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 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
print ma50 if myargs.ma200 is True: ma200 = stock.get_200day_moving_avg() print ma200 if myargs.marketcap is True: marketcap = stock.get_market_cap() print marketcap if myargs.getopen is True: getopen = stock.get_open() print getopen if myargs.getbook is True: getbook = stock.get_book_value() 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:
except: pass try: russell3000.set_value(s,'Open',shy.get_open()) except: pass try: russell3000.set_value(s,'Average daily volume',shy.get_avg_daily_volume()) except: pass try: russell3000.set_value(s,'Market cap',shy.get_market_cap()) except: pass try: russell3000.set_value(s,'Book value',shy.get_book_value()) except: pass try: russell3000.set_value(s,'Ebitda',shy.get_ebitda()) except: pass try: russell3000.set_value(s,'Dividend share',shy.get_dividend_share()) except: pass #try: # russell3000.set_value(s,'Divident yield',shy.get_dividend_yield()) #except: # pass try:
print(yahoo.get_ebitda())
print(yahoo.get_earnings_share())
print(yahoo.get_price_book())
print(goog.get_ebitda())
print(goog.get_earnings_share())
print(goog.get_price_book())
from yahoo_finance import Share
IBB = Share('IBB')
print(IBB.get_ebitda())
from yahoo_finance import Share
li = ['YHOO','GOOG']
yahoo = Share('YHOO')
goog = Share('GOOG')
print(yahoo.get_book_value())
for i in li:
t = Share(i)
print(i)
print(t.get_book_value())
from pprint import pprint
from yahoo_finance import Share
yahoo = Share('YHOO')
print(yahoo.get_ebitda())
pprint(yahoo.get_info())
import glob, pandas as pd
from yahoo_finance import Share
res = []
for f in glob.glob('data/*.csv'):
market = f.replace("data/", "").replace(".csv", "")
df = pd.read_csv(f)
for line in df.iterrows():
res.append((market, line[1].Symbol, line[1].Name))
for (market, symbol, name) in res:
if market == 'nyse':
x = Share(symbol)
print x.get_book_value()
print x.get_ebitda()
print x.get_earnings_share()
print x.get_price_sales()
from Parser.models import EtfInfo, EtfData, StockInfo, StockDetail
etfResult = StockInfo.objects.values('ticker', 'name')
#for etfIdx in range(0, len(etfResult)) :
tickerStr = etfResult[0]['ticker']
share = Share(tickerStr)
dateStr = share.get_trade_datetime()[0:11].replace('-','')
ma_200Str = convert(share.get_200day_moving_avg())
ma_50Str = convert(share.get_50day_moving_avg())
book_valueStr = convert(share.get_book_value())
volume_avgStr = convert(share.get_avg_daily_volume())
ebitdaStr = convert(share.get_ebitda())
dividend_yieldStr = convert(share.get_dividend_yield())
market_capStr = convert(share.get_market_cap())
year_highStr = convert(share.get_year_high())
year_lowStr = convert(share.get_year_low())
print tickerStr, dateStr, ma_200Str, ma_50Str, book_valueStr, volume_avgStr, ebitdaStr, dividend_yieldStr, market_capStr, year_highStr, year_lowStr
# print share.get_change()
# print share.get_days_high()
# print share.get_days_low()
# print share.get_dividend_share()
# print share.get_info()
# Fundamentals of stocks using yahoo finance as data source
from yahoo_finance import Share
