def update(stock1):
stock1.lastprice = ystockquote.get_price(stock1)
stock1.volume = ystockquote.get_volume(stock1)
price_change = ystockquote.get_change(stock1)
market_cap = ystockquote.get_market_cap(stock1)
get_high = ystockquote.get_52_week_high(stock1)
get_low = ystockquote.get_52_week_low(stock1)
pb_ratio = ystockquote.get_price_book_ratio(stock1)
ebitda = ystockquote.get_ebitda(stock1)
dividend = ystockquote.get_dividend_yield(stock1)
stock1.save()
def update(stock1):
stock1.lastprice = ystockquote.get_price(stock1)
stock1.volume = ystockquote.get_volume(stock1)
price_change = ystockquote.get_change(stock1)
market_cap = ystockquote.get_market_cap(stock1)
get_high = ystockquote.get_52_week_high(stock1)
get_low = ystockquote.get_52_week_low(stock1)
pb_ratio = ystockquote.get_price_book_ratio(stock1)
ebitda = ystockquote.get_ebitda(stock1)
dividend = ystockquote.get_dividend_yield(stock1)
stock1.save()
def diff52WeekHigh(self, df):
allHighs = list()
for symbol in df.index.values.tolist():
try:
baseVal = df.loc[symbol, "PriceCurrent"]
high52 = float(ystockquote.get_52_week_high(symbol))
high52 = round(((high52 - baseVal) * 100) / baseVal, 1)
except:
high52 = 0
allHighs.append(high52)
df[self.diff52Col] = pd.Series(allHighs, index=df.index)
return df
def update(stock1):
stock1.lastprice = ystockquote.get_price(stock1)
stock1.volume = ystockquote.get_volume(stock1)
stock1.price_change = float(ystockquote.get_change(stock1))
stock1.market_cap = ystockquote.get_market_cap(stock1)
stock1.get_high = ystockquote.get_52_week_high(stock1)
stock1.get_low = ystockquote.get_52_week_low(stock1)
stock1.pb_ratio = ystockquote.get_price_book_ratio(stock1)
stock1.pe_ratio = ystockquote.get_price_earnings_ratio(stock1)
stock1.dividend = ystockquote.get_dividend_yield(stock1)
stock1.peg = get_peg(stock1)
stock1.revenue = get_revenue(stock1)
stock1.a_gain = get_annualized_gain(stock1)
stock1.save()
def _main():
for s in ["NA.TO", "XBB.TO", "NOU.V", "AP-UN.TO", "BRK-A", "AAPL"]:
print("=============================================")
print("s: {}".format(s))
print("get_name: {}".format(ysq.get_name(s)))
print("get_price: {}".format(ysq.get_price(s)))
print("get_volume: {}".format(ysq.get_volume(s)))
print("get_stock_exchange: {}".format(ysq.get_stock_exchange(s)))
print("get_market_cap: {}".format(ysq.get_market_cap(s)))
print("get_dividend_yield: {}".format(ysq.get_dividend_yield(s)))
print("get_price_earnings_ratio: {}".format(
ysq.get_price_earnings_ratio(s)))
print("get_52_week_low: {}".format(ysq.get_52_week_low(s)))
print("get_52_week_high: {}".format(ysq.get_52_week_high(s)))
print("get_currency: {}".format(ysq.get_currency(s)))
def do_thread_loop(self):
if ( self.running ):
if ( self.mqtt_connected ):
for stock in self.tickerlist:
ticker = stock.ticker
print "querrying for ", ticker
now = datetime.datetime.now()
open_time = now.replace( hour=self.openhour, minute=self.openmin, second=0 )
close_time = now.replace( hour=self.closehour, minute=self.closemin, second=0 )
open_day = False
for day in self.tradingdow:
if ( day == datetime.datetime.today().weekday() ):
open_day = True
if (( now > open_time) and ( now < close_time ) and open_day):
self.mqttc.publish( self.basetopic + "/" + ticker + "/name", stock.name, qos = 2, retain=True)
try:
price = ystockquote.get_price( ticker )
self.mqttc.publish( self.basetopic + "/" + ticker + "/price", price, qos = 2, retain=True)
#TODO add previous close value!!!!!!1
change = ystockquote.get_change( ticker )
self.mqttc.publish( self.basetopic + "/" + ticker + "/change", change, qos = 2, retain=True)
volume = ystockquote.get_volume( ticker )
self.mqttc.publish( self.basetopic + "/" + ticker + "/volume", volume, qos = 2, retain=True)
if ( stock.high_low ):
yrhigh = ystockquote.get_52_week_high( ticker )
self.mqttc.publish( self.basetopic + "/" + ticker + "/yrhigh", yrhigh, qos = 2, retain=True)
yrlow = ystockquote.get_52_week_low( ticker )
self.mqttc.publish( self.basetopic + "/" + ticker + "/yrlow", yrlow, qos = 2, retain=True)
if ( stock.mavg ):
avg50 = ystockquote.get_50day_moving_avg( ticker )
self.mqttc.publish( self.basetopic + "/" + ticker + "/50day-ma", avg50, qos = 2, retain=True)
avg200 = ystockquote.get_200day_moving_avg( ticker )
self.mqttc.publish( self.basetopic + "/" + ticker + "/200day-ma", avg200, qos = 2, retain=True)
self.mqttc.publish( self.basetopic + "/" + ticker + "/time", time.strftime( "%x %X" ), qos = 2, retain=True)
except:
print "querry error in ystockquote."
