# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.

# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

from datetime import datetime

from csv import reader

from urllib import urlopen

from clr import AddReference

AddReference("System.Core")

AddReference("QuantConnect.Common")

AddReference("QuantConnect.Algorithm")

from System import *

from QuantConnect import *

from QuantConnect.Algorithm import *

from QuantConnect.Data.UniverseSelection import *

class DropboxUniverseSelectionAlgorithm(QCAlgorithm):

'''In this algortihm we show how you can easily use the universe selection feature to fetch symbols

to be traded using the AddUniverse method. This method accepts a function that will return the

desired current set of symbols. Return Universe.Unchanged if no universe changes should be made'''

def __init__(self):

# the changes from the previous universe selection

self.__changes = SecurityChanges.None

# only used in backtest for caching the file results

self.__backtestSymbolsPerDay = {}

def CoarseSelectionFunction(self, dateTime):

url = "https://www.dropbox.com/s/2az14r5xbx4w5j6/daily-stock-picker-live.csv?dl=1" \

if self.LiveMode else \

"https://www.dropbox.com/s/rmiiktz0ntpff3a/daily-stock-picker-backtest.csv?dl=1"

# handle live mode file format

if self.LiveMode:

# fetch the file from dropbox

file = urlopen(url).read()

# if we have a file for today, break apart by commas and return symbols

if len(file) > 0: return file.ToCsv()

# no symbol today, leave universe unchanged

return self.Universe.Unchanged

# backtest - first cache the entire file

if len(self.__backtestSymbolsPerDay) == 0:

# fetch the file from dropbox only if we haven't cached the result already

file = reader(urlopen(url))

for line in file:

date = datetime.strptime(line[0], '%Y%m%d')

self.__backtestSymbolsPerDay[date] = line[1:]

# if we have symbols for this date return them, else specify Universe.Unchanged

return self.__backtestSymbolsPerDay.get(datetime(dateTime), self.Universe.Unchanged)

def Initialize(self):

'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''

self.SetStartDate(2013,01,01) #Set Start Date

self.SetEndDate(2013,12,31) #Set End Date

# this sets the resolution for data subscriptions added by our universe

self.UniverseSettings.Resolution = Resolution.Daily

self.AddUniverse("my-dropbox-universe", Resolution.Daily, self.CoarseSelectionFunction)

def OnData(self, data):

'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.

Arguments:

data: Slice object keyed by symbol containing the stock data

'''

if len(data.Bars) == 0: return

if self.__changes == SecurityChanges.None: return

# start fresh

self.Liquidate()

percentage = 1./len(data.Bars)

for tradeBar in data.Bars.Values:

self.SetHoldings(tradeBar.Symbol, percentage)

# reset changes

self.__changes = SecurityChanges.None

def OnSecuritiesChanged(self, changes):

'''Event fired each time the we add/remove securities from the data feed'''

# each time our securities change we'll be notified here

self.__changes = changes