Files
quantconnect--lean/Algorithm.Python/DropboxBaseDataUniverseSelectionAlgorithm.py
T
Michael Handschuh 18a559943e Upgrade LEAN Python to 3.6 from 2.7
- Adds log to display the python version the algorithm is using.
- Fixes python algorithms that were failing because of small subtleties
like leading zeroes.
- Updates pythonnet with a version compiled with python 3.6 flags

- Changes in DockerfileFoundation: we now use miniconda to manage the python
environment.
- Took the opportunity to add NTLK (#1349), Tensorforce (#1369) and
PyTorch/Pyro (#1385).
- Changes readme in Algorithm.Python to show steps to install miniconda
2018-02-23 15:09:06 -05:00

98 lines
3.5 KiB
Python

# 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 clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Data import SubscriptionDataSource
from QuantConnect.Python import PythonData
from datetime import date, timedelta, datetime
from System.Collections.Generic import List
from QuantConnect.Algorithm import QCAlgorithm
from QuantConnect.Data.UniverseSelection import *
import decimal as d
import numpy as np
import math
import json
### <summary>
### In this algortihm we show how you can easily use the universe selection feature to fetch symbols
### to be traded using the BaseData custom data system in combination with the AddUniverse{T} method.
### AddUniverse{T} requires a function that will return the symbols to be traded.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="universes" />
### <meta name="tag" content="custom universes" />
class DropboxBaseDataUniverseSelectionAlgorithm(QCAlgorithm):
def Initialize(self):
self.UniverseSettings.Resolution = Resolution.Daily;
self.SetStartDate(2013,1,1)
self.SetEndDate(2013,12,31)
self.AddUniverse(StockDataSource, "my-stock-data-source", self.stockDataSource)
def stockDataSource(self, data):
list = []
for item in data:
for symbol in item["Symbols"]:
list.append(symbol)
return list
def OnData(self, slice):
if slice.Bars.Count == 0: return
if self._changes == None: return
# start fresh
self.Liquidate()
percentage = 1 / d.Decimal(slice.Bars.Count)
for tradeBar in slice.Bars.Values:
self.SetHoldings(tradeBar.Symbol, percentage)
# reset changes
self._changes = None
def OnSecuritiesChanged(self, changes):
self._changes = changes
class StockDataSource(PythonData):
def GetSource(self, config, date, isLiveMode):
url = "https://www.dropbox.com/s/2az14r5xbx4w5j6/daily-stock-picker-live.csv?dl=1" if isLiveMode else \
"https://www.dropbox.com/s/rmiiktz0ntpff3a/daily-stock-picker-backtest.csv?dl=1"
return SubscriptionDataSource(url, SubscriptionTransportMedium.RemoteFile)
def Reader(self, config, line, date, isLiveMode):
if not (line.strip() and line[0].isdigit()): return None
stocks = StockDataSource()
stocks.Symbol = config.Symbol
csv = line.split(',')
if isLiveMode:
stocks.Time = date
stocks["Symbols"] = csv
else:
stocks.Time = datetime.strptime(csv[0], "%Y%m%d")
stocks["Symbols"] = csv[1:]
return stocks