def printStocks(sL) : # Prints the stocks for x in sL: # A for each loop lcd.clear() # Clears the LCD print x + " " + ystockquote.get_price(x) # Gets the price of x and prints it to console lcd.message(x + " " + ystockquote.get_price(x)) # Gets the price and shows it on the lcd print ystockquote.get_change(x) # Gets the price change and prints it to the console lcd.message(ystockquote.get_change(x)) # Gets the price change and shows it on the lcd sleep(10) # Sleeps so it user can read the info
def oil():
# crude oil
crude = ystockquote.get_price('CLJ14.NYM')
print crude
# heating oil
heat = ystockquote.get_price('HOH14.NYM')
print heat
if float(crude) < 98:
body = "Low price alert! Crude: " + crude + " Heat: " + heat
messager(body)
print body
return
def printStocks(sL): # Prints the stocks
for x in sL: # A for each loop
lcd.clear() # Clears the LCD
print x + " " + ystockquote.get_price(
x) # Gets the price of x and prints it to console
lcd.message(
x + " " +
ystockquote.get_price(x)) # Gets the price and shows it on the lcd
print ystockquote.get_change(
x) # Gets the price change and prints it to the console
lcd.message(ystockquote.get_change(
x)) # Gets the price change and shows it on the lcd
sleep(10) # Sleeps so it user can read the info
def buy_stock_conditionals(data, portfolio, monthly, request):
price = ystockquote.get_price(str(data))
number_shares = math.trunc(float(monthly) / float(price))
if portfolio:
for items in portfolio:
empty_stock_add_shares(data, items, number_shares)
else:
price = ystockquote.get_price(str(data))
cost = float(price) * float(number_shares)
real_cost = decimal.Decimal(cost)
PersonalStockPortfolio.objects.create(name="primary", owner=request.user, stock_one_name=str(data),
stock_one_shares=number_shares, cost=real_cost)
data = {data: number_shares}
return data
def run(self):
"""
Main loop
"""
properties = {"app_id": self.app_id}
while True:
# Loop over the tickers and lookup the stock price and volume
for ticker in self.tickers:
measurements = []
price = ystockquote.get_price(ticker)
volume = ystockquote.get_volume(ticker)
timestamp = int(time.time())
if volume == 'N/A' or price == 'N/A':
sys.stderr.write(
'Could not find ticker \"{0}\", skipping'.format(
ticker))
else:
print("ticker: {0}, price: {1}, volume: {2}".format(
ticker, price, volume))
measurements.append(
Measurement(metric='STOCK_PRICE',
value=price,
source=ticker,
properties=properties))
measurements.append(
Measurement(metric='STOCK_VOLUME',
value=volume,
source=ticker,
properties=properties))
self.send_measurements(measurements)
time.sleep(self.interval)
def run(self):
"""
Main loop
"""
properties = {"app_id": self.app_id}
while True:
# Loop over the tickers and lookup the stock price and volume
for ticker in self.tickers:
measurements = []
price = ystockquote.get_price(ticker)
volume = ystockquote.get_volume(ticker)
timestamp = int(time.time())
if volume == 'N/A' or price == 'N/A':
sys.stderr.write('Could not find ticker \"{0}\", skipping'.format(ticker))
else:
print("ticker: {0}, price: {1}, volume: {2}".format(ticker, price, volume))
measurements.append(Measurement(metric='STOCK_PRICE',
value=price,
source=ticker,
properties=properties))
measurements.append(Measurement(metric='STOCK_VOLUME',
value=volume,
source=ticker,
properties=properties))
self.send_measurements(measurements)
time.sleep(self.interval)
def __init__(self, ticker):
self.ticker = ticker
params = getParams(ticker)
self.mean = params[0][0]
self.var = params[0][1]
self.vol = params[1]
self.price = get_price(self.ticker)
def buy(self, ticker, amount):
buy_price = y.get_price(ticker)
buy_date = datetime.today()
pos = Position(ticker, buy_date, buy_price, amount)
self.open_positions.append(pos)
buy = Decimal(buy_price.strip(' "')) * Decimal(amount)
self.cash = int(self.cash - buy)
def buy(self, ticker, amount):
buy_price = y.get_price(ticker)
buy_date = datetime.today()
pos = Position(ticker, buy_date, buy_price, amount)
self.open_positions.append(pos)
buy = Decimal(buy_price.strip(' "')) * Decimal(amount)
self.cash = int(self.cash - buy)
def testMovingAverage(self, stock):
if self.MA35 > self.MA350 and self.MA35 > float(
quote.get_price(stock)):
return 1
else:
return 0
def post_stock_price(symbol, apikey, devicename):
'''
Retrieve the stock price for the given ticker symbol ("T" for AT&T) and
post it in the correct M2X data stream.