else:
print "Markets closed"
self.mqttc.publish( self.basetopic + "/" + ticker + "/null", "", qos = 2, retain=True)
def test_get_52_week_high(self):
value = ystockquote.get_52_week_high(self.symbol)
self.assertIsInstance(value, str)
def test_get_52_week_high(self):
value = ystockquote.get_52_week_high(self.symbol)
self.assertIsInstance(value, str)
print(ystockquote.get_price_eps_estimate_current_year('GOOG'))
##Some of the methods available
name = ystockquote.get_company_name('GOOG')
mktcap = ystockquote.get_market_cap('GOOG')
print ("Name: %s , Market Cap %s" %(name,mktcap))
ystockquote.get_200_sma()
ystockquote.get_50_sma()
ystockquote.get_annualized_gain()
ystockquote.get_1_year_target()
ystockquote.get_52_week_high()
ystockquote.get_52_week_low()
ystockquote.get_change_200_sma()
ystockquote.get_52_week_range()
ystockquote.get_book_value()
ystockquote.get_eps_estimate_current_year()
ystockquote.get_eps()
ystockquote.get_ticker_trend()
ystockquote.get_short_ratio()
ystockquote.get_revenue()
ystockquote.get_average_daily_volume()
ystockquote.get_float_shares()
ystockquote.get_dividend_yield()
ystockquote.get_notes()
ystockquote.get_pe()
ystockquote.get_all()
class Stocks(peewee.Model):
week_high_52 = peewee.FloatField()
week_low_52 = peewee.FloatField()
price = peewee.FloatField()
volume = peewee.IntegerField()
company = peewee.CharField()
class Meta:
database = db
Stocks.create_table()
google_arg1 = ystockquote.get_52_week_high('GOOG')
google_arg2 = ystockquote.get_52_week_low('GOOG')
google_arg3 = ystockquote.get_price('GOOG')
google_arg4 = ystockquote.get_volume('GOOG')
google_stocks = Stocks(week_high_52=google_arg1,
week_low_52=google_arg2,
price=google_arg3,
volume=google_arg4,
company='Google')
google_stocks.save()
adobe_arg1 = ystockquote.get_52_week_high('ADBE')
adobe_arg2 = ystockquote.get_52_week_low('ADBE')
adobe_arg3 = ystockquote.get_price('ADBE')
adobe_arg4 = ystockquote.get_volume('ADBE')
def individual_stock(request, stock_id):
stock1 = get_object_or_404(Stock, pk=stock_id)
# Stock Information per Stock
stock1.lastprice = ystockquote.get_price(stock1)
stock1.volume = ystockquote.get_volume(stock1)
price_change = ystockquote.get_change(stock1)
market_cap = ystockquote.get_market_cap(stock1)
get_high = ystockquote.get_52_week_high(stock1)
get_low = ystockquote.get_52_week_low(stock1)
pb_ratio = ystockquote.get_price_book_ratio(stock1)
ebitda = ystockquote.get_ebitda(stock1)
dividend = ystockquote.get_dividend_yield(stock1)
# Graph
# Last known weekday
current_day = weekday().isoformat()
# Retrieve live data YYYY-MM-DD
historical_price = ystockquote.get_historical_prices(stock1, '2010-01-24', current_day)
correct_order = sorted(historical_price)
stock_prices = []
dates = []
for values in correct_order:
stock_prices.append(historical_price[values]['Adj Close'])
dates.append(values)
# Convert to Float
for p in range(len(stock_prices)):
stock_prices[p] = float(stock_prices[p])
# Convert to Datetime Format
dates_objects = []
for d in dates:
dates_objects.append(datetime.strptime(d,'%Y-%m-%d'))
source = ColumnDataSource(data=dict(x=dates_objects,y=stock_prices, time=dates))
# Tools
hover = HoverTool(tooltips=[('Stock Price','@y'),('time','@time'),], mode='vline')
crosshair = CrosshairTool(dimensions=['height'])
TOOLS = [hover, crosshair]
plot = figure(x_axis_type="datetime", responsive = True ,plot_height=250, tools = TOOLS, toolbar_location=None)
plot.line('x','y',source=source)
first_date = dates[0]
last_date = dates[-1]
callback = CustomJS(args=dict(x_range=plot.x_range), code="""
var start = cb_obj.get("value");
x_range.set("start", start);
x_range.set("end", start+2);
""")
