def get_stock_info(symbols, moreInfo=False): """ Scrape stock info from Yahoo finance @Param 'moreInfo': False for getting price, True for getting more information @Return 'message': "symbol: Price-number, Open Price-number, Pre Close Price-number, High Price-number, Low price-number" """ message = '' for symbol in symbols: try: stock = Share(symbol) price = stock.get_price() except AttributeError: price = None if price == None: # Stock symbol not exists, replace with an alert message message += '#' + symbol + ': ' + 'The stock symbol does not exit' + '\n' elif moreInfo: message += '#%s: Price-%s, Open Price-%s, Pre Close Price-%s, High Price-%s, Low price-%s\n' \ % (symbol, price, stock.get_open(), stock.get_prev_close(), stock.get_days_high(), stock.get_days_low()) else: message += '#' + symbol + ': ' + price + '\n' alert_message = 'Please type #1 followed by stock symbols to get more information' if moreInfo == True else \ 'Please type #0 followed by stock symbols to get stock price' return message if message != '' else alert_message
def find_quote(word):
"""Given an individual symbol,
find and return the corresponding financial data
word -- the symbol for which you're finding the data (ex. "GOOG")
"""
cleanword=re.sub('[@<>]', '', word)
share = Share(cleanword)
price = share.get_price()
if price != None:
# Extract data
day_high = share.get_days_high()
day_low = share.get_days_low()
market_cap = share.get_market_cap()
year_high = share.get_year_high()
year_low = share.get_year_low()
yoy = calculate_YoY(share)
output_string = ('*Stock*: \'{}\' \n*Current Price*: ${} \n*Day Range*: '
'${} - ${} \n*52 Wk Range*: ${} - ${} \n*YoY Change*: {}\n*Market Cap*: '
'${}').format(word.upper(), str(price), str(day_low), str(day_high),
str(year_low), str(year_high), str(yoy), str(market_cap))
else:
output_string = "Can't find a stock with the symbol \'" + cleanword.upper() + "\'"
return output_string
def find_quote(word):
"""Given an individual symbol,
find and return the corresponding financial data
word -- the symbol for which you're finding the data (ex. "GOOG")
"""
cleanword = re.sub('[@<>]', '', word)
share = Share(cleanword)
price = share.get_price()
if price != None:
# Extract data
day_high = share.get_days_high()
day_low = share.get_days_low()
market_cap = share.get_market_cap()
year_high = share.get_year_high()
year_low = share.get_year_low()
yoy = calculate_YoY(share)
output_string = (
'*Stock*: \'{}\' \n*Current Price*: ${} \n*Day Range*: '
'${} - ${} \n*52 Wk Range*: ${} - ${} \n*YoY Change*: {}\n*Market Cap*: '
'${}').format(word.upper(), str(price),
str(day_low), str(day_high), str(year_low),
str(year_high), str(yoy), str(market_cap))
else:
output_string = "Can't find a stock with the symbol \'" + cleanword.upper(
) + "\'"
return output_string
def get_quote(symbol):
share = Share(symbol)
if not share.get_price():
return {}
change_f = float(share.get_change())
change_str = '+%.02f' % change_f if change_f >= 0 else '%.02f' % change_f
change_percent_f = change_f / float(share.get_open()) * 100
change_percent = '+%.02f' % change_percent_f if change_percent_f >= 0 else '%.02f' % change_percent_f
return {
'price': share.get_price(),
'change': change_str,
'change_percent': change_percent,
'open_price': share.get_open(),
'market_cap': share.get_market_cap(),
'year_low': share.get_year_low(),
'year_high': share.get_year_high(),
'day_low': share.get_days_low(),
'day_high': share.get_days_high(),
'volume': share.get_volume(),
'pe_ratio': share.get_price_earnings_ratio() or '-'
}
def stock_search(symbol="YHOO"):
stock = Share(symbol)
open_price = stock.get_open()
close_price = stock.get_prev_close()
price = stock.get_price()
high = stock.get_days_high()
low = stock.get_days_low()
volume = stock.get_volume()
return stock, open_price, close_price, price, high, low, volume
def stock_summary(request, symbol=None):
if symbol == None:
symbol = request.POST['symbol']
current_stock = Stock()
stock = Share(symbol)
current_stock.symbol = symbol.upper()
current_stock.price = stock.get_price()
current_stock.change = stock.get_change()
current_stock.volume = stock.get_volume()
current_stock.prev_close = stock.get_prev_close()
current_stock.stock_open = stock.get_open()
current_stock.avg_daily_volume = stock.get_avg_daily_volume()
current_stock.stock_exchange = stock.get_stock_exchange()
current_stock.market_cap = stock.get_market_cap()
current_stock.book_value = stock.get_book_value()
current_stock.ebitda = stock.get_ebitda()
current_stock.dividend_share = stock.get_dividend_share()
current_stock.dividend_yield = stock.get_dividend_yield()
current_stock.earnings_share = stock.get_earnings_share()
current_stock.days_high = stock.get_days_high()
current_stock.days_low = stock.get_days_low()
current_stock.year_high = stock.get_year_high()
current_stock.year_low = stock.get_year_low()
current_stock.fifty_day_moving_avg = stock.get_50day_moving_avg()
current_stock.two_hundred_day_moving_avg = stock.get_200day_moving_avg()
current_stock.price_earnings_ratio = stock.get_price_earnings_ratio()
current_stock.price_earnings_growth_ratio = stock.get_price_earnings_growth_ratio()
current_stock.price_sales = stock.get_price_sales()
current_stock.price_book = stock.get_price_book()
current_stock.short_ratio = stock.get_short_ratio()
date_metrics = []
url = 'http://chartapi.finance.yahoo.com/instrument/1.0/'+symbol+'/chartdata;type=quote;range=1y/csv'
page = urllib2.urlopen(url).read()
pagebreaks = page.split('\n')
for line in pagebreaks:
items = line.split(',')
if 'Company-Name:' in line:
current_stock.company_name = line[13:len(line)]
current_stock.save()
if 'values' not in items:
if len(items)==6:
hd = HistoricalData(
stock_id = Stock.objects.get(id=int(current_stock.id)).id,
date = items[0][4:6]+'/'+items[0][6:9]+'/'+items[0][0:4],
close = items[1][0:(len(items[1])-2)],
high = items[2][0:(len(items[2])-2)],
price_open = items[3][0:(len(items[3])-2)],
low = items[4][0:(len(items[4])-2)],
volume = items[5][0:-6]+","+items[5][-6:-3]+","+items[5][-3:len(items[5])])
hd.save()
date_metrics.append(hd)
del date_metrics[0]
return render(request, "stock_summary.html", {'current_stock': current_stock, 'date_metrics': date_metrics})
def getAllStockData(ticker):
'''Get a few random tickers.'''
