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 stocks(dict_response):
message = ""
try:
query_text = dict_response['_text'].lower()
if query_text.find("stocks ") != -1:
query_text = query_text[7:]
y = Share(query_text)
message += "Trading information for " + y.get_name(
) + " (" + query_text + ") :\n"
message += "Opened: " + y.get_open() + "\n"
message += "Current: " + y.get_price() + "\n"
message += "Earnings share: " + y.get_earnings_share() + "\n"
message += "Short ratio: " + y.get_short_ratio() + "\n"
message += "Previous close: " + y.get_prev_close() + "\n"
except:
message = technical_issues()
return message
def get_company_info(ticker):
try:
s = Share(ticker)
data = {
'Market_cap': s.get_market_cap(),
'Average_volume': s.get_avg_daily_volume(),
'EPS': s.get_earnings_share(),
'Short_ratio': s.get_short_ratio(),
'PE': s.get_price_earnings_ratio(),
'PEG': s.get_price_earnings_growth_ratio(),
}
return DataFetcher._extract_company_info(data)
except YQLQueryError:
logger.error("Company info not found for {}".format(ticker))
except Exception as e:
logger.error("Unexpected error occured: {}".format(e))
return {}
def get_company_info(ticker):
try:
s = Share(ticker)
data = {
'Market_cap': s.get_market_cap(),
'Average_volume': s.get_avg_daily_volume(),
'EPS': s.get_earnings_share(),
'Short_ratio': s.get_short_ratio(),
'PE': s.get_price_earnings_ratio(),
'PEG': s.get_price_earnings_growth_ratio(),
}
return DataFetcher._extract_company_info(data)
except YQLQueryError:
logger.error("Company info not found for {}".format(ticker))
except Exception as e:
logger.error("Unexpected error occured: {}".format(e))
return {}
def get_symbol_yahoo_stats_yql(symbols, exclude_name=False):
"""
Get the symbols' basic statistics from Yahoo Finance.
Input:
symbols - a list of symbol strings, e.g. ['AAPL']
Output: stats in Pandas DataFrame.
This function is ported from pandas_datareader/yahoo/components.py
"""
sym_list = str2list(symbols)
if sym_list == None:
return DataFrame()
# Yahoo Finance tags, refer to http://www.financialwisdomforum.org/gummy-stuff/Yahoo-data.htm
tags = ['Symbol']
if not exclude_name:
tags += ['Name']
tags += ['Exchange', 'MarketCap', 'Volume', 'AverageDailyVolume', 'BookValue', 'P/E', 'PEG', 'Price/Sales',
'Price/Book', 'EBITDA', 'EPS', 'EPSEstimateNextQuarter', 'EPSEstimateCurrentYear', 'EPSEstimateNextYear',
'OneyrTargetPrice', 'PriceEPSEstimateCurrentYear', 'PriceEPSEstimateNextYear', 'ShortRatio',
'Dividend/Share', 'DividendYield', 'DividendPayDate', 'ExDividendDate']
lines = []
for sym in sym_list:
stock = Share(sym)
line = [sym]
if not exclude_name:
line += [stock.get_name()]
line += [stock.get_stock_exchange(), str2num(stock.get_market_cap(), m2b=True),
str2num(stock.get_volume()), str2num(stock.get_avg_daily_volume()), str2num(stock.get_book_value()),
str2num(stock.get_price_earnings_ratio()), str2num(stock.get_price_earnings_growth_ratio()),
str2num(stock.get_price_sales()), str2num(stock.get_price_book()), str2num(stock.get_ebitda()),
str2num(stock.get_earnings_share()), str2num(stock.get_EPS_estimate_next_quarter()),
str2num(stock.get_EPS_estimate_current_year()), str2num(stock.get_EPS_estimate_next_year()),
str2num(stock.get_one_yr_target_price()), str2num(stock.get_price_EPS_estimate_current_year()),
str2num(stock.get_price_EPS_estimate_next_year()), str2num(stock.get_short_ratio()),
str2num(stock.get_dividend_share()), str2num(stock.get_dividend_yield()), stock.get_dividend_pay_date(),
stock.get_ex_dividend_date()]
lines.append(line)
stats = DataFrame(lines, columns=tags)
stats = stats.drop_duplicates()