'''
client = M2XClient(key=apikey)
# Find the correct device if it exists, if not create it.
try:
device = [d for d in client.devices(q=devicename) if d.name == devicename][0]
except IndexError:
device = client.create_device(name=devicename,
description="Stockreport Example Device",
visibility="private")
# Get the stream if it exists, if not create the stream.
try:
stream = device.stream(symbol)
except HTTPError:
stream = device.create_stream(symbol)
device.update_stream(symbol, unit={'label': 'Dollars', 'symbol': '$'})
postime = datetime.now()
stock_price = ystockquote.get_price(symbol).encode('utf-8')
stream.add_value(stock_price, postime)
def get_current_price(symbol):
"""
Get the latest price!
:param symbol:
:return:
"""
return float(ystockquote.get_price(symbol))
def buyStockIfPossible(self): for k,v in self.stocks.items(): cost = float(ystockquote.get_price(k)); if(cost < self.capital): count = int(self.capital / cost); self.stocks[k] = v + count; self.capital -= cost * count;
def check(symbol, position=False):
days = 20
quotes = prices(symbol, days)
_raising = raising(symbol)
_price = float(ystockquote.get_price(symbol))
_over_mavg = over_mavg(_price, quotes)
_min = min(quotes)
#print "%s min %s, now %s" % (symbol, _min, _price)
if (position):
color = "red"
else:
color = "orange"
if (_raising and _over_mavg):
print "<div style=color:green>Raising and over mavg: BUY %s</div>" % symbol
return
if (not _over_mavg):
print "<div style=color:%s>Not over mavg: SELL %s</div>" % (color,
symbol)
return
if (_price <= _min):
print "<div style=color:orange>Under 20 day min: SELL %s</div>" % (
color, symbol)
return
print "<div>No matching signal for %s</div>" % symbol
def get_current_price(symbol):
"""
Get the latest price!
:param symbol:
:return:
"""
return float(ystockquote.get_price(symbol))
def post_stock_price(symbol, apikey, devicename):
'''
Retrieve the stock price for the given ticker symbol ("T" for AT&T) and
post it in the correct M2X data stream.
'''
client = M2XClient(key=apikey)
# Find the correct device if it exists, if not create it.
try:
device = [
d for d in client.devices(q=devicename) if d.name == devicename
][0]
except IndexError:
device = client.create_device(name=devicename,
description="Stockreport Example Device",
visibility="private")