stock = Share(ticker)
stock.refresh()
data = {
'name': stock.get_name(),
'price': stock.get_price(),
'change': stock.get_change(),
'volume': stock.get_volume(),
'prev_close': stock.get_prev_close(),
'open': stock.get_open(),
'avg_daily_volume': stock.get_avg_daily_volume(),
'stock_exchange': stock.get_stock_exchange,
'market_cap': stock.get_market_cap(),
'book_value': stock.get_book_value(),
'ebitda': stock.get_ebitda(),
'dividend_share': stock.get_dividend_share(),
'dividend_yield': stock.get_dividend_yield(),
'earnings_share': stock.get_earnings_share(),
'days_high': stock.get_days_high(),
'days_low': stock.get_days_low(),
'year_high': stock.get_year_high(),
'year_low': stock.get_year_low(),
'50day_moving_avg': stock.get_50day_moving_avg(),
'200day_moving_avg': stock.get_200day_moving_avg(),
'price_earnings_ratio': stock.get_price_earnings_ratio(),
'price_earnings_growth_ratio': stock.get_price_earnings_growth_ratio(),
'get_price_sales': stock.get_price_sales(),
'get_price_book': stock.get_price_book(),
'get_short_ratio': stock.get_short_ratio(),
'trade_datetime': stock.get_trade_datetime(),
'percent_change_from_year_high': stock.get_percent_change_from_year_high(),
'percent_change_from_year_low': stock.get_percent_change_from_year_low(),
'change_from_year_low': stock.get_change_from_year_low(),
'change_from_year_high': stock.get_change_from_year_high(),
'percent_change_from_200_day_moving_average': stock.get_percent_change_from_200_day_moving_average(),
'change_from_200_day_moving_average': stock.get_change_from_200_day_moving_average(),
'percent_change_from_50_day_moving_average': stock.get_percent_change_from_50_day_moving_average(),
'change_from_50_day_moving_average': stock.get_change_from_50_day_moving_average(),
'EPS_estimate_next_quarter': stock.get_EPS_estimate_next_quarter(),
'EPS_estimate_next_year': stock.get_EPS_estimate_next_year(),
'ex_dividend_date': stock.get_ex_dividend_date(),
'EPS_estimate_current_year': stock.get_EPS_estimate_current_year(),
'price_EPS_estimate_next_year': stock.get_price_EPS_estimate_next_year(),
'price_EPS_estimate_current_year': stock.get_price_EPS_estimate_current_year(),
'one_yr_target_price': stock.get_one_yr_target_price(),
'change_percent_change': stock.get_change_percent_change(),
'divended_pay_date': stock.get_dividend_pay_date(),
'currency': stock.get_currency(),
'last_trade_with_time': stock.get_last_trade_with_time(),
'days_range': stock.get_days_range(),
'years_range': stock.get_year_range()
}
return data
def process_tweet(self, text):
organizations = self.extract_orgs(text)
print(organizations)
if not organizations:
print('unable to match a company in this tweet')
return
if len(organizations) > 1:
print(
'tweet is about more than one company, unsure how to proceed')
return
sentiment_scores = self.sentiment_analyzer.polarity_scores(text)
print(sentiment_scores)
for k in sorted(sentiment_scores):
print('{0}: {1}, '.format(k, sentiment_scores[k]), end='')
print() # flush new line
# lookup current price, daily high and low
stock = Share(self.companies[organizations[0]])
price = float(stock.get_price())
high = float(stock.get_days_high())
low = float(stock.get_days_low())
if sentiment_scores['neg'] > 0.75:
# negative sentiment on the stock, short it
position = amount_to_trade(PORTFOLIO_SIZE, RISK_PERCENTAGE, high,
low, price, 'Short')
elif sentiment_scores['pos'] > 0.5:
# positive or neutral sentiment on the stock, buy it
position = amount_to_trade(PORTFOLIO_SIZE, RISK_PERCENTAGE, high,
low, price, 'Buy')
else:
position = (0, 0, 'No Order')
print(
f'Execute Trade: {position[2]} {position[0]} of {self.companies[organizations[0]]}, set stop loss at {position[1]}'
)
questrade_symbol = self.questrade_client.get_symbol(
self.companies[organizations[0]])
print(questrade_symbol)
if questrade_symbol:
order = Order(os.getenv('QUESTRADE_ACCOUNT_NUMBER'),
questrade_symbol['symbolId'],
position[0],
None,
stop_price=position[1],
action=position[2])
trade = self.questrade_client.create_order(order)
print(trade)
def getCurrent(ticker):
"""
Return the most recent stock data through yahoo_finance.
"""
stock = Share(ticker)
stock.refresh() #refresh the query
open_ = stock.get_open()
volume = stock.get_volume()
high = stock.get_days_high()
price = stock.get_price()
time = stock.get_trade_datetime()
low = stock.get_days_low()
return (open_, high, volume, price, time, low)
def strategy1():
print "strategy1"
# the purpose of this strategy is to make sure the stock is progressing
# upwords and has been gradually increasing. I don't want a stock that
# isn't a somewhat straight line
# potentials = set()
potentials = []
f = open("todays-gainers.txt", "r")
for line in f:
name = line.replace('\n', '')
# print name
stock = Share(name)
# print "open: "+stock.get_open()
# print "high: "+stock.get_days_high()
# print "low: "+stock.get_days_low()
# print "curr: "+stock.get_price()
if stock.get_open() is not None:
oo = stock.get_open()
hh = stock.get_days_high()
cc = stock.get_price()
if type(oo) is str and type(hh) is str and type(cc) is str:
o = float(oo)
h = float(hh)
# l = float(stock.get_days_low())
c = float(cc)
delta_open_cur = c - o
delta_high_cur = abs(h - c)
# delta_low_open = abs(l-o)
if delta_open_cur != 0.0 and delta_high_cur != 0.0:
difference_high = delta_high_cur / delta_open_cur * 100.0
else:
difference_high = 0
# difference_low = delta_low_open/delta_open_cur*100.0
if difference_high < 35 and difference_high > -1:
# print "LOOK AT THIS ONE"
potentials.append(name)
print name
change = (1.0 - (o / c)) * 100.0
print change
print "---------------"
# print "DIFFERENCE: "+str(difference_high)
# print "DIFFERENCE LOW: "+str(difference_low)
# message = "Strategy 1:\n"
# message += "These are potentials\n"
# message += str(potentials)
# sendMessage(message)
# printPotentials(potentials)
return potentials
def rec(p):
yahoo = Share(p)
a = yahoo.get_prev_close()
b = yahoo.get_year_high()
c = yahoo.get_year_low()
d = yahoo.get_open()
e = yahoo.get_ebitda()
f = yahoo.get_market_cap()
g = yahoo.get_avg_daily_volume()
h = yahoo.get_dividend_yield()
i = yahoo.get_earnings_share()
j = yahoo.get_days_low()
k = yahoo.get_days_high()
l = yahoo.get_50day_moving_avg()
m = yahoo.get_200day_moving_avg()
n = yahoo.get_price_earnings_ratio()
o = yahoo.get_price_earnings_growth_ratio()
print p
print "Previous Close: ", a
print "Year High", b
print "Year Low", c
print "Open:", d
print "EBIDTA", e
print "Market Cap", f
print "Average Daily Volume", g
print "Dividend Yield", h
print "Earnings per share", i
print "Days Range:", j, "-", k
print "50 Days Moving Average", l
print "200 Days Moving Average", m
print "Price Earnings Ratio", n
print "Price Earnings Growth Ratio", o
import MySQLdb
db = MySQLdb.connect(host="127.0.0.1",
user="******",
passwd="1111",
db="stocks",
local_infile=1)
cur = db.cursor()
cur.execute(
"""
INSERT INTO stockapp_info (symbol, prev_close, year_high, year_low, open_price , ebidta, market_cap, avg_daily_vol , dividend_yield, eps , days_low ,days_high, moving_avg_50, moving_avg_200, price_earnings_ratio, price_earnings_growth_ratio)
VALUES
(%s, %s, %s, %s, %s, %s, %s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
""", (p, a, b, c, d, e, f, g, h, i, j, k, l, m, n, o))
db.commit()
cur.close()
def get_new_stops(symbol, current_stop, spread, start_date):
share = Share(symbol)
day_high = float(share.get_days_high())
day_low = float(share.get_days_low())
newdate = (datetime.datetime.strptime(start_date,"%Y-%M-%d") + datetime.timedelta(days=1)).strftime("%Y-%M-%d")
prices = share.get_historical(start_date, today)
days_high=max([float(y['High']) for y in prices] + [day_high])
days_low=min([float(y['Low']) for y in prices] + [day_low])
print symbol
if days_low < current_stop:
print "%s - stop activated! , days_low-%s" % (symbol,days_low)
print days_low
elif (days_high - spread) > current_stop:
print "%s - new stop: %s" % (symbol, days_high - spread)
def yahoo_aktuell(self):
#symbol = '^NDX'
# symbol = 'FB'
wp = Share(self.wertpapier.ric)
open = wp.get_open()
high = wp.get_days_high()
low = wp.get_days_low()
close = wp.get_price()
time = wp.get_trade_datetime()
# MEZ: +1 Stunde
# MESZ: +2 Stunden
# Close KO: Uhrzeit: 2017-04-04 20:00:00 UTC+0000 => 22 Uhr
# Close NDX: Uhrzeit: 2017-04-04 21:15:00 UTC+0000 => 23:15 Uhr
print('Symbol:', self.wertpapier.ric, 'Kursdaten:', open, high, low,
close)
print('Uhrzeit:', time)
def main():
PATH_OF_DATA = 'data'
error_log_file = open('error.log', 'a')
index_lists = [f[:-4] for f in listdir(PATH_OF_DATA) if f[-4:] == '.csv']
skipFlag = True if len(sys.argv) > 1 else False
tillFlag = True if len(sys.argv) > 2 else False
for stock_index in index_lists:
if skipFlag:
if stock_index != sys.argv[1]:
continue
else:
skipFlag = False
if tillFlag:
if stock_index == sys.argv[2]:
break
filename = join(PATH_OF_DATA, stock_index + '.csv')
if isfile(filename): # 如果已經有檔案，就讀出最後一行然後插入在後面
lastline = get_last_row(filename)
print 'lastline = ', lastline
try:
st = Share(stock_index + '.tw')
if not time_after(lastline[0], st.get_trade_datetime()[:10]):
print 'time : ', st.get_trade_datetime()[:10]
fo = open(filename, 'ab')
cw = csv.writer(fo, delimiter=',')
# 更新當天資料
cw.writerow([
st.get_trade_datetime()[:10],
st.get_open(),
st.get_days_high(),
st.get_days_low(),
st.get_price(),
st.get_volume(), '0.0'
])
print "更新一筆！"
else:
print "不需要更新"
except:
print stock_index, "update error!"