stats = stats.set_index('Symbol')
return stats
def selectStock(stocks):
'''
select the stock with today's trading volume at least 6 fold higher than
average historical trading volume
'''
start_time = time()
resultStock = {}
count = 0
num = 0
for symb in stocks.keys():
try:
stock = Share(symb)
vol = int(stock.get_volume())
daily_avg_vol = int(stock.get_avg_daily_volume())
price = float(stock.get_price())
prevPrice = float(stock.get_prev_close())
avg_50day = float(stock.get_50day_moving_avg())
avg_200day = float(stock.get_200day_moving_avg())
except (TypeError, AttributeError):
continue
num += 1
volRatio = vol / daily_avg_vol
print num, stocks[symb][0], volRatio
if volRatio > 6 and price > prevPrice and price > avg_50day:
count += 1
stocks[symb].extend([
vol, daily_avg_vol, volRatio, price, prevPrice, avg_50day,
avg_200day,
stock.get_price_earnings_ratio(),
stock.get_price_book(),
stock.get_short_ratio(),
stock.get_dividend_yield()
])
resultStock = {
symb: stocks[symb]
for symb in stocks.keys() if len(stocks[symb]) > 1
}
print '{} stock(s) has marvelous volume'.format(count)
print 'total time of running: {} seconds'.format(time() - start_time)
return resultStock
def write_technical_files(stock_code, start_time, end_time):
# """ Experiment on quandl """
# print('quandl data')
# mydata = quandl.get("FRED/GDP")
# print(mydata)
# print('hello')
# data = quandl.get("WIKI/FB.11", start_date="2014-01-01", end_date="2014-12-31", collapse="monthly", transform="diff")
# print(data)
stock = Share(stock_code)
print('stock.get_info()')
print(stock.get_info())
print('get_price()')
print(stock.get_price())
print('get_change()')
print(stock.get_change())
print('get_stock_exchange()')
print(stock.get_stock_exchange())
print('get_market_cap()')
print(stock.get_market_cap())
print('get_book_value()')
print(stock.get_book_value())
print('get_ebitda()')
print(stock.get_ebitda())
print('get_dividend_share()')
print(stock.get_dividend_share())
print('get_dividend_yield()')
print(stock.get_dividend_yield())
print('get_earnings_share()')
print(stock.get_earnings_share())
print('get_50day_moving_avg()')
print(stock.get_50day_moving_avg())
print('get_200day_moving_avg()')
print(stock.get_200day_moving_avg())
print('get_price_earnings_ratio()')
print(stock.get_price_earnings_ratio())
print('get_price_earnings_growth_ratio()')
print(stock.get_price_earnings_growth_ratio())
print('get_price_sales()')
print(stock.get_price_sales())
print('get_price_book()')
print(stock.get_price_book())
print('get_short_ratio()')
print(stock.get_short_ratio())
print('historical_data')
print(stock.get_historical(start_time, end_time))
historical_data = stock.get_historical(start_time, end_time)
info_text = "Symbol\t" + "Stock Exchange\t" + "Price\t" + "Market Cap\t" + "Book Value\t" + "EBITDA\t" + "50d Moving Avg\t" + "100d Moving Avg\n"
info_text += str(stock.get_info()['symbol']) + "\t" + str(stock.get_stock_exchange()) + "\t" + str(stock.get_price()) + "\t" + str(stock.get_market_cap()) + "\t" + str(stock.get_book_value()) + "\t";
info_text += str(stock.get_ebitda()) + "\t" + str(stock.get_50day_moving_avg()) + "\t" + str(stock.get_200day_moving_avg()) + "\n";
info_directory = '/data/info.tsv'
write_to_file(info_directory, info_text)
high_low_text = "date\t" + "High\t" + "Low\n"
open_close_text = "date\t" + "Open\t" + "Close\n"
volume_text = "date\t" + "Volume\n"
for index, value in enumerate(historical_data):
date = str(historical_data[len(historical_data) - 1 - index]['Date'])
date = date.replace('-','')
stock_high = str(historical_data[len(historical_data) - 1 - index]['High'])