# Get the stream if it exists, if not create the stream.
try:
stream = device.stream(symbol)
except HTTPError:
stream = device.create_stream(symbol)
device.update_stream(symbol, unit={'label': 'Dollars', 'symbol': '$'})
postime = datetime.now()
stock_price = ystockquote.get_price(symbol).encode('utf-8')
stream.add_value(stock_price, postime)
def check(symbol, position=False):
days = 20
quotes = prices(symbol, days)
_raising = raising(symbol)
_price = float(ystockquote.get_price(symbol))
_over_mavg = over_mavg(_price, quotes)
_min = min(quotes)
#print "%s min %s, now %s" % (symbol, _min, _price)
if(position):
color = "red"
else:
color = "orange"
if(_raising and
_over_mavg):
print "<div style=color:green>Raising and over mavg: BUY %s</div>" % symbol
return
if(not _over_mavg):
print "<div style=color:%s>Not over mavg: SELL %s</div>" % (color, symbol)
return
if(_price <= _min):
print "<div style=color:orange>Under 20 day min: SELL %s</div>" % (color, symbol)
return
print "<div>No matching signal for %s</div>" % symbol
def get_stock_cost(data, number_shares, items):
price = ystockquote.get_price(str(data))
cost = float(price) * float(number_shares)
real_cost = decimal.Decimal(cost)
items.cost += real_cost
items.save()
return real_cost
def update_price(dict): ''' Updates portfolio with new prices ''' print 'Updating portfolio...' for key in dict: dict[key][4] = ystockquote.get_price(dict[key][1])
def run(stocks):
with open(get_stockfile(), 'a') as data:
for stock in stocks:
current = ystockquote.get_price(stock)
if isinstance(current, float):
data.write(stock + ' ' + current + '\n')
print 'Purchased', stock, 'at', current
def update_price():
# pull today
now = datetime.now()
today = ("%s-%02d-%02d" % (now.year, now.month, now.day))
quotes = ystockquote.get_historical_prices('SPY', '2015-01-15',
today) #pull data
#writing json
with open('www/live-data/price.json', 'w') as file:
json.dump(quotes, file)
#get current price
current_price = ystockquote.get_price('SPY')
current_date = now.strftime('%Y-%m-%d')
current_time = now.strftime('%H:%M:%S')
current_value = str(current_date) + "," + str(current_time) + "," + str(
current_price)
header = "date,time,price"
with open('www/live-data/current.csv', 'wb') as f:
fwriter = csv.writer(f, delimiter=" ")
fwriter.writerow([header])
fwriter.writerow([current_value])
if app_config.DEPLOYMENT_TARGET:
flat.deploy_folder('www/live-data',
'live-data',
max_age=app_config.DEFAULT_MAX_AGE)
def priceMe(tick): price = 0 try: price = float(ystockquote.get_price(tick)) except: return price return price
def export(self, xlsx_file, s_flag):
wb = Workbook()
ws = wb.create_sheet(0)
ws.title = "Guru 13Fs"
print "Writing {0}...".format(xlsx_file)
headers = ["Gurus", "Date", "Symbol", "Action", "Average", "Minimum", "Volume", "Portfolio Impact"]
if s_flag:
headers.append("Current Share Price")
col = 0
for header in headers:
header_cell = ws.cell(row = 0, column = col)
header_cell.value = header
if header == "Gurus":
ws.merge_cells(start_row = 0, start_column = 0, end_row = 0, end_column = 2)
col += 2
col += 1
db = self.client.gurudb
gurus = db.gurus
cursor = gurus.find()
share_prices = dict()
guruRow = 1
for guru in cursor:
tickers = guru['tickers']
for ticker in tickers:
history = ticker['transactionHistory']
transactions = history['transactions']
symbol = ticker['ticker']
if share_prices.get(symbol) == None and s_flag:
share_prices[symbol] = ystockquote.get_price(symbol)
print "Retrieved {0} at ${1} for {2}".format(symbol, share_prices[symbol], guru['name'])
for transaction in transactions:
guru_cell = ws.cell(row = guruRow, column = 0)
guru_cell.value = guru['name']
ws.merge_cells(start_row = guruRow, start_column = 0, end_row = guruRow, end_column = 2)
symbol_cell = ws.cell(row = guruRow, column = self.SYMBOL_CELL)
symbol_cell.value = symbol
impact_cell = ws.cell(row = guruRow, column = self.IMPACT_START_CELL)
impact_cell.value = "{0}%".format(ticker['percent'])
transaction_cell = ws.cell(row = guruRow, column = self.DATE_CELL)
transaction_cell.value = transaction['date']
