def fetch_data(self):
print("fetching")
stock = self.stock
start_date = datetime.strftime(self.date - timedelta(days=500), '%Y-%m-%d')
end_date = datetime.strftime(self.date, '%Y-%m-%d')
print("downloading stock data...")
try:
share_getter = Share(stock)
if stock[-1] == 'L': comparitor = Share('^FTSE')
else: comparitor = Share(share_getter.get_stock_exchange())
except:
print("network not available")
comparitor = None
df, dfb = pd.DataFrame(), pd.DataFrame()
try:
df = df.from_dict(share_getter.get_historical(start_date, end_date))
dfb = dfb.from_dict(comparitor.get_historical(start_date, end_date))
print("download complete: fetched", len(df.index) +
len(dfb.index), "records")
df = df.drop(['Symbol'], axis=1)
df['comparitor'] = dfb['Adj_Close']
df['Adj_Close'] = pd.to_numeric(df['Adj_Close'], errors='ignore')
df['Volume'] = pd.to_numeric(df['Volume'], errors='ignore')
df['comparitor'] = pd.to_numeric(df['comparitor'], errors='ignore')
return df
except Exception as e:
print("error in fetch_data", e)
return df
def _fetch_data(self, base_date, end_date):
"""
helper function which retrieves data from the yahoo finance api
"""
print("downloading stock data...")
try:
share_getter = Share(self.stock)
if self.stock[-1] == 'L': comparitor = Share('^FTSE')
else: comparitor = Share(share_getter.get_stock_exchange())
except:
print("network not available")
comparitor = None
df, dfb = pd.DataFrame(), pd.DataFrame()
try:
df = df.from_dict(share_getter.get_historical(base_date, end_date))
dfb = dfb.from_dict(comparitor.get_historical(base_date, end_date))
print("download complete: fetched",
len(df.index) + len(dfb.index), "records")
df = df.drop(['Symbol'], axis=1)
df['comparitor'] = dfb['Adj_Close']
df['Adj_Close'] = pd.to_numeric(df['Adj_Close'], errors='ignore')
df['comparitor'] = pd.to_numeric(df['comparitor'], errors='ignore')
df['comparitor'] = df['Adj_Close'] / df['comparitor']
df['roll_av'] = df['Adj_Close'].rolling(center=False,
window=7).mean()
return df
except Exception as e:
print("error in fetch_data", e)
return df
def get_symbol_exchange(sym):
"""
Download the stock exchange sym from Yahoo Finance.
YQL is required.
"""
stock = Share(sym)
return stock.get_stock_exchange()
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 get_current_stock_info(stock_short):
stock_share = Share(stock_short)
stock_current_info = {}
stock_current_info['stock_short'] = stock_short
stock_latest_price = stock_share.get_price()
stock_current_info['stock_latest_price'] = stock_latest_price
stock_trade_datetime = stock_share.get_trade_datetime()
stock_current_info['stock_trade_datetime'] = stock_trade_datetime
stock_exchange = stock_share.get_stock_exchange()
stock_current_info['stock_exchange'] = stock_exchange
stock_company_name = stock_share.get_name()
stock_current_info['stock_company_name'] = stock_company_name
return stock_current_info
def fetch_stock_price(self, stock_unit_key):
# Step 1: Make HTTP Call to fetch the Stock Details
# Step 2: Once received, create it into its corresponding model
# Step 2.1 : Between the models, exchange packet as a native dictionary, rather as a JSON object
# Get the share price
share_item = Share(stock_unit_key)
if share_item.get_open() is None:
return
share_item_dict = share_item.data_set
st_model = StockModel()
st_model.stock_unit = stock_unit_key
st_model.stock_title = share_item_dict['Name']
# Share Price + Unit of Currency
st_model.stock_price = share_item.get_price(
) + " " + share_item_dict['Currency']
deviation_price = share_item.get_change()
st_model.stock_deviation = deviation_price + " (" + share_item_dict[
'ChangeinPercent'] + ") " # Ex: '-1.83 (-1.59%)'
if deviation_price[0] == '-':
st_model.stock_deviation_status = 'Decline'
else:
