identified the data points (top gainers, top losers, count of the tickers with positive movement);
# now let's create the text description.
# https://docs.python.org/2/library/string.html#format-specification-mini-language
# https://docs.python.org/2/library/string.html
desc_of_top_gainers = ['%s (%g%%)' % (t.ticker_symbol, t.daily_percent_change) for t in top_gainers]
desc_of_top_gainers = ', '.join(desc_of_top_gainers)
desc_of_top_losers = ['%s (%g%%)' % (t.ticker_symbol, t.daily_percent_change) for t in top_losers]
desc_of_top_losers = ', '.join(desc_of_top_losers)
percentage_positive_movement = '{:.2%}'.format(1.0*count_tickers_with_positive_movement/ticker_count_for_this_service)
desc_of_positive_movement = "recs with gains today: %s (%d of %d)" % (percentage_positive_movement, count_tickers_with_positive_movement, ticker_count_for_this_service)
summary_for_this_service = "%s %s" % (service_pretty_name, desc_of_positive_movement)
summary_for_this_service += "\n %s" % desc_of_top_gainers
summary_for_this_service += "\n %s" % desc_of_top_losers
text_summaries.append(summary_for_this_service)
print summary_for_this_service
service_blurbs = '```' + "\n------------------------\n".join(text_summaries) + '```'
headline = "*Ticker performance snapshot for %s *" % datetime.now().strftime('%a, %b %d, %Y %H:%M') # eg: Tue, May 12, 2015 11:15
subtitle = "(per service: top 3, worst 3, and % of recs with positive movement)"
message_to_post = '\n'.join([headline, subtitle, service_blurbs])
post_message_to_slack(message_to_post)