error_log_file.write('%s, Update Error\n' % (stock_index))
def post(): ## Update stock info try: stock_list = Stock.objects.all() for stock in stock_list: try: s = Share(stock.symbol) stock.price = s.get_price() stock.open_price = s.get_open() stock.pre_close_price = s.get_prev_close() stock.high_price = s.get_days_high() stock.low_price = s.get_days_low() stock.save() except Exception, e: pass except Exception, e: pass
def get_today_stock_data(ticker):
try:
s = Share(ticker)
data = {
'Open': float(s.get_open()),
'Close': float(s.get_prev_close()),
'High': float(s.get_days_high()),
'Low': float(s.get_days_low()),
'Volume': int(s.get_volume()),
'Date': datetime.date.today(),
}
return data
except YQLQueryError:
logger.error("Daily data not found for {}".format(ticker))
except Exception as e:
logger.error("Unexpected error occurred: {}".format(e))
return {}
def get_today_stock_data(ticker):
try:
s = Share(ticker)
data = {
'Open': float(s.get_open()),
'Close': float(s.get_prev_close()),
'High': float(s.get_days_high()),
'Low': float(s.get_days_low()),
'Volume': int(s.get_volume()),
'Date': datetime.date.today(),
}
return data
except YQLQueryError:
logger.error("Daily data not found for {}".format(ticker))
except Exception as e:
logger.error("Unexpected error occurred: {}".format(e))
return {}
def RealTime(filepath,instrument):
# Download CSV from yahoo if the CSV does not already exist.
if not isfile(filepath):
download_daily_bars(instrument,2016,filepath)
# Get Live Results from Yahoo Database and append to CSV
s = Share(instrument)
date = datetime.today().strftime('%Y-%m-%d')
O,H,L,C,V,AC = (s.get_open(), s.get_days_high(), s.get_days_low(), s.get_price(),
s.get_volume(),s.get_price())
#Date,Open,High,Low,Close,Volume,Adj Close
field = [date,O,H,L,C,V,AC]
with open(filepath,'a') as csvfile:
old = csv.writer(csvfile)
add = old.writerow(field)
def rec(p):
yahoo = Share(p)
a=yahoo.get_prev_close()
b=yahoo.get_year_high()
c=yahoo.get_year_low()
d=yahoo.get_open()
e=yahoo.get_ebitda()
f=yahoo.get_market_cap()
g=yahoo.get_avg_daily_volume()
h=yahoo.get_dividend_yield()
i=yahoo.get_earnings_share()
j=yahoo.get_days_low()
k=yahoo.get_days_high()
l=yahoo.get_50day_moving_avg()
m=yahoo.get_200day_moving_avg()
n=yahoo.get_price_earnings_ratio()
o=yahoo.get_price_earnings_growth_ratio()
print p
print "Previous Close: ",a
print "Year High",b
print "Year Low",c
print "Open:",d
print "EBIDTA",e
print "Market Cap",f
print "Average Daily Volume",g
print "Dividend Yield",h
print "Earnings per share",i
print "Days Range:", j ,"-",k
print "50 Days Moving Average",l
print "200 Days Moving Average",m
print"Price Earnings Ratio", n
print"Price Earnings Growth Ratio",o
import MySQLdb
db = MySQLdb.connect(host="127.0.0.1", user="******",passwd="1111", db="stocks",local_infile = 1)
cur=db.cursor()
cur.execute ("""
INSERT INTO stockapp_info (symbol, prev_close, year_high, year_low, open_price , ebidta, market_cap, avg_daily_vol , dividend_yield, eps , days_low ,days_high, moving_avg_50, moving_avg_200, price_earnings_ratio, price_earnings_growth_ratio)
VALUES
(%s, %s, %s, %s, %s, %s, %s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
""", (p,a,b,c,d,e,f,g,h,i,j,k,l,m,n,o))
db.commit()
cur.close()
def sp500info(): #gets the S&P 500 price, ticker, changes, etc.
sp500ticker = '^GSPC'
sp500desc = "S&P 500 Index: "
sp500index = Share(sp500ticker)
#sp500price = sp500index.get_price()
sp500price = scraper(sp500ticker)
#sp500change = sp500index.get_change()
sp500open = sp500index.get_open()
#print sp500index.get_50day_moving_avg()
#print sp500index.get_200day_moving_avg()
#print sp500ma50, sp500ma200
sp500price = str(sp500price).strip('[]')
sp500price = sp500price.replace(",", "")
#print(repr(sp500price)) #scrub the ticker for hidden values; troubleshooting
sp500change = float(sp500price) - float(sp500open)
sp500dayhigh = sp500index.get_days_high()
sp500percentchange = getPercentChange(sp500index, sp500change, sp500open)
return sp500percentchange, sp500dayhigh, sp500open, sp500change, sp500price, sp500index, sp500desc
def main():
PATH_OF_DATA = 'data'
error_log_file = open('error.log', 'a')
index_lists = [ f[:-4] for f in listdir(PATH_OF_DATA) if f[-4:] == '.csv' ]
skipFlag = True if len(sys.argv) > 1 else False
tillFlag = True if len(sys.argv) > 2 else False
for stock_index in index_lists:
if skipFlag:
if stock_index != sys.argv[1]:
continue
else:
skipFlag = False
if tillFlag:
if stock_index == sys.argv[2]:
break
filename = join(PATH_OF_DATA, stock_index+'.csv')
if isfile(filename):# 如果已經有檔案，就讀出最後一行然後插入在後面
lastline = get_last_row(filename)
print 'lastline = ', lastline
try:
st = Share(stock_index+'.tw')
if not time_after(lastline[0], st.get_trade_datetime()[:10]):
print 'time : ', st.get_trade_datetime()[:10]
fo = open(filename, 'ab')
cw = csv.writer(fo, delimiter=',')
# 更新當天資料
cw.writerow([st.get_trade_datetime()[:10], st.get_open(), st.get_days_high(),
st.get_days_low(), st.get_price(), st.get_volume(), '0.0'])
print "更新一筆！"
else:
print "不需要更新"
except:
print stock_index, "update error!"