st_model.stock_deviation_status = 'Incline'
st_model.stock_equity = share_item.get_stock_exchange()
st_model.stock_last_update_time = 'At close: ' + share_item_dict[
'LastTradeDateTimeUTC']
st_model.stock_52wkrange = share_item.get_year_low(
) + " - " + share_item.get_year_high()
st_model.stock_open = share_item.get_open()
st_model.stock_market_cap = share_item.get_market_cap()
st_model.stock_prev_close = share_item.get_prev_close()
st_model.stock_peratio_tte = share_item.get_price_earnings_ratio()
st_model_to_publish = self.payload_to_publish_dict.get_stock_payload_to_publish(
st_model)
self.push_stock_to_delivery_queue(st_model_to_publish, stock_unit_key)
def bot_action(c, symbol):
stock = Share(symbol) # Link stock with yahoo_finance module
print(stock)
if stock.get_price() == None:
main()
#print(stock.get_price())
head = 'Up to date stock info for **${0}** ({1}):\n\n'.format(symbol.upper(), stock.get_name())
price = '**Price:** ${0:.2f}\n\n'.format(float(stock.get_price()))
price_open = '**Open:** ${0:.2f}\n\n'.format(float(stock.get_open()))
change = '**Change:** {0:.2f} ({1})\n\n'.format(float(stock.get_change()), stock.get_percent_change())
vol = '**Volume:** {0:,.2f}\n\n'.format(float(stock.get_volume()))
market_cap = '**Mkt Cap:** {0}\n\n'.format(stock.get_market_cap())
average = '**Average (50 day):** {0:.2f}\n\n'.format(float(stock.get_50day_moving_avg()))
exchange = '**Exchange:** {0}\n\n'.format(stock.get_stock_exchange())
divider = '-----------------------------------------------------------------------------------------\n\n'
tail = "Don't abuse me, robots have feelings too! | [Source Code](https://github.com/Logicmn/Reddit-Stock-Bot) " \
"| [Report Bug](https://www.reddit.com/message/compose/?to=Pick-a-Stock) " \
"| [Suggest Feature](https://www.reddit.com/message/compose/?to=Pick-a-Stock)"
c.reply(head + divider + price + price_open + change + vol + market_cap + average + exchange+ divider + tail)
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 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)
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() print ma200 if myargs.marketcap is True: marketcap = stock.get_market_cap() print marketcap if myargs.getopen is True: getopen = stock.get_open()
from yahoo_finance import Share
inp = open('input.txt', 'r')
out = open('output.txt', 'w')
for line in inp:
temp = Share(line)
temp.refresh()
out.write(line.rstrip("\n") + "," + temp.get_price() + "," + temp.get_change() + "\n")
#FORMAT: Symbol, last closing price, last change
temp = Share('FUSVX')
print(temp.get_stock_exchange())
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())
#make sure it really represents a stock
try:
yahooSymbol = Share(ticker)
except:
print('error in starting ticker- ' + ticker + " deleted")
error = 1
try:
yahooIndustry = industry(ticker)
except:
print('error in getting industry- ' + ticker + " deleted")
error = 1
if error != 1:
# If NYSE
if str(yahooSymbol.get_stock_exchange()) == "NYQ":
NYSEdict[ticker] = (yahooSymbol.get_name(), yahooIndustry)
current = len(NYSEquotes)
try:
NYSEquotes.append(
quotes_historical_yahoo_ochl(ticker, d1, d2,
asobject=True))
except:
print('error - ' + ticker + " deleted")
NYSEdict.pop(ticker)
if current != len(NYSEquotes):
del NYSEquotes[len(NYSEquotes) - 1]
else:
if NYSEquotes[len(NYSEquotes) - 1] == None:
del NYSEquotes[len(NYSEquotes) - 1]
NYSEdict.pop(ticker)
def result_page(request):
rstlist = list()
grow_sortlst = list()
value_sortlst = list()
quality_sortlst = list()
grow_stcklist = [ 'PNW','RL','PPG','ACN', 'ATVI', 'AYI', 'AMD', 'LNT', 'ALXN', 'GOOGL']
value_stcklist = ['AMG', 'AFL', 'APD', 'AKAM','PCG','PM','PSX', 'AAP', 'AES', 'AET']
quality_stcklist = ['MMM', 'ABT', 'ABBV','PEP','PKI','PRGO','PFE', 'ALB', 'ECL', 'AGN']
