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
class StockAnalysis:
stock_symbol = 'YHOO'
stock_company_name = "Yahoo Inc,"
quote = Share(stock_symbol)
name = quote.get_name()
stock_company_name = name.split(". ")
def __init__(self,symbol):
self.stock_symbol = symbol
self.quote = Share(self.stock_symbol)
self.name = self.quote.get_name()
self.stock_company_name = self.name.split(". ")
def getStockSymbol(self):
return self.stock_symbol
def getStockPriceInfo(self,symbol):
stock_price = self.quote.get_price()
currency = self.quote.get_currency()
#name = self.quote.get_name()
#stock_company_name = name.split(". ")
price_info = {'Symbol':symbol,'Price':stock_price,'Currency':currency,'Name':self.stock_company_name[0]}
return price_info
def getDividendYieldInfo(self,symbol):
dividend_yield = self.quote.get_dividend_yield()
dividend_info = {'Symbol':symbol,'DividendYield':dividend_yield,'Unit':'%'}
return dividend_info
def getPayOurRatio(self,symbol):
dividend_per_share = self.quote.get_dividend_share()
EPS_current_year = self.quote.get_EPS_estimate_current_year()
pay_out_ratio = (float(dividend_per_share) / float(EPS_current_year))*100
pay_out_ratio = float("{0:.2f}".format(pay_out_ratio))
pay_out_info = {'Symbol':symbol,'PayOut Ratio':pay_out_ratio, "Unit":"%",'Name':self.stock_company_name[0]}
return pay_out_info
def getDeividendDetails(self,symbol):
dividend_per_share = self.quote.get_dividend_share()
EPS_current_year = self.quote.get_EPS_estimate_current_year()
dividend_yield = self.quote.get_dividend_yield()
hold_date = self.quote.get_ex_dividend_date()
payout_date = self.quote.get_dividend_pay_date()
if dividend_per_share is None:
dividend_per_share = "0"
dividend_yield = "0%"
payout_date = "None"
hold_date = "None"
pay_out_ratio = (float(dividend_per_share) / float(EPS_current_year))*100
pay_out_ratio = str(float("{0:.2f}".format(pay_out_ratio)))+"%"
dividend_info = {'Symbol':symbol, 'DividedPerShare':dividend_per_share, 'EPSCurrentYearEstimation': EPS_current_year, 'PayOutRatio':pay_out_ratio,'ExDividedDate':hold_date,'LastPayoutDate':payout_date,'DividendYield':dividend_yield,'Name':self.stock_company_name[0]}
return dividend_info
def getExDividedDate(self,symbol):
hold_date = self.quote.get_ex_dividend_date()
payout_date = self.quote.get_dividend_pay_date()
data = {'Symbol':symbol,'ExDividedDate':hold_date,'LastPayoutDate':payout_date,'Name':self.stock_company_name[0]}
return data
def isDividedRateHealthy(self):
pass
def getDividendDateDetails(self):
pass
def getNumberOfOutStandingShares(self,symbol):
total_market_cap = self.quote.get_market_cap()
current_price = self.quote.get_prev_close()
if "B" in total_market_cap:
total_market_cap = total_market_cap.rstrip("B")
total_market_cap = float(total_market_cap)*1000000000
elif "M" in total_market_cap:
total_market_cap = total_market_cap.rstrip("M")
total_market_cap = float(total_market_cap)*100000000
out_standing_shares = (total_market_cap/float(current_price))/1000000
out_standing_shares = round(out_standing_shares,2)
data = {'Symbol':symbol,'OutStandingShares':out_standing_shares,'Name':self.stock_company_name[0]}
return data
def get200DaysLowPrice(self,symbol):
pass
def get200DaysHighPrice(self,symbol):
pass
def get50DaysLowPrice(self,symbol):
pass
def get50DaysHighPrice(self,symbol):
pass
def getPERation(self):
pass
def stock_quote_get():
print(request.args.get('symbol'))
symbol = str(request.args.get('symbol'))
# get all the relevant data from the Yahoo Finance API
stock = Share(symbol)
stock_name = stock.get_name()
stock_symbol = stock.symbol
stock_price = stock.get_price()
stock_change = stock.get_change()
stock_change_pct = stock.get_percent_change()
prev_close = stock.get_prev_close()
open = stock.get_open()
day_range = stock.get_days_range()
year_range = stock.get_year_range()
volume = stock.get_volume()
avg_volume = stock.get_avg_daily_volume()
market_cap = stock.get_market_cap()
pe_ratio = stock.get_price_earnings_ratio()
eps = stock.get_earnings_share()
dividend = stock.get_dividend_share()
dividend_yld = stock.get_dividend_yield()
dividend_ex_date = stock.get_ex_dividend_date()
yr_target = stock.get_one_yr_target_price()
historical = stock.get_historical('2017-01-01',
date.isoformat(date.today()))
# put the data into the DynamoDB database
table = dynamodb.Table('Stocks')
response = table.put_item(
Item={
'symbol': symbol,
'date': date.isoformat(date.today()),
'prev_close': prev_close,
'open': open,
'day_range': day_range,
'year_range': year_range,
'volume': volume,
'avg_volume': avg_volume,
'market_cap': market_cap,
'pe_ratio': pe_ratio,
'eps': eps,
'dividend': dividend,
'dividend_yld': dividend_yld,
'dividend_ex_date': dividend_ex_date,
'yr_target': yr_target,
})
close_history = []
for point in historical:
close_date = point['Date']
close_date = int(
time.mktime(datetime.strptime(close_date, "%Y-%m-%d").timetuple()))
close_price = point['Adj_Close']
close_price = float(close_price)
close_history.append([close_date, close_price])
return render_template("stock/stock_detail.html",
stock_name=stock_name,
stock_symbol=stock_symbol,
stock_price=stock_price,
stock_change=stock_change,
stock_change_pct=stock_change_pct,
prev_close=prev_close,
open=open,
day_range=day_range,
year_range=year_range,
volume=volume,
avg_volume=avg_volume,
market_cap=market_cap,
pe_ratio=pe_ratio,
eps=eps,
dividend=dividend,
dividend_yld=dividend_yld,
dividend_ex_date=dividend_ex_date,
yr_target=yr_target,
close_history=close_history)
) 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( ) print "get_percent_change_from_50_day_moving_average:", tesla.get_percent_change_from_50_day_moving_average( ) print "get_change_from_50_day_moving_average:", tesla.get_change_from_50_day_moving_average( ) print "get_EPS_estimate_next_quarter:", tesla.get_EPS_estimate_next_quarter() print "get_EPS_estimate_next_year:", tesla.get_EPS_estimate_next_year() print "get_ex_dividend_date:", tesla.get_ex_dividend_date() print "get_EPS_estimate_current_year:", tesla.get_EPS_estimate_current_year() print "get_price_EPS_estimate_next_year:", tesla.get_price_EPS_estimate_next_year( ) print "get_price_EPS_estimate_current_year:", tesla.get_price_EPS_estimate_current_year( ) print "get_one_yr_target_price:", tesla.get_one_yr_target_price() print "get_change_percent_change:", tesla.get_change_percent_change() print "get_dividend_pay_date:", tesla.get_dividend_pay_date() print "get_currency:", tesla.get_currency() print "get_last_trade_with_time:", tesla.get_last_trade_with_time() print "get_days_range:", tesla.get_days_range() print "get_year_range:", tesla.get_year_range() # http://stackoverflow.com/questions/24233385/pulling-yahoo-finance-data-using-python # http://chartapi.finance.yahoo.com/instrument/1.0/TSLA/chartdata;type=quote;range=1y/csv