tickers = [
'KMI', 'NNA', 'CAFD', 'GE', 'F', 'MMM', 'TXN', 'BBL', 'GLW', 'STM', 'INTC',
'QCOM'
]
for ticker in tickers:
stockobj = Share(ticker)
price = stockobj.get_price()
bookvalue = stockobj.get_book_value()
p_e = stockobj.get_price_earnings_ratio()
market_cap = stockobj.get_market_cap()
price_to_book = float(price) / float(bookvalue)
print("\n%s" % ticker)
print("price %.2f" % float(price))
print("bookvalue %.2f" % float(bookvalue))
print("price_to_book %.2f" % float(price_to_book))
print("P/E %.2f" % float(p_e))
print("market cap %s" % market_cap)
def loadKeyStatistics (cls, companyID = 'A'):
'''
dataset
df= pd.DataFrame(columns=['marketCapital','bookValue','ebitda','dividentShare','DividentYield','earningShare',
'BookPrice','SalesPrice','earningsGrowth','earningsRatio', 'symbol', 'date'])
'''
yahoo = Share(companyID)
yahoo.refresh()
try:
a = re.search('[a-zA-Z]+', yahoo.get_market_cap())
b = re.search('[a-zA-Z]+', yahoo.get_ebitda())
if a.group(0) is not None:
p = re.split('[a-zA-Z]+', yahoo.get_market_cap())
if a.group(0) in 'B':
marketCap = float(p[0]) * 10 ** 9
elif a.group(0) in 'M':
marketCap = float(p[0]) * 10 ** 6
else:
marketCap = -1
print ('Market cap: ' + yahoo.get_market_cap())
else:
marketCap = yahoo.get_market_cap()
if b.group(0) is not None:
p = re.split('[a-zA-Z]+', yahoo.get_ebitda())
if b.group(0) in 'B':
ebitda = float(p[0]) * 10 ** 9
elif b.group(0) in 'M':
ebitda = float(p[0]) * 10 ** 6
else:
ebitda = -1
print ('Ebitda: ' +yahoo.get_ebitda())
else:
ebitda = yahoo.get_ebitda()
except (TypeError, AttributeError):
print ('Missing :' + companyID)
e = sys.exc_info()[0]
print( "<p>Error: %s</p>" % e )
ebitda = -1.0
marketCap = -1.0
try:
company = LoadYahooFinance(symbol = companyID, marketCap = marketCap, bookValue = float(yahoo.get_book_value()), ebitda = ebitda,
dividentShare = float(yahoo.get_dividend_share()), dividentYield = float(yahoo.get_dividend_yield()), earningShare = float(yahoo.get_earnings_share()),
bookPrice = float(yahoo.get_price_book()), salesPrice = float(yahoo.get_price_sales()), earningsGrowth = float(yahoo.get_price_earnings_growth_ratio()),
earningRatio = float(yahoo.get_price_earnings_ratio()))
return company
except TypeError:
print ('Missing :' + companyID)
e = sys.exc_info()[0]
print( "<p>Error: %s</p>" % e )
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())
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 10 17:01:18 2016
@author: SMALLON
"""
IBB = ['AMGN','GILD','CELG','BIIB','REGN','MYL','ILMN','VRTX','ALXN','INCY','BMRN','MDVN','JAZZ', 'ALKS','SHPG','SGEN','ALNY','QGEN','UTHR','TSRO','NBIX','TECH','ENDP','ACAD','AKRX','ICPT','IONS','HZNP','JUNO','CBPO','LGND','PRAH','GRFS','MDCO','KITE','INCR','IPXL','MYGN','OPHT','NKTR','RARE','NVAX','EXEL','PRTA','IRWD','RDUS','BLUE','ONCE','AGIO','LXRX','ARIA','GWPH','PCRX','SAGE','PTLA','MCRB','ALDR','FPRX','INVA','XLRN','HALO','ACOR','ACHN','DEPO','FGEN','DERM','INSY','TBPH','CXRX','SRPT','CHRS','SUPN','MGNX','LMNX','AMAG','GHDX','RGEN','RLYP','CEMP','ADRO','MNTA','DBVT','FMI','AMPH','FOLD','XNCR','EGRX','SGNT','MACK','PACB','INSM','SGYP','ANIP','INO','CERS','RTRX','ATRA','AMRI','EPZM','PDLI','BPMC','CLVS','SCMP','NK','ARRY','XBIT','SCLN','FLML','RPTP','VNDA','LBIO','AERI','MNKD','CLDX','SPPI','OTIC','TLGT','FLXN','ARNA','OMER','GERN','PGNX','ENTA','AMRN','SGMO','RVNC','NDRM', 