stckdict = dict()
if request.method == 'POST':
allotment = int(str(request.POST['allotment']))
ori_allotment = allotment
iv_type = 0
for key in request.POST.keys():
print "iv_type="+str(iv_type)
print str(key)
if key in ['ethical','growth','index','quality','value']:
iv_type = iv_type + 1
print("current selected types count = " + str(iv_type))
if iv_type == 2:
allotment = allotment/float(2)
if 'ethical' in request.POST.keys():
AAPL = Share('AAPL')
aapl_f = float(str(AAPL.get_percent_change_from_year_low())[0:-1]) + \
float(str(AAPL.get_percent_change_from_50_day_moving_average())[0:-1]) - \
float(str(AAPL.get_percent_change_from_year_high())[0:-1])
ADBE = Share('ADBE')
adbe_f = float(str(ADBE.get_percent_change_from_year_low())[0:-1]) + \
float(str(ADBE.get_percent_change_from_50_day_moving_average())[0:-1]) - \
float(str(ADBE.get_percent_change_from_year_high())[0:-1])
NSRGY = Share('NSRGY')
nsrgy_f = float(str(NSRGY.get_percent_change_from_year_low())[0:-1]) + \
float(str(NSRGY.get_percent_change_from_50_day_moving_average())[0:-1]) - \
float(str(NSRGY.get_percent_change_from_year_high())[0:-1])
stckdict['AAPL'] = AAPL
stckdict['ADBE'] = ADBE
stckdict['NSRGY'] = NSRGY
total_f = (aapl_f + adbe_f + nsrgy_f)*iv_type
aapl_pct = aapl_f/float(total_f)
adbe_pct = adbe_f/float(total_f)
nsrgy_pct = nsrgy_f/float(total_f)
aaplD = {"sticker":"AAPL","name":AAPL.get_name(),"aloc_pct":str(aapl_pct),"aloc_amt":str(allotment*aapl_pct),"price":str(AAPL.get_price()),"exchange":str(AAPL.get_stock_exchange())}
adbeD = {"sticker":"ADBE","name":ADBE.get_name(),"aloc_pct":str(adbe_pct),"aloc_amt":str(allotment*adbe_pct),"price":str(ADBE.get_price()),"exchange":str(ADBE.get_stock_exchange())}
nsrgyD = {"sticker":"NSRGY","name":NSRGY.get_name(),"aloc_pct":str(nsrgy_pct),"aloc_amt":str(allotment*nsrgy_pct),"price":str(NSRGY.get_price()),"exchange":str(NSRGY.get_stock_exchange())}
rstlist.append(aaplD)
rstlist.append(adbeD)
rstlist.append(nsrgyD)
if 'growth' in request.POST.keys():
for stock in grow_stcklist:
while True:
try:
detail = Share(stock)
except:
time.sleep(0.1)
continue
break
stckdict[stock]=detail
heapq.heappush(grow_sortlst, (float(str(detail.get_percent_change_from_year_low())[0:-1]) +
float(
str(detail.get_percent_change_from_200_day_moving_average())[0:-1]) +
float(str(detail.get_percent_change_from_50_day_moving_average())[0:-1]) +
float(str(detail.get_percent_change_from_year_high())[0:-1]), stock,
detail))
if len(grow_sortlst) > 3:
heapq.heappop(grow_sortlst)
total_f = 0
for item in grow_sortlst:
total_f = total_f + item[0]
for item in grow_sortlst:
item_pct = item[0]/float(total_f*iv_type)
item_amt = allotment*item_pct
rstlist.append({"sticker":item[1],"name":item[2].get_name(),"aloc_pct":str(item_pct),"aloc_amt":str(item_amt),"price":str(item[2].get_price()),"exchange":str(item[2].get_stock_exchange())})
if 'index' in request.POST.keys():
VTI = Share('VTI')
vti_f = float(str(VTI.get_percent_change_from_year_low())[0:-1]) + \
float(str(VTI.get_percent_change_from_200_day_moving_average())[0:-1]) - \
float(str(VTI.get_percent_change_from_year_high())[0:-1])
IXUS = Share('IXUS')
ixus_f = float(str(IXUS.get_percent_change_from_year_low())[0:-1]) + \
float(str(IXUS.get_percent_change_from_200_day_moving_average())[0:-1]) - \
float(str(IXUS.get_percent_change_from_year_high())[0:-1])
ILTB = Share('ILTB')
iltb_f = float(str(ILTB.get_percent_change_from_year_low())[0:-1]) + \
float(str(ILTB.get_percent_change_from_200_day_moving_average())[0:-1]) - \
float(str(ILTB.get_percent_change_from_year_high())[0:-1])
stckdict['VTI'] = VTI
stckdict['IXUS'] = IXUS
stckdict['ILTB'] = ILTB
total_f = (vti_f + ixus_f + iltb_f)*iv_type
vti_pct = vti_f / float(total_f)
ixus_pct = ixus_f / float(total_f)