action_cell = ws.cell(row = guruRow, column = self.ACTION_CELL)
action_cell.value = transaction['entryType']
average_cell = ws.cell(row = guruRow, column = self.AVERAGE_CELL)
# convert from int to decimal. stored in mongo this way for percision reasons
average_cell.value = float(transaction['avg']) * 0.01
minimum_cell = ws.cell(row = guruRow, column = self.MINIMUM_CELL)
minimum_cell.value = float(transaction['min']) * 0.01
volume_cell = ws.cell(row = guruRow, column = self.VOLUME_CELL)
volume_cell.value = transaction['numberOfShares']
if s_flag:
current_share_price_cell = ws.cell(row = guruRow, column = self.CURRENT_SHARE_PRICE_START_CELL)
current_share_price_cell.value = share_prices.get(symbol)
guruRow += 1
wb.save(xlsx_file)
print "Wrote {0}".format(xlsx_file)
return
def mainIndex():
if request.method == 'POST':
ticker = request.form['search']
stockPrice = ystockquote.get_price(ticker)
return render_template('index.html', selectedMenu='Home', price=stockPrice, symbol=ticker, queryType='stock')
if 'username' in session:
return render_template('index.html', selectedMenu='Home', username=session['username'])
return render_template('index.html', selectedMenu='Home')
def update_prices():
"""
update stock prices calling ystockquote
"""
from finance_game.models import Stock
for stock in Stock.objects.all():
stock.price = ystockquote.get_price(stock.symbol)
stock.save()
def __init__(self, ticker):
self.ticker = ticker
self.price = round(float(ystock.get_price(ticker)), 2)
self.ma_5 = None
self.ma_10 = None
self.ma_20 = None
self.ma_50 = None
self._calculate_moving_averages()
def post(self):
self.write("{\"number\": \"five\"}")
if request.headers['Content-Type'] == 'application/json':
data = json.loads(request.data)
ticker = data['ticker']
price = ystockquote.get_price(ticker)
returnStatement = "{\"price\": \""+str(price)+"\"}"
self.write(returnStatement)
def add_stock(stock, target):
price = ystockquote.get_price(stock)
c.execute("INSERT INTO stocks VALUES (?,?,?)", (
stock,
target,
price,
))
conn.commit() # Save (commit) the changes
print "\nStock added to database"
def stockfinder_view(request, ticker=None):
"""
This view displays a HTML-page where the user can search for stocks
on the OSL stock exchange.
"""
ticker = ticker + '.OL'
price = get_price(ticker)
data = {'ticker': ticker,'price': price}
return HttpResponse((data['ticker'], data['price']))
def getPrice(self):
global verbose
if self.name == 'Cash':
return
if verbose:
print("PRICE GET: %s" % (self.name))
ret = ystockquote.get_price(self.name)
self.price = float(ret)
if verbose:
print("PRICE RCV: %s $%.2f" % (self.name, self.price))
def price(ticker):
"""
For a given 'ticker' this function returns a dict containing
{'ticker':'T', price:'P'}
(Can lookup towards yahoo finance or even better - use live data
from SEB )
"""
price = get_price(ticker)
data = {"ticker": ticker, "price": price}
return data
def run():
for line in open(get_stockfile(), 'r').readlines():
purchased = line.split()
current = ystockquote.get_price(purchased[0])
difference = 100 * round(float(current) / float(purchased[1]) - 1, 5)
print purchased[0] + ':',
print 'bought at', purchased[1] + ',',
print 'current price is', current,
print '(' + str(difference) + '%)'
def match_stocks(data, portfolio_stocks):
data_list = {}
for stock, values in data[0]['stockPort'].iteritems():
for quote in portfolio_stocks:
if stock == quote.hidden_symbol:
value = (float(ystockquote.get_price(stock))*values)
data_list[quote.name] = value
else:
pass
return [data_list, data[1]]
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 get_percent_change(symbol):
change = ystockquote.get_change(symbol)
price = ystockquote.get_price(symbol)
percent_change = 100*float(change)/(float(price)-float(change))
percent_decimal = round(Decimal(percent_change), 2)
if percent_decimal > 0:
return '+'+str(percent_decimal)
elif percent_decimal==0:
return '0'
else:
return '-'+str(abs(percent_decimal))
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 get_current_price(symbol):
"""
Get the latest price for a symbol.