error_log_file.write('%s, Update Error\n' % (stock_index))
def fetch_current_data(self, sym):
ts = get_latest_trading_date(get_cur_time())
if ts in self.datasets_daily[sym].keys() or ts > self.endDate:
return
try:
sdata = Share(sym)
gquote = gQuotes(sym)
except:
# live with the fact that data from the most recent day is missing
return
self.datasets_daily[sym][ts] = t = {}
t['Date'] = '3000-01-01' #debugging purposes, so we know this is current. This won't be saved to file
t['High'] = float(sdata.get_days_high())
t['Low'] = float(sdata.get_days_low())
t['Open'] = float(sdata.get_open())
# t['Close'] = sdata.get_price()
t['Close'] = float(gquote[0]['LastTradePrice']) # use google data for latest 'Close', which is more accurate
t['Volume'] = float(sdata.get_volume())
for k in t.keys():
if t[k] == None:
raise Exception('missing most recent daily', sym)
def getStock(ticker):
stock = Share(ticker)
#name = stock.get_name()
po = str(stock.get_open())
pn = str(stock.get_price())
pcl = str(stock.get_prev_close())
pc = str(stock.get_percent_change())
low = str(stock.get_days_low())
high = str(stock.get_days_high())
h = datetime.now().strftime("%I")
p = datetime.now().strftime("%p")
x = ticker.upper() + "\nCurrent: " + pn +"\nClose: " + pcl + "\nChange: "+ pc + "\nLow: " + low + "\nHigh: " + high
y = ticker.upper() + "\nCurrent: " + pn + "\nOpen: " + po + "\nChange: " + pc + "\nLow: " + low + "\nHigh: " + high
if h <= "4" and p == "PM":
return x
elif h >= "4" and p == "PM":
return y
elif h <= "8" and p == "AM":
return y
else:
return x
def postStockHistory(self) -> None:
for stockID in self.stocksToMonitor:
timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
currentDate = timestamp[:10]
# Get the average MySQL query
avgQuery = StockQueries.getAverageQuery("stock_activity_price",
"stock_activity",
"stock_activity_date",
currentDate)
# Get the average value
average = self.sd.getAverageValue(avgQuery)
if average == None:
average = -1
yahoo = Share(stockID)
# Get the schema of the stock_history table and format it as a comma delimited
# string for use in the MySQL query.
stockHistoryAttributes = self.tableDict.get("stock_history")
attributesString = self._attrsToCommaDeliminatedString(
stockHistoryAttributes)
try:
# Format as a comma delimted string for use in the SQL query
attributesToInsert = self._attrsToCommaDeliminatedString([
'"' + stockID + '"', '"' + currentDate + '"',
yahoo.get_open(), average,
yahoo.get_price(),
yahoo.get_days_high(),
yahoo.get_days_low()
])
except YQLQueryError:
logging.warning("Yahoo finance is currently unavailable.")
insQuery = StockQueries.getInsertQuery("stock_history",
attributesString,
attributesToInsert)
self.sd.runQuery(insQuery)
def history():
# If a user goes to the display page and a session is not active
if session.get('active') != True:
sym = 'SPY'
session['active'] = True
session['sym'] = sym
else:
sym = session['sym'] # if a session is active leave the sym alone
share = Share(sym)
historical = share.get_historical('2016-03-13', '2016-04-15')
canvas_list = []
for day in historical:
canvas_list.append([int(day['Date'][:4]),
int(day['Date'][5:7]) - 1,
int(day['Date'][-2:]),
float(day['Open']),
float(day['High']),
float(day['Low']),
float(day['Close'])
])
info = share.get_info()
open = share.get_open()
high = share.get_days_high()
low = share.get_days_low()
price = share.get_price()
canvas_list.append([int(info['end'][:4]),
int(info['end'][5:7]) - 1,
int(info['end'][-2:]),
float(open),
float(high),
float(low),
float(price)
])
return render_template('history.html',
canvas_list=canvas_list,
sym=sym)
def getHistoricalData(ticker, daysAgo):
try:
yahooHoo = Share(ticker)
except ValueError:
print "Couldn't 'Share("+str(ticker)+")'"
data=yahooHoo.get_historical(dateDaysAgo(daysAgo), today())
try:
empty={}
element={'Volume': yahooHoo.get_volume(), 'Symbol': ticker, 'High': yahooHoo.get_days_high(), 'Low': yahooHoo.get_days_low(), 'Open': yahooHoo.get_open(), 'Close': yahooHoo.get_price(), 'Date': yahooHoo.get_trade_datetime()[0:10]}
data.append(element)
except ValueError:
print "LALALA"
if len(data) > 0:
data = sorted(data, key=lambda k: k['Date'], reverse=False) #Sort by Date of json element
#try:
# if data[-1]['Date'] != element['Date']:
# data.append(element)
#except ValueError:
# print "DOH"
#data = sorted(data, key=lambda k: k['Date'], reverse=False) #Sort by Date of json element
return data
class stockdata:
def __init__(self, symb, online=1):
self._symb = symb
# <class 'yahoo_finance.Share'>
if (online):
try:
self.body = Share(symb)
except:
self.body = np.nan
print("Share error:", self._symb)
def get_price(self):
'''
get today's price
if market closed, the price is the close price
Returns
-------
price : str
'''
price = self.body.get_price()
return price
def get_days_high(self):
'''
get today's high price
Returns
-------
dayhigh : str
'''
dayhigh = self.body.get_days_high()
return dayhigh
def get_days_low(self):
'''
get today's low price
Returns
-------
daylow : str
'''
daylow = self.body.get_days_low()
return daylow
def get_historical(self, start_date, end_date):
'''
Parameters
----------
start_date : str
'year-month-day', for example '2015-10-01'
end_date : str
Returns
-------
historical : dlist, dict list
historical : <class 'list'>
historical[0] : <class 'dict'>
historical[0][High] : <class 'str'>
for example:
[{'Adj_Close': '75.620003',
'Close': '75.620003',
'Date': '2015-10-23',
'High': '75.760002',
'Low': '72.839996',
'Open': '73.980003',
'Symbol': 'BABA',
'Volume': '22342100'},
{}, ... {}]
'''
historical = self.body.get_historical(start_date, end_date)
return historical
def save_historical_file(self, start_date, end_date):
'''
save historical data to excel file in form of DataFrame
the file name is 'get_historical_SYMB_ENDATE.xlsx', for example, 'get_historical_YHOO_2015-10-24.xlsx'
Parameters
----------
start_date : str
'year-month-day', for example '2015-10-01'
end_date : str
Returns
-------
len : int
length of historical
'''
try:
historical = self.body.get_historical(start_date, end_date)
except:
print("get_historical error:", self._symb, start_date, end_date)
return 0
length = len(historical)
if (length == 0):
#print("len is 0:", self._symb)
return 0
# check data
try:
high = float(historical[0]['High'])
except:
print("get_high error:", self._symb)
return 0
df = pd.DataFrame(historical)
file_name = './data/' + self._symb + '_historical_' + end_date + '.xlsx'
df.to_excel(file_name)
return length
def read_historical_file(self, end_date):
'''
read historical data from file
the file name is 'get_historical_SYMB_ENDATE.xlsx', for example, 'get_historical_YHOO_2015-10-24.xlsx'
Parameters
----------
end_date : str
'year-month-day', for example '2015-10-01'
Returns
-------
df : DataFrame of Pandas
df : <class 'pandas.core.frame.DataFrame'>
df[:1] : <class 'pandas.core.frame.DataFrame'>
df.High(df['High']) : <class 'pandas.core.series.Series'>
df.loc[0] : <class 'pandas.core.indexing._LocIndexer'>
df.iloc[0] : <class 'pandas.core.indexing._iLocIndexer'>
for example:
Adj_Close Close Date High Low Open Symbol Volume
0 75.620003 75.620003 2015-10-23 75.760002 72.839996 73.980003 BABA 22342100
1 70.989998 70.989998 2015-10-22 71.629997 70.070000 70.160004 BABA 10691400
2 69.480003 69.480003 2015-10-21 71.790001 68.889999 71.790001 BABA 16800200