'BLCM','OMED','TRVN','ARDX','ARWR','CGEN','VSAR','AKBA','ADMS','NLNK','VTAE','COLL','AGTC','NSTG','CNCE','ESPR','IMGN','KPTI','PTCT','IMMU','PETX','ITEK','CCXI','BCRX','DRRX','FOMX','FLKS','ZGNX','RIGL','CRIS','VTL','CMRX','OVAS','RGLS','OSIR','QURE','EGLT','TTPH','NEOS','CASC','IMDZ','CARA','ECYT','AQXP','ANTH','OCUL','ADVM','ADHD','TKAI','SQNM','AFMD','ZFGN','INFI','LIFE','DRNA','CHMA','DNAI','KMPH','OREX','AEGR','USD']
SMBIx = IBB = ['AMGN','GILD','CELG','BIIB','REGN','MYL','ILMN','VRTX','ALXN','INCY','BMRN','MDVN','JAZZ', 'ALKS','SHPG','SGEN','ALNY','QGEN','UTHR','TSRO','NBIX','TECH','ENDP','ACAD','AKRX','ICPT','IONS','HZNP','JUNO','CBPO','LGND','PRAH','GRFS','MDCO','KITE','INCR','IPXL','MYGN','OPHT','NKTR','RARE','NVAX','EXEL','PRTA','IRWD','RDUS','BLUE','ONCE','AGIO','LXRX','ARIA','GWPH','PCRX','SAGE','PTLA','MCRB','ALDR','FPRX','INVA','XLRN','HALO','ACOR','ACHN','DEPO','FGEN','DERM','INSY','TBPH','CXRX','SRPT','CHRS','SUPN','MGNX','LMNX','AMAG','GHDX','RGEN','RLYP','CEMP','ADRO','MNTA','DBVT','FMI','AMPH','FOLD','XNCR','EGRX','SGNT','MACK','PACB','INSM','SGYP','ANIP','INO','CERS','RTRX','ATRA','AMRI','EPZM','PDLI','BPMC','CLVS','SCMP','NK','ARRY','XBIT','SCLN','FLML','RPTP','VNDA','LBIO','AERI','MNKD','CLDX','SPPI','OTIC','TLGT','FLXN','ARNA','OMER','GERN','PGNX','ENTA','AMRN','SGMO','RVNC','NDRM', 'BLCM','OMED','TRVN','ARDX','ARWR','CGEN','VSAR','AKBA','ADMS','NLNK','VTAE','COLL','AGTC','NSTG','CNCE','ESPR','IMGN','KPTI','PTCT','IMMU','PETX','ITEK','CCXI','BCRX','DRRX','FOMX','FLKS','ZGNX','RIGL','CRIS','VTL','CMRX','OVAS','RGLS','OSIR','QURE','EGLT','TTPH','NEOS','CASC','IMDZ','CARA','ECYT','AQXP','ANTH','OCUL','ADVM','ADHD','TKAI','SQNM','AFMD','ZFGN','INFI','LIFE','DRNA','CHMA','DNAI','KMPH','OREX','AEGR','USD']
from yahoo_finance import Share
for i in IBB:
t = Share(i)
book = float(t.get_book_value())
if (book > 5.00):
print(i,book,"Book value more than 5b")
from yahoo_finance import Share
for i in IBB:
t = Share(i)
P2S = (t.get_price_sales())
print(P2S)
# 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(
)
import glob, pandas as pd
from yahoo_finance import Share
res = []
for f in glob.glob('data/*.csv'):
market = f.replace("data/","").replace(".csv","")
df = pd.read_csv(f)
for line in df.iterrows():
res.append((market, line[1].Symbol, line[1].Name))
for (market,symbol,name) in res:
if market=='nyse':
x = Share(symbol)
print x.get_book_value()
print x.get_ebitda()
print x.get_earnings_share()
print x.get_price_sales()
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()
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)
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())
