def init():
'''
Populates investment portfolio with universe, benchmark(s), and current portfolio(s).
Also populates variables needed for the drop-downs like what attributes to consider.
'''
#configure instrument universe - the total set of instruments to be considered in the analysis.
instrumentUniverse,iu_holdings = initialize.universe_from_csv()
res = investmentportfolio.Create_Portfolio(instrumentUniverse)
#add initial set of holdings to instrument universe
res = investmentportfolio.Create_Portfolio_Holdings('instrument_universe',iu_holdings)
#configure benchmark portfolios
benchmarks = initialize.benchmarks_from_csv()
for b in benchmarks:
res = investmentportfolio.Create_Portfolio(b[0])
#add initial set of holdings to benchmark
res = investmentportfolio.Create_Portfolio_Holdings(b[0]['name'],b[1])
#configure initial portfolio
my_portfolio,mp_holdings = initialize.portfolio_from_csv()
res = investmentportfolio.Create_Portfolio(my_portfolio)
#add initial set of holdings to my portfolio
res = investmentportfolio.Create_Portfolio_Holdings(my_portfolio['name'],mp_holdings)
return Response(json.dumps(res), mimetype='application/json')
def portfolio_from_csv():
"""
Loads a portfolio in Algo Risk Service (ARS) format into the Investment Portfolio service.
"""
holdings = {
'timestamp':'{:%Y-%m-%dT%H:%M:%S.%fZ}'.format(datetime.datetime.now()),
'holdings':[]
}
data = json.loads(request.data)
data = [row.split(',') for row in data]
headers = data[0]
#Loop through and segregate each portfolio by its identifier (there may be multiple in the file)
#Column 1 (not 0) is the ID column. Column 5 is the PORTFOLIO column...
portfolios = {}
unique_id_col = headers.index("UNIQUE ID")
id_type_col = headers.index("ID TYPE")
name_col = headers.index("NAME")
pos_units_col = headers.index("POSITION UNITS")
portfolio_col = headers.index("PORTFOLIO")
price_col = headers.index("PRICE")
currency_col = headers.index("CURRENCY")
#for d in data...
for d in data[1:]:
hldg = {
"name":d[name_col],
"instrumentId":d[unique_id_col],
"quantity":d[pos_units_col]
}
if len(headers)>5:
for meta in headers[6:]:
hldg[meta.replace('\r','')] = d[headers.index(meta)].replace('\r','')
if d[portfolio_col] not in portfolios:
portfolios[d[portfolio_col]] = [hldg]
else:
portfolios[d[5]].append(hldg)
#Send each portfolio and its holdings to the investment portfolio service
for key, value in portfolios.items():
my_portfolio = {
"timestamp": '{:%Y-%m-%dT%H:%M:%S.%fZ}'.format(datetime.datetime.now()) ,
'closed':False,
'data':{'type':'unit test portfolio'},
'name':key
}
#create portfolio
try:
req = investmentportfolio.Create_Portfolio(my_portfolio)
except:
print("Unable to create portfolio for " + str(key) + ".")
try:
for h in range(0,len(value),500):
hldgs = value[h:h+500]
req = investmentportfolio.Create_Portfolio_Holdings(str(key),hldgs)
except:
print("Unable to create portfolio holdings for " + str(key) + ".")
return req