stock_low = str(historical_data[len(historical_data) - 1 - index]['Low'])
stock_open = str(historical_data[len(historical_data) - 1 - index]['Open'])
stock_close = str(historical_data[len(historical_data) - 1 - index]['Close'])
stock_volume = str(int(historical_data[len(historical_data) - 1 - index]['Volume']) / 1000)
high_low_text += date + "\t" + stock_high + "\t" + stock_low + "\n"
open_close_text += date + "\t" + stock_open + "\t" + stock_close + "\n"
volume_text += date + "\t" + stock_volume + "\n"
high_low_directory = '/data/highlow.tsv'
open_close_directory = '/data/openclose.tsv'
volume_directory = '/data/volume.tsv'
write_to_file(high_low_directory, high_low_text)
write_to_file(open_close_directory, open_close_text)
write_to_file(volume_directory, volume_text)
ratio_text = "name\t" + "value\n"
if stock.get_change() != None:
name = "Change"
value = str(stock.get_change())
ratio_text += name + "\t" + value + "\n"
if stock.get_dividend_share() != None:
name = "Dividend Share"
value = str(stock.get_dividend_share())
ratio_text += name + "\t" + value + "\n"
if stock.get_dividend_yield() != None:
name = "Divident Yield"
value = str(stock.get_dividend_yield())
ratio_text += name + "\t" + value + "\n"
if stock.get_earnings_share() != None:
name = "Earning Share"
value = str(stock.get_earnings_share())
ratio_text += name + "\t" + value + "\n"
if stock.get_price_earnings_ratio() != None:
name = "Price Earning"
value = str(stock.get_price_earnings_ratio())
ratio_text += name + "\t" + value + "\n"
if stock.get_price_earnings_growth_ratio() != None:
name = "Price Earning Growth"
value = str(stock.get_price_earnings_growth_ratio())
ratio_text += name + "\t" + value + "\n"
if stock.get_price_sales() != None:
name = "Price Sales"
value = str(stock.get_price_sales())
ratio_text += name + "\t" + value + "\n"
if stock.get_price_book() != None:
name = "Price Book"
value = str(stock.get_price_book())
ratio_text += name + "\t" + value + "\n"
if stock.get_short_ratio() != None:
name = "Short"
value = str(stock.get_short_ratio())
ratio_text += name + "\t" + value + "\n"
ratio_directory = '/data/ratio.tsv'
write_to_file(ratio_directory, ratio_text)
selections.append('Volume: ')
print output
if myargs.change is True:
change = stock.get_change()
output.append(change)
selections.append('Change: ')
print change
if myargs.avgvol is True:
avgvolume = stock.get_avg_daily_volume()
print avgvolume
if myargs.short is True:
short = stock.get_short_ratio()
print short
if myargs.peratio is True:
pe = stock.get_price_earnings_ratio()
print pe
if myargs.exchange is True:
exchange = stock.get_stock_exchange()
if myargs.ma50 is True:
ma50 = stock.get_50day_moving_avg()
print ma50
if myargs.ma200 is True:
ma200 = stock.get_200day_moving_avg()
russell3000.set_value(s,'50 days MA',shy.get_50day_moving_avg()) except: pass try: russell3000.set_value(s,'200 days MA',shy.get_200day_moving_avg()) except: pass try: russell3000.set_value(s,'Price earnings ratio',shy.get_price_earnings_ratio()) except: pass try: russell3000.set_value(s,'Price earnings growth ratio',shy.get_price_earnings_growth_ratio()) except: pass try: russell3000.set_value(s,'Price sales',shy.get_price_sales()) except: pass try: russell3000.set_value(s,'Price book',shy.get_price_book()) except: pass try: russell3000.set_value(s,'Short ratio',shy.get_short_ratio()) except: pass u=datetime.now() ofn='r3alldata'+str(u)[0:4]+str(u)[5:7]+str(u)[8:10]+'.xls' russell3000.to_excel(ofn)
def checklist(symbol, ibd50_list, ibd_session):
"""
Looks up information on a given stock market symbol.