:param symbol: (str)
:return: (float)
"""
quote = ystockquote.get_price(symbol)
if quote == 'N/A':
return None
return float(quote)
def __init__(self, ticker, sess):
self.ticker = ticker
self.sess = sess
# Next points will be inited in _initialize_points()
self.r2 = None
self.r1 = None
self.p = None
self.s1 = None
self.s2 = None
self.price = round(float(ystock.get_price(ticker)), 2)
self._initialize_points()
def updatePrices(stocks2): filne = "stocks.txt" f = open(filne, 'r+') lines = f.readlines() for i in range(1, len(lines)): place = i-1 #Only update if stock is owned if(stocks2[5][place]==True): stocks2[4][place] = ystockquote.get_price(stocks2[0][place]) return stocks2
def record_stock_price(self, stock, file):
price = ystockquote.get_price(stock)
now = datetime.now()
self.history[now] = price
with open(file, "a") as f:
f.write(str(now))
f.write(',')
f.write(price)
f.write("\n")
f.close()
def get_predicted_stock(symbol):
symbol = "$"+symbol.upper()
predicted_stock = {}
predicted_change = dao.get_predicted_stock_change(symbol, db)
current_value = get_price(symbol.strip("$"))
# Calculate a predicted stock value based on the predicted change
predicted_value = float(predicted_change) + float(current_value)
predicted_stock['symbol'] = symbol
predicted_stock['predicted_change'] = predicted_change
predicted_stock['predicted_value'] = predicted_value
predicted_stock['current_value'] = current_value
return json.dumps(predicted_stock)
def get_predicted_stock(symbol):
symbol = "$" + symbol.upper()
predicted_stock = {}
predicted_change = dao.get_predicted_stock_change(symbol, db)
current_value = get_price(symbol.strip("$"))
# Calculate a predicted stock value based on the predicted change
predicted_value = float(predicted_change) + float(current_value)
predicted_stock['symbol'] = symbol
predicted_stock['predicted_change'] = predicted_change
predicted_stock['predicted_value'] = predicted_value
predicted_stock['current_value'] = current_value
return json.dumps(predicted_stock)
def record_stock_price(self, stock, file):
price = ystockquote.get_price(stock)
now = datetime.now()
self.history[now] = price
with open(file, "a") as f:
f.write(str(now))
f.write(',')
f.write(price)
f.write("\n")
f.close()
def savequote(stockid, lastquotestamp, conn):
c = conn.cursor()
c.execute(
"select symbolgoogle, symbolyahoo, type from stocks where id=:id",
{'id': int(stockid)})
row = c.fetchone()
if row['type'].upper() == 'STOCK':
symbol = str(row['symbolgoogle'])
quote = getQuotes(symbol) # get quote
value = quote[0]["LastTradePrice"]
# parse uses posix stype for timezone offsets. ISO requires inversion in sign!!
correcteddate = quote[0]["LastTradeDateTimeLong"]
if correcteddate.find('+'):
correcteddate = correcteddate.replace('+', '-')
elif correcteddate.find('-'):
correcteddate = correcteddate.replace('-', '+')
date = dateutil.parser.parse(correcteddate, tzinfos=tzd)
timestamp = date.isoformat()
if date.tzinfo is None:
timestamp += 'Z'
elif row['type'].upper() == 'CURRENCY':
symbol = str(row['symbolyahoo'])
value = float(get_price(symbol)) # get quote
date = datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
timestamp = date.isoformat()
if (lastquotestamp is None) or (dateutil.parser.parse(
lastquotestamp, tzinfos=tzd) != date):
# Date changed since last quote => save to database
c.execute(
"""
insert into quotes(stockid,timestamp,value)
values(?,?,?)
