def __init__(self):
self.db = MoneykyDB()
class Moneyky(object):
def __init__(self):
self.db = MoneykyDB()
def portfolio_of_day(self, amount = 30, bench = "SPX"):
'''This function is the one that will run once per day - Important Function'''
companies = self.random_portfolio(amount)
holdings = self.get_holdings_performance(companies)
benchmark = self.get_ticker_performance(bench, True)
output = {
'date' : holdings[0]['today'],
'performance_ytd' : self.average_performance('ytdperformance', holdings),
'performance_1year' : self.average_performance('1yearperformance', holdings),
'benchmark_ytd' : benchmark['ytdperformance'],
'benchmark_1year' : benchmark['1yearperformance'],
'holdings' : holdings
}
self.portfolio = output
self.save()
return output
def get_holdings_performance(self, holdings = []):
''' creates a list of holdings with their associated performance (Data from http://dev.markitondemand.com) '''
tickerlist = [company[1] for company in holdings if not company == None]
data = []
for ticker in tickerlist:
data.append(self.get_ticker_performance(ticker))
return data
def get_ticker_performance(self, ticker, index = False):
''' helper function to get a single stock's performance from Yahoo Finance'''
### Construct API Call ###
url = "http://www.bloomberg.com/markets/chart/data/1Y/" + ticker
if index or ticker == 'SPX':
url += ":IND"
else:
url += ":US"
response = requests.get(url)
result = response.json()
# For testing
# response = open('../sample-historical-data.json', 'r')
# result = json.load(response)
prices = result['data_values']
if prices:
closingdate = self.timestamp_to_date(prices[-1][0])
ytdindex = self.find_index_of_date(prices, closingdate, 'ytd')
yearindex = self.find_index_of_date(prices, closingdate, 'year')
return {
'ticker' : ticker,
'today' : self.timestamp_to_date(prices[-1][0], True),
'close' : prices[-1][1],
'1year' : self.timestamp_to_date(prices[yearindex][0], True),
'1yearprice' : prices[yearindex][1],
'1yearperformance' : self.percent_growth(prices[yearindex][1], prices[-1][1]),
'ytd' : self.timestamp_to_date(prices[ytdindex][0], True),
'ytdprice' : prices[ytdindex][1],
'ytdperformance' : self.percent_growth(prices[ytdindex][1], prices[-1][1])
}
def seeddb(self, amount = 30):
''' runs once if there are no companies in the snp_companies file '''
output = self.db.seed_companies("/var/www/moneyky/spx-companies.json")
# output += self.portfolio_of_day(amount)
return output
def random_portfolio(self, amount = 10):
return self.db.get_random_companies(amount)
def save(self):
''' Save everything to the database after we're happy with it '''
if (self.portfolio):
self.db.set_portfolio(self.portfolio)
def get_portfolio(self, id = None):
portfolio = self.db.get_portfolio_and_companies(id)
if portfolio:
return portfolio
else:
return
def get_company(self, ticker):
return self.db.get_company_by_ticker(ticker)
def chart_results(self):
portfolios = self.db.get_all_portfolios()
portfolio_results = {
'portfolios': portfolios,
'overview' : {
'ytd' : self.average_performance('difference_ytd', portfolios),
'1year' : self.average_performance('difference_1year', portfolios)
}
}
portfolio_results['overview']['results_ytd'] = self.outperform(portfolio_results['overview']['ytd'])
portfolio_results['overview']['results_1year'] = self.outperform(portfolio_results['overview']['1year'])
num_points = len(portfolios)
pprint(num_points)
now = time.time()
dates =[]
moneyky_perf=[]
portfolio_perf=[]
#Form the lists
for each in portfolios:
dates.append(each['date'])
moneyky_perf.append(float(each['difference_ytd']))
portfolio_perf.append(float(each['difference_1year']))
TOOLS = "reset,save"
r = figure(x_axis_type = "datetime", tools=TOOLS, plot_width=800, plot_height=400)
r.line(dates, portfolio_perf, legend='Monkey ytd', color="firebrick", alpha=0.8, line_width=4)
r.line(dates, moneyky_perf, legend='Monkey 1 Year', color="navy", alpha=0.8, line_width=4)
r.title = "Moneyky vs Benchmark Performance"
r.grid.grid_line_alpha=100
return (vplot(r)), portfolio_results # return the plot
### ##########################################################
### Helper Functions ###
def outperform(self, difference):
if difference > 0:
return "outperform"
elif difference == 0:
return "inline"
else:
return "underperform"
def find_index_of_date(self, dates = [], closingdate = "", date = 'ytd'):
'''The first day of trading isn't always January 1st, so this finds the index first day of trading'''
if not closingdate:
closingdate = datetime.now()
Datetofind = None
if (date == 'ytd'):
Datetofind = datetime(closingdate.year, 1, 1)
else:
Datetofind = datetime(closingdate.year - 1, closingdate.month, closingdate.day)
utcDatetofind = self.date_to_timestamp(Datetofind)
count = 0
for time, price in dates:
if utcDatetofind <= time:
return count
count += 1
return
def average_performance(self, columnname = '1yearperformance', holdings = [] ):
allperformances = [stock[columnname] for stock in holdings if not stock == None]
return round(sum(allperformances) / len(allperformances), 2)
def percent_growth(self, originalprice = 0, currentprice = 0):
''' Return the Percent Change '''
dif = currentprice - originalprice
return round((dif / originalprice) * 100, 2)
def timestamp_to_date(self, timestamp, string = False):
''' timestamps are in milliseconds so divide by 1000 '''
time = datetime.fromtimestamp(timestamp/1000)
if string:
return time.strftime("%Y-%m-%d %H:%M:%S")
return time
def date_to_timestamp(self, date):
''' takes datetime object and returns unix timestamp '''
return int(time.mktime(date.timetuple()) * 1000)