'''
file_name = './data/' + self._symb + '_historical_' + end_date + '.xlsx'
# file_name = './data/get_historical_' + self._symb + '_' + end_date + '.xlsx'
try:
df = pd.read_excel(file_name)
except FileNotFoundError as e:
df = pd.DataFrame({[]})
print(e, self._symb)
self._df = df
return df
# get date through row
def fget_date(self, row):
val = self._df.Date[row]
return val
def fget_close(self, row):
val = self._df.Close[row]
return val
def fget_high(self, row):
val = self._df.High[row]
return val
def fget_low(self, row):
val = self._df.Low[row]
return val
# get date through row && col
def fget_data(self, col, row):
# val = self._df[col][row]
# return val
return 0
continue
stock = Share(ticker)
stock.refresh()
change = (float(stock.get_price()) - float(
stock.get_prev_close())) / float(stock.get_prev_close())
change = round(change * 100.0, 2)
if change > 0.0:
change = '+' + str(change)
else:
change = str(change)
line = ticker.ljust(7)
line += stock.get_price().ljust(9)+ change.ljust(8)+ stock.get_volume().ljust(11) + \
str(round(float(stock.get_volume())/float(stock.get_avg_daily_volume())*100.0)).ljust(8) +\
stock.get_open().ljust(10)+ \
stock.get_days_low().ljust(10)+ \
stock.get_days_high().ljust(10)+ \
stock.get_year_low().ljust(10)+ \
stock.get_year_high().ljust(10)
line = line + str(stock.get_market_cap()).ljust(11) + \
str(stock.get_price_earnings_ratio()).ljust(8)+\
stock.get_50day_moving_avg().ljust(10) +\
stock.get_200day_moving_avg().ljust(10)
print(line)
except Exception as e:
print("Exception error:", str(e))
traceback.print_exc()
i += 1
#you get get a spy.txt and then filter everything by yourself
def main():
# 1. get the time
day = Time.get_utc_day()
hours_mins = Time.get_utc_hours_minutes()
# 1. Get all the list of stocks
stocks = base.managers.stock_manager.get_many()
# 2. go through stock and update the desired values
for stock in stocks:
ticker = stock.get('ticker')
try:
# 2.1 Get the info from the yahoo API
updated_stock = Share(ticker)
except:
print "-->Failed to update: %s with Yahoo API" % ticker
continue
price = updated_stock.get_price()
open = updated_stock.get_open()
days_high = updated_stock.get_days_high()
days_low = updated_stock.get_days_low()
year_high = updated_stock.get_year_high()
year_low = updated_stock.get_year_low()
volume = updated_stock.get_volume()
market_cap = updated_stock.get_market_cap()
pe_ratio = updated_stock.get_price_earnings_ratio()
div_yield = updated_stock.get_dividend_yield()
change = updated_stock.get_change()
change_percent = updated_stock.data_set.get('ChangeinPercent')
# 2.2 Get the stock body
stock_body = stock.get('body')
stock_price = {hours_mins: price}
if stock_body:
# 1. Get the stock info for the day:
stock_info = stock_body.get(day)
if stock_info:
stock_price = stock_info.get('price')
stock_price.update({hours_mins: price})
else:
stock_body = {}
# 2.2.4 update the stock info dict
stock_info = {'price': stock_price}
stock_info.update({'open': open})
stock_info.update({'days_high': days_high})
stock_info.update({'days_low': days_low})
stock_info.update({'year_high': year_high})
stock_info.update({'year_low': year_low})
stock_info.update({'volume': volume})
stock_info.update({'market_cap': market_cap})
stock_info.update({'pe_ratio': pe_ratio})
stock_info.update({'div_yield': div_yield})
stock_info.update({'change': change})
stock_info.update({'change_percent': change_percent})
# update the stock body
stock_body.update({day: stock_info})
stock.body = stock_body
# 3. update the stock in the DB
try:
base.managers.stock_manager.update_one(stock)
except:
print "-->Failed to update: %s in DB" % ticker
continue
# Determine functionality
from yahoo_finance import Share
tesla = Share('TSLA')
print tesla.get_price()
print tesla.get_market_cap()
print "get_book_value:", tesla.get_book_value()
print "get_ebitda:", tesla.get_ebitda()
print "get_dividend_share:", tesla.get_dividend_share()
print "get_dividend_yield:", tesla.get_dividend_yield()
print "get_earnings_share:", tesla.get_earnings_share()
print "get_days_high:", tesla.get_days_high()
print "get_days_low:", tesla.get_days_low()
print "get_year_high:", tesla.get_year_high()
print "get_year_low:", tesla.get_year_low()
print "get_50day_moving_avg:", tesla.get_50day_moving_avg()
print "get_200day_moving_avg:", tesla.get_200day_moving_avg()
print "get_price_earnings_ratio:", tesla.get_price_earnings_ratio()
print "get_price_earnings_growth_ratio:", tesla.get_price_earnings_growth_ratio(
)
print "get_price_sales:", tesla.get_price_sales()
print "get_price_book:", tesla.get_price_book()
print "get_short_ratio:", tesla.get_short_ratio()
print "get_trade_datetime:", tesla.get_trade_datetime()
# "a:", print tesla.get_historical(start_date, end_date)
# "a:", print tesla.get_info()
print "get_name:", tesla.get_name()
print "refresh:", tesla.refresh()
print "get_percent_change_from_year_high:", tesla.get_percent_change_from_year_high(
)
print("Stock: %12s TimeStamp: %20s" % (stock, t))
# sample: yahoo = Share('YHOO')
# print t, yahoo.get_open(), yahoo.get_price(), yahoo.get_days_high(), yahoo.get_days_low()
# update timestamp
t = time.strftime('%Y-%m-%dT%H:%M:%S')
# get yahoo finacne information
shareinfo = Share(stock)
# print share information
print(
"lc: %d price: %s open: %s dayhigh: %s daylow: %s volume: %s"
% (x, shareinfo.get_price(), shareinfo.get_open(),
shareinfo.get_days_high(), shareinfo.get_days_low(),
shareinfo.get_volume()))
# line space
print
# write data to csv file
writer.writerow({
'ts': t,
'symbol': stock,
'price': shareinfo.get_price(),
'open': shareinfo.get_open(),
'days_high': shareinfo.get_days_high(),
'days_low': shareinfo.get_days_low(),
'volume': shareinfo.get_volume()
})
config = {
'user': '******',
'password': '******',
'host': '192.168.XXX.XXX',
'port': '3306',
'database': 'dbname',
'raise_on_warnings': True,
}
cnx = mysql.connector.connect(**config)
cursor = cnx.cursor()
cursor.execute("SHOW TABLES")
tables = cursor.fetchall()
for YTicker in tables:
x = str(YTicker[0])
Symbol = x.replace("_", ".")
print(Symbol)
yahoo = Share(Symbol)
Date = time.strftime("%Y-%m-%d")
Adj_Close = yahoo.get_price()
High = yahoo.get_days_high()
Low = yahoo.get_days_low()
Volume = yahoo.get_volume()
add_value = (
"INSERT INTO " + YTicker[0] +
" (Symbol, Date, Adj_Close, High, Low, Volume) VALUES (%s, %s, %s, %s, %s, %s)"
)
data = (Symbol, Date, Adj_Close, High, Low, Volume)
cursor.execute(add_value, data)
cnx.commit()
print(YTicker[0] + " updated... to" + Adj_Close)
def predict():
today = dt.date.today()
if today.isoweekday() == 6:
pred_date = today - dt.timedelta(1)
elif today.isoweekday() == 7:
pred_date = today - dt.timedelta(2)
else:
pred_date = today
pred_day = int(pred_date.day)
pred_month = int(pred_date.month)
pred_year = int(pred_date.year)
# If a user goes to the display page and a session is not active
if session.get('active') != True:
sym = 'SPY'
session['active'] = True
session['sym'] = sym
else:
sym = session['sym'] # if a session is active leave the sym alone
try: # Error handling... Some Stock symbols exist but there is no historical information in Yahoo Finance...
share = Share(sym)
historical = share.get_historical(str(today - dt.timedelta(5)), str(today - dt.timedelta(1))) # need to auto input the date...
