def getQuotes(self, companyLabel):
# TODO: if NO CHANGE:
# return nothing
print 'Fetching Quotes', companyLabel
results = ystockquote.get_historical_prices(companyLabel, '20100101', '20130301')
div = ystockquote.get_dividend_yield(companyLabel)
print 'Fetched Quotes'
if str(div) == 'N/A':
div = 0
else:
div = float(div) * .01
del results[0] # column names
quotes = []
for i,entry in enumerate(results):
# second column is opening price
if i+1 >= len(results) or self.isFirstWorkDay(entry[0], results[i+1][0]):
gain = float(entry[1+2]) * (1+div)
quotes.append(gain)
return quotes
def get_current_dividened_yield(self):
cur_div = Decimal(0)
cur_div = ystockquote.get_dividend_yield(self.symbol)
try:
cur_div = Decimal(cur_div)
except:
pass
return cur_div
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 test_get_all(self):
symbol = 'GOOG'
all_info = ystockquote.get_all(symbol)
self.assertIsInstance(all_info, dict)
self.assertEqual(all_info['dividend_yield'],
ystockquote.get_dividend_yield(symbol))
self.assertEqual(all_info['fifty_sma'],
ystockquote.get_50_sma(symbol))
self.assertEqual(all_info['company_name'],
ystockquote.get_company_name(symbol))
self.assertEqual(all_info['book_value'],
ystockquote.get_book_value(symbol))
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 check_db(path):
# Create data base:
db = sdm.StockDBMgr('./stock_db/' + path, startdate, enddate)
# db.update_all_symbols()
inv = []
symbolList = db.get_all_symbols()
print(len(symbolList))
print(symbolList)
for s in symbolList:
if False:
print("symbol:{}, yield:{}, name:{}".format(
s, sq.get_dividend_yield(s), sq.get_name(s)))
if not db.validate_symbol_data(s):
inv.append(s)
continue
# Only applies if recent download...
if True:
df = db.get_symbol_data(s)
t = startdate
if df is not None and len(df) > 0:
# t = r[-1].date
t = df.iloc[-1].name.date()
else:
inv.append(s)
continue
if (today - t) > datetime.timedelta(4):
inv.append(s)
print("%s: len = %d" % (s, len(df)))
print("Invalid list:")
for s in inv:
print(s)
def test_get_dividend_yield(self):
value = ystockquote.get_dividend_yield(self.symbol)
self.assertIsInstance(value, str)
def test_get_dividend_yield(self):
value = ystockquote.get_dividend_yield(self.symbol)
self.assertIsInstance(value, str)
##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()
print (ystockquote.get_all('GOOG'))
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)
def yahoo_play():
# db = sdm.StockDBMgr('./stock_db/tsx', startdate, enddate)
# for s in db.get_all_symbols():
for s in ['SPY', 'NA.TO', 'XBB.TO', 'AP-UN.TO', 'AAPL', 'XOM']:
print(s, ysq.get_dividend_yield(s))
def test_ysq_api_dividend(s):
assert 0 <= ysq.get_dividend_yield(s) < 100
def data_type():
print "From the list above, enter the data type you'd like to see"
data = raw_input("> ")
print "What stock would you like to see data on?"
stock = raw_input("> ")
if data == 'price' or data == 'Price':
print ystockquote.get_price(stock)
elif data == 'change' or data == 'Change':
print ystockquote.get_change(stock)
elif data == 'Volume' or data == 'volume':
print ystockquote.get_avg_daily_vol(stock)
elif data == 'exchange' or data == 'Exchange':
print ystockquote.get_stock_exchange(stock)
elif data == 'market cap' or data == 'Market cap' or data == 'Market Cap':
print ystockquote.get_market_cap(stock)
elif data == 'book value' or data == 'Book value' or data == 'Book Value':
print ystockquote.get_book_value(stock)
elif data == 'eps' or data == 'EPS':
print ystockquote.get_earnings_per_share(stock)
elif data == 'short ratio' or data == 'Short Ratio':
print ystockquote.get_short_ratio(stock)
elif data == 'dividend yield' or data == 'Dividend Yield' or data == 'div yield':
print ystockquote.get_dividend_yield(stock)
elif data == 'ebitda' or data == 'EBITDA':
print ystockquote.get_ebitda(stock)
else:
print 'Sorry, we don\'t have that data type'
quit()