slider = vform(Slider(start=0, end=100, title="Start Date", callback=callback))
widget_script, widget_div = components(slider)
script, div = components(plot)
stock1.save()
context = {'stock':stock1,
'hprice': stock_prices,
'widget_script': widget_script,
'widget_div': widget_div,
'the_script': script,
'the_div':div,
'thedate': dates_objects,
'dates':dates
}
return render(request, 'stocktracker/individual.html', context)
def individual_stock(request, stock_id):
stock1 = get_object_or_404(Stock, pk=stock_id)
# Stock Information per Stock
stock1.lastprice = ystockquote.get_price(stock1)
stock1.volume = ystockquote.get_volume(stock1)
price_change = ystockquote.get_change(stock1)
market_cap = ystockquote.get_market_cap(stock1)
get_high = ystockquote.get_52_week_high(stock1)
get_low = ystockquote.get_52_week_low(stock1)
pb_ratio = ystockquote.get_price_book_ratio(stock1)
ebitda = ystockquote.get_ebitda(stock1)
dividend = ystockquote.get_dividend_yield(stock1)
# Graph
# Last known weekday
current_day = weekday().isoformat()
# Retrieve live data YYYY-MM-DD
historical_price = ystockquote.get_historical_prices(
stock1, '2010-01-24', current_day)
correct_order = sorted(historical_price)
stock_prices = []
dates = []
for values in correct_order:
stock_prices.append(historical_price[values]['Adj Close'])
dates.append(values)
# Convert to Float
for p in range(len(stock_prices)):
stock_prices[p] = float(stock_prices[p])
# Convert to Datetime Format
dates_objects = []
for d in dates:
dates_objects.append(datetime.strptime(d, '%Y-%m-%d'))
source = ColumnDataSource(
data=dict(x=dates_objects, y=stock_prices, time=dates))
# Tools
hover = HoverTool(tooltips=[
('Stock Price', '@y'),
('time', '@time'),
],
mode='vline')
crosshair = CrosshairTool(dimensions=['height'])
TOOLS = [hover, crosshair]
plot = figure(x_axis_type="datetime",
responsive=True,
plot_height=250,
tools=TOOLS,
toolbar_location=None)
plot.line('x', 'y', source=source)
first_date = dates[0]
last_date = dates[-1]
callback = CustomJS(args=dict(x_range=plot.x_range),
code="""
var start = cb_obj.get("value");
x_range.set("start", start);
x_range.set("end", start+2);
""")
slider = vform(
Slider(start=0, end=100, title="Start Date", callback=callback))
widget_script, widget_div = components(slider)
script, div = components(plot)
stock1.save()
context = {
'stock': stock1,
'hprice': stock_prices,
'widget_script': widget_script,
'widget_div': widget_div,
'the_script': script,
'the_div': div,
'thedate': dates_objects,
'dates': dates
}
return render(request, 'stocktracker/individual.html', context)
summaryPage = requests.get('http://finance.yahoo.com/q/pr?s=' + symbol, stream=False)
d = summaryPage.content
soup1 = BeautifulSoup(d)
getSummary = soup1.find_all('p')
price = str(ystockquote.get_price(symbol))
change = str(ystockquote.get_change(symbol))
volume = str(ystockquote.get_volume(symbol))
stockExchange = str(ystockquote.get_stock_exchange(symbol))
marketCap = str(ystockquote.get_market_cap(symbol))
bValue = str(ystockquote.get_book_value(symbol))
ebitda = str(ystockquote.get_ebitda(symbol))
mvavg = str(ystockquote.get_200day_moving_avg(symbol))
High = str(ystockquote.get_52_week_high(symbol))
Low = str(ystockquote.get_52_week_low(symbol))
commaData = []
data=[price, change, volume, stockExchange, mvavg, bValue, ebitda, marketCap, High, Low]
for individData in data:
commaInt = humanize.intcomma(individData)
commaData.append(commaInt)
if float(price) > 0.00:
try:
stockInfo = ('\n'
def view_stock(request, ticker):
if request.user.__class__.__name__ is 'CustomUser':
c_user = get_object_or_404(CustomUser, pk=request.user.pk)
account = Account.objects.get(user=c_user)
else:
account = False
stock = get_object_or_404(Stock, ticker=ticker)
companyName = stock.ticker
companyName = companyName.upper()
stock = Stock.objects.get(ticker=companyName)
namer = "'" + companyName + "'"
ystock = Share(companyName)
the_price = ystock.get_price()
regex = 'Business Summary</span></th><th align="right"> </th></tr></table><p>(.+?)</p>'
pattern = re.compile(regex)
root_url = urllib.urlopen("http://finance.yahoo.com/q/pr?s=" +
companyName + "+Profile")
htmltext = root_url.read()
decoded_str = str(re.findall(pattern, htmltext)).decode("utf8")
encoded_str = decoded_str.encode('ascii', 'ignore')
stock.description = encoded_str
stock.description = stock.description[:-2]
stock.description = stock.description[2:]
stock.book_value = ystockquote.get_book_value(companyName)
stock.change = ystockquote.get_change(companyName)
#stock.dividend_per_share = ystockquote.get_dividend_per_share(companyName)
#stock.dividend_yield = ystockquote.get_dividend_yield(companyName)
stock.ebitda = ystockquote.get_ebitda(companyName)
stock.fifty_two_week_high = ystockquote.get_52_week_high(companyName)
stock.fifty_two_week_low = ystockquote.get_52_week_low(companyName)
stock.market_cap = ystockquote.get_market_cap(companyName)
stock.short_ratio = ystockquote.get_short_ratio(companyName)
stock.stock_exchange = ystockquote.get_stock_exchange(companyName)
stock.volume = ystockquote.get_volume(companyName)
stock.price = ystock.get_price()
#yahoo_finance
stock.average_daily_volume = ystock.get_avg_daily_volume()
stock.earnings_per_share = ystock.get_price_earnings_ratio()
stock.fifty_day_moving_avg = ystock.get_50day_moving_avg()
stock.two_hundred_day_moving_avg = ystock.get_200day_moving_avg()
stock.price_book_ratio = ystock.get_price_book()
stock.last_sale = ystock.get_price()
stock.price_earnings_growth_ratio = ystock.get_price_earnings_growth_ratio(
)
stock.price_earnings_ratio = ystock.get_price_earnings_ratio()
stock.price_sales_ratio = ystock.get_price_sales()
stock.save()
vl = []
acl = []
hl = []
ll = []
cl = []
ol = []
days_list = []
d = 0
seven_days_ago = datetime.datetime.now() + datetime.timedelta(-30)
today = datetime.datetime.now()
days = ystockquote.get_historical_prices(
'GOOGL', seven_days_ago.strftime("%Y-%m-%d"),
today.strftime("%Y-%m-%d"))
for day in days.keys():
d += 1
date_label = datetime.datetime.now() + datetime.timedelta(-d)
days_list.append(date_label.strftime("%b-%d"))
day_info = days.get(day)
vol = int(day_info.get('Volume'))
vl.append(vol)
adjcl = float(day_info.get('Adj Close'))
acl.append(adjcl)
highs = float(day_info.get('High'))
hl.append(highs)
lows = float(day_info.get('Low'))
ll.append(lows)
closes = float(day_info.get('Close'))
cl.append(closes)
opens = float(day_info.get('Open'))
ol.append(opens)
volume = vl
lows = ll
opens = ol
highs = hl
averages = acl
closes = cl
days_l = days_list[::-1]
context = RequestContext(
request,
dict(account=account,
request=request,
stock=stock,
volume=volume,
lows=lows,
highs=highs,
opens=opens,
closes=closes,
averages=averages,
days_l=days_l))
return render_to_response('scrapyr_app/stock.html', context=context)
summaryPage = requests.get('http://finance.yahoo.com/q/pr?s=' + symbol, stream=False)
d = summaryPage.content
soup1 = BeautifulSoup(d)
getSummary = soup1.find_all('p')
price = str(ystockquote.get_price(symbol))
change = str(ystockquote.get_change(symbol))
volume = str(ystockquote.get_volume(symbol))
stockExchange = str(ystockquote.get_stock_exchange(symbol))
marketCap = str(ystockquote.get_market_cap(symbol))
bValue = str(ystockquote.get_book_value(symbol))
ebitda = str(ystockquote.get_ebitda(symbol))
mvavg = str(ystockquote.get_200day_moving_avg(symbol))