The returned dictionary contains all information from
Dr. Wish's Stock Checklist for HONR348M.
"""
stock = {}
# Load price data from yahoo.
share = Share(symbol)
ks = yahoo_ks(symbol)
# Basics
basics = stock["basics"] = {}
basics["date"] = datetime.now().strftime("%m/%d/%Y %I:%M:%S%z")
basics["symbol"] = symbol
basics["equity_name"] = share.get_name()
basics["price"] = float(share.get_price())
basics["52w_low"] = float(share.get_year_low())
basics["52w_high"] = float(share.get_year_high())
basics["percent_from_52w_low"] = share.get_percent_change_from_year_low()
basics["percent_from_52w_high"] = share.get_percent_change_from_year_high()
# IBD (Stocks only)
ibd = stock["ibd"] = ibd_stock_checkup(symbol, ibd_session)
# ibd["industry"]
ibd["industry_rank"] = float(ibd["industry_rank"])
# ibd["industry_top5"]
# ibd["3y_eps_growth"]
# ibd["3y_sales_growth"]
# ibd["eps_change"]
ibd["eps_rating"] = float(ibd["eps_rating"])
ibd["rs_rating"] = float(ibd["rs_rating"])
# ibd["acc_distr_rating"]
ibd["ibd_rating"] = float(ibd["ibd_rating"])
ibd["in_ibd50"] = symbol in ibd50_list
# ibd["fundamental_greens"]
# ibd["technical_greens"]
ibd["next_earning"] = datetime.strptime(ibd["next_earning"], '%m/%d/%Y')
# Yahoo Finance (Stocks only)
yahoo = stock["yahoo"] = {}
yahoo["pe"] = float(share.get_price_earnings_ratio())
yahoo["peg"] = float(share.get_price_earnings_growth_ratio())
yahoo["ps"] = float(share.get_price_sales())
yahoo["market_cap"] = share.get_market_cap()
yahoo["float"] = ks["Float"]
yahoo["annual_roe"] = ks["Return on Equity"]
yahoo["percent_inst"] = ks["% Held by Institutions"]
yahoo["percent_float_short"] = ks["Short % of Float"]
yahoo["short_ratio"] = float(share.get_short_ratio())
# Evidence of an uptrend/downtrend
uptrend = stock["uptrend"] = {}
downtrend = stock["downtrend"] = {}
pdstockdata = data.DataReader(symbol, 'yahoo', '1900-01-01')
sd = StockDataFrame.retype(pdstockdata)
sd.BOLL_PERIOD = 15
close1 = sd['close'][-1]
close2 = sd['close'][-2]
low1 = sd['low'][-1]
low2 = sd['low'][-2]
high1 = sd['high'][-1]
high2 = sd['high'][-2]
avg_30d = sd['close_30_sma'][-1]
avg_4w = sd['close_20_sma'][-1]
avg_10w = sd['close_50_sma'][-1]
avg_30w = sd['close_150_sma'][-1]
high_52w = sd['high'].tail(250).max()
lbb1 = sd['boll_lb'][-1]
lbb2 = sd['boll_lb'][-2]
ubb1 = sd['boll_ub'][-1]
ubb2 = sd['boll_ub'][-2]
# Find all GLTs (ATH not broken for at least another 90 days)
last_ath = 0.0
ath = Series()
for day, day_high in sd['high'].iteritems():
last_ath = max(last_ath, day_high)
ath.set_value(day, last_ath)
ath_days = sd[sd['high'] == ath]['high']
glt = Series()
for i, (day, high) in enumerate(ath_days.iteritems()):
next_day = ath_days.keys()[i +
1] if i < len(ath_days) - 1 else Timestamp(
str(date.today()))
if next_day - day >= Timedelta('90 days'):
glt.set_value(day, high)
uptrend["c>30d_avg"] = close1 > avg_30d
uptrend["c>10w_avg"] = close1 > avg_10w
uptrend["c>30w_avg"] = close1 > avg_30w
uptrend["4w>10w>30w"] = avg_4w > avg_10w > avg_30w
# uptrend["w_rwb"] =
uptrend["last_glt_date"] = glt.keys()[-1].to_datetime().date(