canvas_list = []
info = share.get_info()
open = share.get_open()
high = share.get_days_high()
low = share.get_days_low()
price = share.get_price()
canvas_list.append([int(info['end'][:4]),
int(info['end'][5:7]) - 1,
int(info['end'][-2:]),
float(price)
])
for day in historical:
canvas_list.append([int(day['Date'][:4]),
int(day['Date'][5:7]) - 1,
int(day['Date'][-2:]),
float(day['Close'])
])
df_preds = pd.read_csv('data/predictions.csv')
date = df_preds[df_preds['sym'] == sym]['date'].values[0]
historical_day = float(share.get_historical(date, date)[0]['Close'])
year = date[:4]
month = date[5:7]
day = date[-2:]
predicted_value = historical_day + df_preds[df_preds['sym'] == sym]['regressor_mse'].values[0]
predicted_rmse = df_preds[df_preds['sym'] == sym]['mse'].values[0] ** .5
box1_low = predicted_value - (predicted_rmse / 2.)
box1_high = predicted_value + (predicted_rmse / 2.)
box2_low = predicted_value - (predicted_rmse)
box2_high = predicted_value + (predicted_rmse)
return render_template('predict.html',
canvas_list=canvas_list,
sym=sym,
box1_low=box1_low,
box1_high=box1_high,
box2_low = box2_low,
box2_high=box2_high,
year=year,
month=month,
day=day,
pred_day=pred_day,
pred_month=pred_month,
pred_year=pred_year)
except:
return redirect("/error")
def main():
global shareName
global stream
global buyPrice
global shareAmount
global currentBallance
global beforePrice
global dayOpen
global dayHigh
global dayLow
cls()
start = 1
prevPrice = 0
textNum = 1
textNumLimit = 6
sellPriceReached = False
buyPrice = 131.09
beforePrice = buyPrice
shareAmount = 10
shareName = raw_input("Enter The Share You Would Like To Monitor:\n" + "--"*25 + "\n> ").strip().upper() #YHOO
alertPrice = buyPrice * 1.20
riskThreshold = buyPrice / 1.20
cls()
waitTime = 1 #Until Starts
initDatabase()
UpDownValues = [""]
print ">" + "-"*52 + ":Monitoring_Share_[" + shareName + "]:" + "-"*52 + "<"
while True:
try:
status = most_common(UpDownValues)
share = Share(shareName)
price = getPrice(share, "false", None)
dayOpen = share.get_open()
dayHigh = share.get_days_high()
dayLow = share.get_days_low()
if price == prevPrice:
pass
else:
info = getPrice(share, "true", status)
saveToDatabase(info, 1)
print info
if price > prevPrice:
UpDownValues.append("UP")
elif price < prevPrice:
UpDownValues.append("DOWN")
if len(UpDownValues) > 15: #Risk Threshold to pull out
UpDownValues.pop()
if float(price) >= float(alertPrice):
if str(status) == "DOWN":
if price < riskThreshold:
sellShares(shareAmount/2)
#sendMessage("Current Status:\n" + str(sellProfit("phone")) + "\n>" + "---"*5 + "<\nSell Half of Shares.")
elif str(status) == "UP":
if price >= buyPrice:
if price >= alertPrice:
sellPriceReached = True
sellShares(shareAmount)
if textNum <= textNumLimit:
#sendMessage("Current Status:\n" + str(sellProfit("phone")) + "\n>" + "---"*5 + "<\nBen's Monitor.")
pass
else:
pass
if sellPriceReached == True:
if price < alertPrice - 10:
sellShares("All")
prevPrice = price
xValue = getTime()
yValue = price
time.sleep(0.3) #Default: (0.3)
except Exception, e:
exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
if "'str' and 'NoneType'" in str(e):
raw_input("-"*75 + "\nCurrent Share Status:\n[Error] | Unable to find the share: [" + shareName + "] | Press (Enter) To Go Back To Main Menu.\n" + "> ")
main()
elif "object has no attribute" in str(e):
pass
elif "Query failed with error" in str(e):
pass
elif "Expecting value: line 1 column 1 (char 0)" in str(e):
pass
elif "float() argument must be a string or a number" in str(e):
cls()
raw_input("[Input Error] | Unable To Find Share(" + shareName + ")\nPress Enter To Retry:\n>------------------------------------------------<\n> ")
main()
else:
print "[Error] " + str(exc_tb.tb_lineno) + " | > " + str(e)
except KeyboardInterrupt:
print "\n"*2 + sellProfit("pause")
chs = raw_input(">"+"---"*16 + "<\n> Main Menu----------------(1)\n> Continue Monitoring------(Any Key)\n>" + "-"*36 + "<\n> ")
if "2" in chs:
main()
else:
print "\n>" + "-"*36 + ":Monitoring_Share_[" + shareName + "]_Continued:" + "-"*36 + "<"
def on_message(self, message):
print_logger.debug("Received message: %s" % (message))
if "ValidateTicker" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed ticker validation request")
self.write_message("ValidationFailed:Malformed")
return
ticker = message[1]
if validate_ticker(ticker):
self.write_message("ValidationSucceeded:%s" % ticker)
print_logger.debug("Ticker was valid")
else:
self.write_message("ValidationFailed:%s" % ticker)
print_logger.debug("Ticker was bad")
return
elif "GetCompanyName" in message:
print_logger.debug("You got here")
message = message.split(":")
company_ticker = message[1]
company_name = get_company_title(company_ticker)
self.write_message("CompanyName:%s" % company_name)
elif "GetStockData" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get ticker information
share_data = Share(ticker)
price = share_data.get_price()
percent_change = share_data.get_change()
previous_close = share_data.get_prev_close()
open_price = share_data.get_open()
volume = share_data.get_volume()
pe_ratio = share_data.get_price_earnings_ratio()
peg_ratio = share_data.get_price_earnings_growth_ratio()
market_cap = share_data.get_market_cap()
book_value = share_data.get_price_book()
average_volume = share_data.get_avg_daily_volume()
dividend_share = share_data.get_dividend_share()
dividend_yield = share_data.get_dividend_yield()
earnings_per_share = share_data.get_earnings_share()
ebitda = share_data.get_ebitda()
fifty_day_ma = share_data.get_50day_moving_avg()
days_high = share_data.get_days_high()
days_low = share_data.get_days_low()
year_high = share_data.get_year_high()
year_low = share_data.get_year_low()
two_hundred_day_ma = share_data.get_200day_moving_avg()
# Build a string to send to the server containing the stock data
share_string = "price:" + str(price) + "|"\
+ "percentChange:" + str(percent_change) + "|"\
+ "previousClose:" + str(previous_close) + "|"\
+ "openPrice:" + str(open_price) + "|"\
+ "volume:" + str(volume) + "|"\
+ "peRatio:" + str(pe_ratio) + "|"\
+ "pegRatio:" + str(peg_ratio) + "|"\
+ "marketCap:" + str(market_cap) + "|"\
+ "bookValue:" + str(book_value) + "|"\
+ "averageVolume:" + str(average_volume) + "|"\
+ "dividendShare:" + str(dividend_share) + "|"\
+ "dividendYield:" + str(dividend_yield) + "|"\
+ "earningsPerShare:" + str(earnings_per_share) + "|"\
+ "ebitda:" + str(ebitda) + "|"\
+ "50DayMa:" + str(fifty_day_ma) + "|"\
+ "daysHigh:" + str(days_high) + "|"\
+ "daysLow:" + str(days_low) + "|"\
+ "yearHigh:" + str(year_high) + "|"\
+ "yearLow:" + str(year_low) + "|"\
+ "200DayMa:" + str(two_hundred_day_ma) + "|"
self.write_message("StockData;%s" % (share_string))
print_logger.debug("Sending Message: StockData;%s" % (share_string))
elif "GetCompanyDesc" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
description = update_description_oneoff(ticker)
self.write_message("CompanyDescription:%s" % str(description))
elif "GetCompanyDividend" in message and "Record" not in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Grab the dividend data from dividata.com
dividend_url = "https://dividata.com/stock/%s/dividend" % ticker
# This should potentially be a
dividend_data = requests.get(dividend_url)
dividend_soup = BeautifulSoup(dividend_data.text, 'html5lib')
if len(dividend_soup.find_all("table")) > 0:
dividend_soup = dividend_soup.find_all("table")[0]
else:
dividend_soup = "<h3>No dividend history found.</h3>"
# Send this div up to the server
self.write_message("DividendHistoryData:" + str(dividend_soup))
elif "GetCompanyDividendRecord" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get the dividend record html for the table and send it up
#dividend_record = strip_dividends(ticker, req_proxy)
#print_logger.debug("Writing message: " + str(dividend_record))
#self.write_message("DividendRecord:" + str(dividend_record))
elif "GetBollinger" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Switch into the tmp directory
old_dir = os.getcwd()
os.chdir(TEMP_DIR)
# Update the historical data for the ticker symbol
YAHOO_FINANCE_HISTORICAL_OBJECT.read_ticker_historical(ticker)
bands = BollingerBandStrategy(data_storage_dir="%s/historical_stock_data" % TEMP_DIR\
, ticker_file="%s/stock_list.txt" % TEMP_DIR, filtered_ticker_file=\
"%s/filtered_stock_list.txt" % TEMP_DIR)
# Save the graph so that we can show it on the website
bands.save_stock_chart(ticker, "%s" % TEMP_DIR)
# Also let the server know that we found an answer
result = bands.test_ticker(ticker)
if result is not None:
print_logger.debug("BB:GoodCandidate")
self.write_message("BB:GoodCandidate")
else:
print_logger.debug("BB:BadCandidate")
self.write_message("BB:BadCandidate")
elif "CheckRobinhoodLogin" in message:
print "HELLO WORLD!!! HELLO WORLD!!! HELLO WORLD!!!%s" % ROBINHOOD_INSTANCE
if ROBINHOOD_INSTANCE.is_logged_in() is True:
self.write_message("RobinhoodLoggedIn:%s" % ROBINHOOD_INSTANCE.username)
else:
self.write_message("RobinhoodNotLoggedIn")
elif "GetPosition" in message:
ticker = message.replace("GetPosition:", "")
account_positions = ROBINHOOD_INSTANCE.get_position_history(active=True)
user_owns_stock = False
position_string = ""
for position in account_positions:
# Get data about the position, including current price.
position_data = requests.get(position["instrument"])
position_data = json.loads(position_data._content)
position.update(position_data)
if position["symbol"] != ticker:
continue
quote_data = requests.get(position["quote"]);
quote_data = json.loads(quote_data._content)
position.update(quote_data)
position_string = json.dumps(position)
user_owns_stock = True
if user_owns_stock is True:
self.write_message("Position:%s" % position_string)
else:
self.write_message("Position:None")
print getbook if myargs.dividendshare is True: getdiv = stock.get_dividend_share() print getdiv if myargs.dividendyield is True: dividendyield = stock.get_dividend_yield() print dividendyield if myargs.eps is True: eps = stock.get_earnings_share() print eps if myargs.dayh is True: dayhigh = stock.get_days_high() print dayhigh if myargs.dayl is True: daylow = stock.get_days_low() print daylow if myargs.yearhigh is True: yearhigh = stock.get_year_high() print yearhigh if myargs.yearlow is True: yearlow = stock.get_year_low() print yearlow if myargs.ebitda is True:
def on_message(self, message):
print_logger.debug("Received message: %s" % (message))
self.write_message("Test Message")
if "ValidateTicker" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed ticker validation request")
self.write_message("ValidationFailed:Malformed")
return
ticker = message[1]
# The file I have stored didn't end up being a good validation
# option as it does not contain a complete list of all
# securities. I have to acquire the data from yahoo
# finance anyway, so just use that. The Share function
# call will throw a NameError exception if the ticker doesn't exist
# isValid = current_stock_list.is_valid_stock(ticker)
isValid = True
try:
test = Share(str(ticker))
if test.get_price() is None:
isValid = False
except NameError:
isValid = False
if isValid:
self.write_message("ValidationSucceeded:%s" % ticker)
print_logger.debug("Ticker was valid")
else:
self.write_message("ValidationFailed:%s" % ticker)
print_logger.debug("Ticker was bad")
return
elif "GetCompanyName" in message:
print_logger.debug("You got here")
message = message.split(":")
company_ticker = message[1]
company_name = ""
try:
company_info="../task_1/google_search_program/cleaned_data/" + company_ticker + "/company_info"
company_name = " "
f = open(company_info, "r")
line = f.readlines()
company_name = line[0].split(",")
company_name = company_name[0]
company_name = company_name.title()
if '(' not in company_name:
company_name = company_name + " (%s)" % company_ticker
except Exception:
company_name = get_company_title_proxied(company_ticker)
self.write_message("CompanyName:%s" % company_name)
elif "ExecuteQuery" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed input query")
self.write_message("QueryResult:Error")
data = current_solr_object.issue_query(str(message[1]))
data = current_solr_object.recover_links(data)
final_string = "QueryResult"
for link in data:
final_string = final_string + ":" + str(link)
self.write_message(final_string)
elif "GetStockData" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get ticker information
share_data = Share(ticker)
price = share_data.get_price()
percent_change = share_data.get_change()
previous_close = share_data.get_prev_close()
open_price = share_data.get_open()
volume = share_data.get_volume()
pe_ratio = share_data.get_price_earnings_ratio()
peg_ratio = share_data.get_price_earnings_growth_ratio()
market_cap = share_data.get_market_cap()
book_value = share_data.get_price_book()
average_volume = share_data.get_avg_daily_volume()
dividend_share = share_data.get_dividend_share()
dividend_yield = share_data.get_dividend_yield()
earnings_per_share = share_data.get_earnings_share()
ebitda = share_data.get_ebitda()
fifty_day_ma = share_data.get_50day_moving_avg()
days_high = share_data.get_days_high()
days_low = share_data.get_days_low()
year_high = share_data.get_year_high()
year_low = share_data.get_year_low()
two_hundred_day_ma = share_data.get_200day_moving_avg()
# Build a string to send to the server containing the stock data
share_string = "price:" + str(price) + "|"\
+ "percentChange:" + str(percent_change) + "|"\
+ "previousClose:" + str(previous_close) + "|"\
+ "openPrice:" + str(open_price) + "|"\
+ "volume:" + str(volume) + "|"\
+ "peRatio:" + str(pe_ratio) + "|"\
+ "pegRatio:" + str(peg_ratio) + "|"\
+ "marketCap:" + str(market_cap) + "|"\
+ "bookValue:" + str(book_value) + "|"\
+ "averageVolume:" + str(average_volume) + "|"\
+ "dividendShare:" + str(dividend_share) + "|"\
+ "dividendYield:" + str(dividend_yield) + "|"\
+ "earningsPerShare:" + str(earnings_per_share) + "|"\
+ "ebitda:" + str(ebitda) + "|"\
+ "50DayMa:" + str(fifty_day_ma) + "|"\
+ "daysHigh:" + str(days_high) + "|"\
+ "daysLow:" + str(days_low) + "|"\
+ "yearHigh:" + str(year_high) + "|"\
+ "yearLow:" + str(year_low) + "|"\
+ "200DayMa:" + str(two_hundred_day_ma) + "|"
self.write_message("StockData;%s" % (share_string))
print_logger.debug("Sending Message: StockData;%s" % (share_string))
elif "GetCompanyDesc" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Read in the company description
description = ""
try:
f = open("../task_1/google_search_program/cleaned_data/%s/company_description" % str(ticker), "r")
description = f.read()
except Exception:
# If the file does not exist, get the data manually
description = update_description_oneoff(ticker)
self.write_message("CompanyDescription:%s" % str(description))
elif "GetCompanyDividend" in message and "Record" not in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Grab the dividend data from dividata.com
dividend_url = "https://dividata.com/stock/%s/dividend" % ticker
# This should potentially be a
dividend_data = requests.get(dividend_url)
dividend_soup = BeautifulSoup(dividend_data.text, 'html5lib')
if len(dividend_soup.find_all("table")) > 0:
dividend_soup = dividend_soup.find_all("table")[0]
else:
dividend_soup = "<h3>No dividend history found.</h3>"
# Send this div up to the server
self.write_message("DividendHistoryData:" + str(dividend_soup))
elif "GetCompanyDividendRecord" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get the dividend record html for the table and send it up
dividend_record = strip_dividends(ticker, req_proxy)
print_logger.debug("Writing message: " + str(dividend_record))
self.write_message("DividendRecord:" + str(dividend_record))
elif "GetBollinger" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get the bollinger band history along with the 5 day moving average
close, lower_band, five_day_ma = calculate_bands(ticker)
last_5_days_5_day_ma = []
last_5_days_bb = []
last_5_days_close = []
for i in range(0, 5):
last_5_days_5_day_ma.append(five_day_ma[i])
last_5_days_bb.append(lower_band[i])
last_5_days_close.append(close[i])
condition_1 = False
condition_2 = False
# Condition 1: Has the stock price at close been below the lower bollinger band
# at market close within the last 5 days
for i in range(0, 5):