""", (int(stockid), timestamp, float(value)))
if not (timestamp is None):
c = conn.cursor()
c.execute("""
UPDATE stocks
SET lastquotestamp = ?, lastquote = ?
WHERE id = ?;
""", (timestamp, float(value),
int(stockid))) # update last quote timestamp
conn.commit()
return timestamp, float(value)
else:
return None, None
def calculate_ebit_ev(cur, ticker):
ebit = float(get_last(ticker, "EBIT", cur))
shares = float(get_last(ticker, "total common shares out", cur))
bonds = float(get_last(ticker, "long-term debt", cur))
#try:
price = float(ystockquote.get_price(ticker))
#except ValueError:
# return 0
ev = price * shares + bonds
if ev == 0:
return
return ebit / ev
def index(request):
stocks = Stock.objects.all()
for stock1 in stocks:
stock1.lastprice = ystockquote.get_price(stock1)
# YYYY-MM-DD
historical_price = ystockquote.get_historical_prices(
stock1, '2016-05-24', '2016-05-26')
hprice = []
for values in historical_price:
hprice.append(historical_price[values]['Close'])
template = loader.get_template('stocktracker/index.html')
context = {'stocks': stocks}
return render(request, 'stocktracker/index.html', context)
def strategytwo():
bought_mode = False
global server
logging.info(
"Strategy TWO:SPX MAKES A NEW 50 DAY HIGH. THE % of NYSE issues making new highs falls by at least 2%. SHORT SPX on CLOSE. BUY 5 DAYS LATER"
)
logging.info("Current price of SPX")
logging.info(ystockquote.get_price("SPY"))
#chance of working is 95%
logging.info('\n')
todays_date = time.strftime("%Y-%m-%d")
logging.info("todays date is " + todays_date)
logging.info('\n')
date_N_days_ago = datetime.now() - timedelta(days=50)
f = str(date_N_days_ago)
date_fifty_days_ago = f.split(' ')[0]
logging.info("the date 50 days ago is")
logging.info(date_fifty_days_ago)
logging.info('\n')
historical_price = ystockquote.get_historical_prices(
"SPY", date_fifty_days_ago, todays_date)
histpricelist = historical_price.items()
histpricelist.sort()
try:
logging.info("the close from fifty days ago is " +
historical_price[date_fifty_days_ago]['Close'])
fiftydaysagoclose = float(
historical_price[date_fifty_days_ago]['Close'])
logging.info('\n')
except Exception:
logging.info(
"looks like the fifty days ago close was a non trading day fixing the problem"
)
logging.info("the close from fifty days ago is " +
str(histpricelist[0][1]['Close']))
fiftydaysagoclose = float(histpricelist[0][1]['Close'])
logging.info('\n')
#getpercentofnysesissues making new highs
def mainpartofthisstrategy():
#get the price every 10 minutes and see if it matches the strategy
current_price = float(ystockquote.get_price("SPY"))
threading.Timer(84600, strategytwo).start()
def run(self):
try:
try:
rate = float(ystockquote.get_price(self.code))
except Exception, err:
print err
return
share = stock.objects.get(code=self.code)
if share.price != rate:
share.update = share.update + 1
share.price = rate * 65
if rate > share.max_price_of_day:
share.max_price_of_day = rate
share.save()
connection.close()
print "sucess"
def run(self):
"""Plugin main loop"""
self.loadParameters()
self.sendEvent("Plugin started","Starting ticker plugin","info",int(time.time()))
while True:
# Loop over the items and lookup the stock price and volume
for i in self.items:
ticker = str(i["ticker"]).upper()
price = ystockquote.get_price(ticker)
volume = ystockquote.get_volume(ticker)
timestamp = int(time.time())
if volume == 'N/A' or price == 'N/A':
self.sendEvent('Ticker Not Found','Could not find ticker \"{0}\", skipping'.format(ticker),"error",timestamp)
else:
self.sendMeasurement('BOUNDARY_STOCK_PRICE',price,ticker,timestamp)