) if len(glt) > 0 else None
uptrend["last_glt_high"] = glt[-1] if len(glt) > 0 else None
uptrend["above_last_glt"] = len(glt) > 0 and close1 > glt[-1]
uptrend["macd_hist_rising"] = sd['macdh'][-1] > sd['macdh_4_sma'][-1]
uptrend["stoch_fast>slow"] = sd['rsv_10_4_sma'][-1] > sd[
'rsv_10_4_sma_4_sma'][-1]
# uptrend["bb_up_expansion_l2"]
# uptrend["rs>30d_avg"] = (Need Investors.com data)
# uptrend["rs_rising"] = (Need Investors.com data)
uptrend["52w_high_l2"] = high_52w == high1 or high_52w == high2
uptrend["ath_l2"] = ath[-1] == high1 or ath[-2] == high2
uptrend["1y_doubled"] = close1 >= 2 * sd['close'][-255:-245].mean()
# uptrend["bounce_30d_l2"] =
# uptrend["bounce_10w_l2"] =
# uptrend["bounce_30w_l2"] =
uptrend["stoch<50"] = sd['rsv_10_4_sma'][-1] < 50
uptrend["<bb_lower_l2"] = low1 < lbb1 or low2 < lbb2
uptrend[
"above_avg_volume"] = sd['volume'][-1] > 1.5 * sd['volume_50_sma'][-1]
downtrend["c<30d_avg"] = close1 < avg_30d
downtrend["c<10w_avg"] = close1 < avg_10w
downtrend["c<30w_avg"] = close1 < avg_30w
downtrend["4w<10w<30w"] = avg_4w < avg_10w < avg_30w
# downtrend["w_bwr"] =
downtrend["macd_hist_falling"] = sd['macdh'][-1] < sd['macdh_4_sma'][-1]
downtrend["stoch_fast<slow"] = sd['rsv_10_4_sma'][-1] < sd[
'rsv_10_4_sma_4_sma'][-1]
# downtrend["bb_down_expansion_l2"]
# downtrend["bounce_30d_l2"] =
# downtrend["bounce_10w_l2"] =
# downtrend["bounce_30w_l2"] =
downtrend["stoch>50"] = sd['rsv_10_4_sma'][-1] > 50
downtrend[">bb_upper_l2"] = high1 > ubb1 or high2 > ubb2
return stock
from yahoo_finance import Share, Currency
yahoo = Share('AAPL')
yahoo.refresh()
print yahoo.get_info()
print yahoo.get_avg_daily_volume()
print yahoo.get_stock_exchange()
print yahoo.get_book_value()
print yahoo.get_ebitda()
print yahoo.get_dividend_share()
print yahoo.get_price_earnings_ratio()
print yahoo.get_short_ratio()
print yahoo.get_price_book()
# f = open('nasdaqlisted.txt', 'r')
# print (f.readline())
# print (f.readline())
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 "get_percent_change_from_year_low:", tesla.get_percent_change_from_year_low( ) print "get_change_from_year_low:", tesla.get_change_from_year_low() print "get_change_from_year_high:", tesla.get_change_from_year_high() print "get_percent_change_from_200_day_moving_average:", tesla.get_percent_change_from_200_day_moving_average( ) print "get_change_from_200_day_moving_average:", tesla.get_change_from_200_day_moving_average( )
def get_stock_info():
share = Share('AAPL')
opening = share.get_open()
dividend_yeild = share.get_earnings_share()
print share.get_short_ratio()
from yahoo_finance import Share, Currency
yahoo = Share('AAPL')
yahoo.refresh()
print yahoo.get_info()
print yahoo.get_avg_daily_volume()
print yahoo.get_stock_exchange()
print yahoo.get_book_value()
print yahoo.get_ebitda()
print yahoo.get_dividend_share()
print yahoo.get_price_earnings_ratio()
print yahoo.get_short_ratio()
print yahoo.get_price_book()
# f = open('nasdaqlisted.txt', 'r')
# print (f.readline())
# print (f.readline())