if last_5_days_close[i] < last_5_days_bb[i]:
condition_1 = True
# Condition 2: Has the current stock price been above the 5 day moving average sometime in the last 3 days
for i in range(0, 3):
if last_5_days_close[i] > last_5_days_5_day_ma[i]:
condition_2 = True
if condition_1 is True and condition_2 is True:
self.write_message("BB:GoodCandidate")
else:
self.write_message("BB:BadCandidate")
elif "GetSentiment" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Lists of sentiment based words
good_words = ["buy", "bull", "bullish", "positive", "gain", "gains", "up"]
bad_words = ["sell", "bear", "bearish", "negative", "loss", "losses", "down"]
DATA_DIRECTORY = "../task_1/google_search_program/cleaned_data/%s" % ticker.upper()
positive_file_stats = []
negative_file_stats = []
positive_files = 0
negative_files = 0
neutral_files = 0
trump_count = 0
files_examined = 0
for root, dirs, files in os.walk(DATA_DIRECTORY):
path = root.split(os.sep)
print((len(path) - 1) * '---', os.path.basename(root))
for file in files:
if "article" in file:
f = open('/'.join(path) + '/' + file)
title = f.readline()
article_text = " ".join(f.readlines())
if article_text.count("trump") > 0:
trump_count = trump_count + 1
positive_word_count = 0
negative_word_count = 0
files_examined = files_examined + 1
for word in good_words:
if word in article_text:
positive_word_count = positive_word_count + article_text.count(word)
print "Word: %s, %s" % (word, article_text.count(word))
for word in bad_words:
if word in article_text:
negative_word_count = negative_word_count + article_text.count(word)
if positive_word_count > negative_word_count:
positive_ratio = float(positive_word_count) / float(negative_word_count + positive_word_count)
if positive_ratio > 0.7:
positive_files = positive_files + 1
positive_file_stats.append((positive_word_count, negative_word_count))
else:
neutral_files = neutral_files + 1
elif positive_word_count == negative_word_count:
neutral_files = neutral_files + 1
else:
negative_ratio = float(negative_word_count) / float(negative_word_count + positive_word_count)
if negative_ratio > 0.7:
negative_files = negative_files + 1
negative_file_stats.append((positive_word_count, negative_word_count))
else:
neutral_files = neutral_files + 1
print_logger.debug("Sentiment:" + str(positive_files) + ":" + str(negative_files) +\
":" + str(neutral_files) + ":" + str(trump_count) + ":" + str(files_examined))
self.write_message("Sentiment:" + str(positive_files) + ":" + str(negative_files) +\
":" + str(neutral_files) + ":" + str(trump_count) + ":" + str(files_examined))
def display():
today = dt.date.today()
# Is the user coming from the form page?
try:
sym = str(request.form['user_input']).strip().upper() or 'SPY'
session['active'] = True
session['sym'] = sym
except:
# If a user goes to the display page and a session is not active
if session.get('active') != True:
sym = 'SPY'
session['active'] = True
session['sym'] = sym
else:
sym = session['sym'] # if a session is active leave the sym alone
share = Share(sym)
if 'start' not in share.get_info(): # is there information related to the stock symbol in Yahoo Finance?
# if request.method == 'POST':
# print "This is a test"
# # if request.form['submit'] == 'Submit':
# # print "before change session"
# # session['active'] = False
print "before return"
return redirect("/error")
# return render_template('error.html',
# sym=session['sym'])
else:
try: # Error handling... Some Stock symbols exist but there is no historical and/or daily information in Yahoo Finance...
quote = float(share.get_price())
com_name = sym #hand_made_list()[sym][0]
historical = share.get_historical(str(today - dt.timedelta(31)), str(today - dt.timedelta(1)))
canvas_list = []
for day in historical:
canvas_list.append([int(day['Date'][:4]),
int(day['Date'][5:7]) - 1,
int(day['Date'][-2:]),
float(day['Open']),
float(day['High']),
float(day['Low']),
float(day['Close'])
])
info = share.get_info()
open = share.get_open()
high = share.get_days_high()
low = share.get_days_low()
price = share.get_price()
canvas_list.append([int(info['end'][:4]),
int(info['end'][5:7]) - 1,
int(info['end'][-2:]),
float(open),
float(high),
float(low),
float(price)
])
return render_template('display.html',
sym=session['sym'],
com_name=com_name,
quote=quote,
canvas_list=canvas_list)
except:
return redirect("/error")
from yahoo_finance import Share
#yahoo = Share('YHOO')
#yahoo = Share('SPXC')
yahoo = Share('TFM')
#yahoo = Share('INDU')
#INDEXSP
#yahoo = Share('NDX')
print yahoo
print yahoo.get_open()
#'36.60'
print yahoo.get_price()
print yahoo.get_price_earnings_ratio()
print 'get_dividend_share: ',yahoo.get_dividend_share()
print 'get_dividend_yield: ',yahoo.get_dividend_yield()
print 'get_earnings_share: ',yahoo.get_earnings_share()
print 'get_price_earnings_ratio: ',yahoo.get_price_earnings_ratio()
print 'get_price_earnings_growth_ratio: ',yahoo.get_price_earnings_growth_ratio()
print 'get_year_high: ',yahoo.get_year_high()
print 'get_year_low: ',yahoo.get_year_low()
print 'get_days_high: ',yahoo.get_days_high()
print 'get_days_low: ',yahoo.get_days_low()
print 'get_ebitda: ',yahoo.get_ebitda()
print 'get_book_value: ',yahoo.get_book_value()
#'36.84'
#print yahoo.get_trade_datetime()
#'2014-02-05 20:50:00 UTC+0000'
#get_avg_daily_volume()
if len(ticker) == 0:
continue
stock = Share(ticker)
stock.refresh()
change = (float(stock.get_price()) - float(stock.get_prev_close()))/float(stock.get_prev_close())
change = round(change *100.0, 2)
if change > 0.0:
change= '+' + str(change)
else:
change =str(change)
line = ticker.ljust(7)
line += stock.get_price().ljust(9)+ change.ljust(8)+ stock.get_volume().ljust(11) + \
str(round(float(stock.get_volume())/float(stock.get_avg_daily_volume())*100.0)).ljust(8) +\
stock.get_open().ljust(10)+ \
stock.get_days_low().ljust(10)+ \
stock.get_days_high().ljust(10)+ \
stock.get_year_low().ljust(10)+ \
stock.get_year_high().ljust(10)
line = line + str(stock.get_market_cap()).ljust(11) + \
str(stock.get_price_earnings_ratio()).ljust(8)+\
stock.get_50day_moving_avg().ljust(10) +\
stock.get_200day_moving_avg().ljust(10)
print(line)
except Exception as e:
print("Exception error:", str(e))
traceback.print_exc()
i+=1
#you get get a spy.txt and then filter everything by yourself
# The "extract" phase loops through stocks from a list stored in stocks.py
# daily and stores it in a Pandas dataframe
print("Extracting stock data from Yahoo Finance for the following stocks:")
print(stocks_list)
print("Extracting...")
df = pd.DataFrame(
columns=["stock", "open", "high", "low", "close", "volume", "date"])
i = 1
for item in stocks_list:
stock = Share(item)
df.loc[i] = [
item,
stock.get_open(),
stock.get_days_high(),
stock.get_days_low(),
stock.get_prev_close(),
stock.get_volume(),
dt.date.today()
]
i += 1
print("Returning generated DataFrame:")
print(df)
# The "load" phase takes the formatted dataframe and loads it into a Postgresql
# database where they will be available for analysis