iltb_pct = iltb_f / float(total_f)
vtiD = {"sticker": "VTI", "name": VTI.get_name(), "aloc_pct": str(vti_pct),
"aloc_amt": str(allotment * vti_pct), "price": str(VTI.get_price()),
"exchange": str(VTI.get_stock_exchange())}
ixusD = {"sticker": "IXUS", "name": IXUS.get_name(), "aloc_pct": str(ixus_pct),
"aloc_amt": str(allotment * ixus_pct), "price": str(IXUS.get_price()),
"exchange": str(IXUS.get_stock_exchange())}
iltbD = {"sticker": "ILTB", "name": ILTB.get_name(), "aloc_pct": str(iltb_pct),
"aloc_amt": str(allotment * iltb_pct), "price": str(ILTB.get_price()),
"exchange": str(ILTB.get_stock_exchange())}
rstlist.append(vtiD)
rstlist.append(ixusD)
rstlist.append(iltbD)
if 'quality' in request.POST.keys():
for stock in quality_stcklist:
while True:
try:
detail = Share(stock)
except:
time.sleep(0.1)
continue
break
stckdict[stock] = detail
heapq.heappush(quality_sortlst, (
float(detail.get_price_earnings_ratio() if detail.get_price_earnings_ratio() != None else 0) +
float(
detail.get_price_earnings_growth_ratio() if detail.get_price_earnings_growth_ratio() != None else 0) +
float(
detail.get_change_from_200_day_moving_average() if detail.get_change_from_200_day_moving_average() != None else 0) +
float(
detail.get_price_earnings_growth_ratio() if detail.get_price_earnings_growth_ratio() != None else 0),
stock, detail))
if len(quality_sortlst) > 3:
heapq.heappop(quality_sortlst)
total_f = 0
for item in quality_sortlst:
total_f = total_f + item[0]
for item in quality_sortlst:
item_pct = item[0] / float(total_f*iv_type)
item_amt = allotment * item_pct
rstlist.append({"sticker": item[1], "name": item[2].get_name(), "aloc_pct": str(item_pct),
"aloc_amt": str(item_amt), "price": str(item[2].get_price()),
"exchange": str(item[2].get_stock_exchange())})
if 'value' in request.POST.keys():
for stock in value_stcklist:
while True:
try:
detail = Share(stock)
except:
time.sleep(0.1)
continue
break
stckdict[stock] = detail
heapq.heappush(value_sortlst,
(float(detail.get_dividend_yield() if detail.get_dividend_yield() != None else 0) +
float(
detail.get_price_earnings_growth_ratio() if detail.get_price_earnings_growth_ratio() != None else 0) -
float(detail.get_price_book() if detail.get_price_book() != None else 0), stock,
detail))
if len(value_sortlst) > 3:
heapq.heappop(value_sortlst)
total_f = 0
for item in value_sortlst:
total_f = total_f + item[0]
print "total_f=" + str(total_f)
for item in value_sortlst:
item_pct = item[0] / float(total_f*iv_type)
item_amt = allotment * item_pct
rstlist.append({"sticker": item[1], "name": item[2].get_name(), "aloc_pct": str(item_pct),
"aloc_amt": str(item_amt), "price": str(item[2].get_price()),
"exchange": str(item[2].get_stock_exchange())})
days_cnt = 15
str_date = str((datetime.now() - timedelta(days=days_cnt)).date().isoformat())
end_date = str(datetime.today().date().isoformat())
day_pro = list()
remaining = 0
for item in rstlist:
while True:
try:
hist_info = stckdict[item["sticker"]].get_historical(str_date,end_date)
except:
continue
break
for i in range(0,6):
if len(day_pro)<=i:
day_pro.append({hist_info[i]["Date"]:float(hist_info[i]["Close"])*int(float(item["aloc_amt"])/float(hist_info[i]["Open"]))+float(item["aloc_amt"])%float(hist_info[i]["Open"])})
else:
day_pro[i][hist_info[i]["Date"]] = float(day_pro[i][hist_info[i]["Date"]]) + float(hist_info[i]["Close"])*int(float(item["aloc_amt"])/float(hist_info[i]["Open"])) + float(item["aloc_amt"])%float(hist_info[i]["Open"])
rstlist.append({"sticker":"portfolio","history":day_pro})
print(json.dumps(rstlist))
return render(request, 'portfolio/result.html', {'result': json.dumps(rstlist)})
return render(request, 'portfolio/home.html')
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())