self.sendMeasurement('BOUNDARY_STOCK_VOLUME',volume,ticker,timestamp)
time.sleep(self.pollInterval)
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 fetchcurrentprice():
content1 = urllib.urlopen("https://www.google.com/finance?q=SPY").read()
m = re.search('(?:<span class=nwp>\n)(.*)', content1)
print(m.group(1))
while not 'Close' in m.group(1):
content1 = urllib.urlopen(
"https://www.google.com/finance?q=SPY").read()
m = re.search('(?:<span class=nwp>\n)(.*)', content1)
current_price = float(ystockquote.get_price("SPY"))
print(current_price)
current_price_array.append(current_price)
print(current_price_array)
if len(current_price_array) > 5760:
print("len of current price array was greater than 5760")
del current_price_array[0]
np.savetxt("spy.csv", current_price_array, fmt='%10.2f', delimiter=",")
time.sleep(15)
threading.Timer(30, fetchcurrentprice).start()
def run(stocks):
overall = 0
owned = []
for line in open(get_stockfile(), 'r').readlines():
if any(line.startswith(stock) for stock in stocks):
purchased = line.split()
current = ystockquote.get_price(purchased[0])
profit = round(float(current) - float(purchased[1]), 3)
overall += profit
print 'Sold', purchased[0], 'at', current + '.',
print 'Return was',
print_money(profit)
else:
owned.append(line)
with open(get_stockfile(), 'w') as data:
for stock in owned:
data.write(stock)
print 'Overall return:',
print_money(overall)
csvfile = open('nasdaqlist.csv', 'rb')
reader = csv.reader(csvfile)
rownum = 0
stocksymbols = []
stockDetails =[]
for row in reader:
# Save header row.
if rownum == 0:
header = row
else:
#print row
stocksymbols.append(row[0])
stockDetails.append(row)
rownum += 1
csvfile.close()
results = []
for stockDetail in stockDetails:
symbol = stockDetail[0]
price = float(ystockquote.get_price(symbol))
bookvalue = float(ystockquote.get_book_value(symbol))
halfBook = bookvalue * 0.5
if (price <= halfBook):
print ', '.join(stockDetail)
results.append(symbol)
print len(results)
def priceBought(self, stock):
self.price = float(quote.get_price(stock))
return self.price
return (sum - 48 * numchars)
#* you can send the text on the next line using Serial Monitor to set the clock to noon Jan 1 2010 and LLTC to $29.45
#T12623472002945
#T13246667523036
#rawtime = str(int(time()-28800))
#rawtime = str(int((time()-28800)) - 120 + 0 - 9 + 97 + 3600)
rawtime = str(int((time() - 28800)) - 120 + 0 - 9 + 97)
print "Raw Time: " + rawtime
print "Converted Time: " + strftime("%a, %d %b %Y %H:%M:%S +0000", localtime())
rawstock = str(ystockquote.get_price('LLTC'))
print "LLTC Stock Price is " + rawstock
rawstock = ''.join(i for i in rawstock if i.isdigit())
rawstock = rawstock[0:4]
print "Strip the decimal, trim to two " + rawstock
#yahoo_result = pywapi.get_weather_from_yahoo('95035', '')
#print "Yahoo says: It is " + string.lower(yahoo_result['condition']['text']) + " and " + yahoo_result['condition']['temp'] + "F now in Milpitas.\n\n"
#clockstring = "aaaaT" + rawtime + rawstock + "bbbb"
clockstring = "T" + rawtime + rawstock
clockstring = clockstring.encode('utf-8')
def validate_stock(stock):
return ystockquote.get_price(stock) != "0.00"
def test_get_price(self):
value = ystockquote.get_price(self.symbol)
self.assertIsInstance(value, str)
def getPriceOfStock(symbol): return float(ystockquote.get_price(symbol))
def get_price_time(symbol): price = ystockquote.get_price(symbol) current_time = datetime.datetime.now() return [symbol, price, str(current_time)]
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()