High = str(ystockquote.get_52_week_high(symbol))
Low = str(ystockquote.get_52_week_low(symbol))
commaData = []
data=[price, change, volume, stockExchange, mvavg, bValue, ebitda, marketCap, High, Low]
for individData in data:
commaInt = humanize.intcomma(individData)
commaData.append(commaInt)
if float(price) > 0.00:
try:
stockInfo = ('\n'
def view_stock(request, ticker):
if request.user.__class__.__name__ is "CustomUser":
c_user = get_object_or_404(CustomUser, pk=request.user.pk)
account = Account.objects.get(user=c_user)
else:
account = False
stock = get_object_or_404(Stock, ticker=ticker)
companyName = stock.ticker
companyName = companyName.upper()
stock = Stock.objects.get(ticker=companyName)
namer = "'" + companyName + "'"
ystock = Share(companyName)
the_price = ystock.get_price()
regex = 'Business Summary</span></th><th align="right"> </th></tr></table><p>(.+?)</p>'
pattern = re.compile(regex)
root_url = urllib.urlopen("http://finance.yahoo.com/q/pr?s=" + companyName + "+Profile")
htmltext = root_url.read()
decoded_str = str(re.findall(pattern, htmltext)).decode("utf8")
encoded_str = decoded_str.encode("ascii", "ignore")
stock.description = encoded_str
stock.description = stock.description[:-2]
stock.description = stock.description[2:]
stock.book_value = ystockquote.get_book_value(companyName)
stock.change = ystockquote.get_change(companyName)
# stock.dividend_per_share = ystockquote.get_dividend_per_share(companyName)
# stock.dividend_yield = ystockquote.get_dividend_yield(companyName)
stock.ebitda = ystockquote.get_ebitda(companyName)
stock.fifty_two_week_high = ystockquote.get_52_week_high(companyName)
stock.fifty_two_week_low = ystockquote.get_52_week_low(companyName)
stock.market_cap = ystockquote.get_market_cap(companyName)
stock.short_ratio = ystockquote.get_short_ratio(companyName)
stock.stock_exchange = ystockquote.get_stock_exchange(companyName)
stock.volume = ystockquote.get_volume(companyName)
stock.price = ystock.get_price()
# yahoo_finance
stock.average_daily_volume = ystock.get_avg_daily_volume()
stock.earnings_per_share = ystock.get_price_earnings_ratio()
stock.fifty_day_moving_avg = ystock.get_50day_moving_avg()
stock.two_hundred_day_moving_avg = ystock.get_200day_moving_avg()
stock.price_book_ratio = ystock.get_price_book()
stock.last_sale = ystock.get_price()
stock.price_earnings_growth_ratio = ystock.get_price_earnings_growth_ratio()
stock.price_earnings_ratio = ystock.get_price_earnings_ratio()
stock.price_sales_ratio = ystock.get_price_sales()
stock.save()
vl = []
acl = []
hl = []
ll = []
cl = []
ol = []
days_list = []
d = 0
seven_days_ago = datetime.datetime.now() + datetime.timedelta(-30)
today = datetime.datetime.now()
days = ystockquote.get_historical_prices("GOOGL", seven_days_ago.strftime("%Y-%m-%d"), today.strftime("%Y-%m-%d"))
for day in days.keys():
d += 1
date_label = datetime.datetime.now() + datetime.timedelta(-d)
days_list.append(date_label.strftime("%b-%d"))
day_info = days.get(day)
vol = int(day_info.get("Volume"))
vl.append(vol)
adjcl = float(day_info.get("Adj Close"))
acl.append(adjcl)
highs = float(day_info.get("High"))
hl.append(highs)
lows = float(day_info.get("Low"))
ll.append(lows)
closes = float(day_info.get("Close"))
cl.append(closes)
opens = float(day_info.get("Open"))
ol.append(opens)
volume = vl
lows = ll
opens = ol
highs = hl
averages = acl
closes = cl
days_l = days_list[::-1]
context = RequestContext(
request,
dict(
account=account,
request=request,
stock=stock,
volume=volume,
lows=lows,
highs=highs,
opens=opens,
closes=closes,
averages=averages,
days_l=days_l,
),
)
return render_to_response("scrapyr_app/stock.html", context=context)