# 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 AlgorithmImports import *

### <summary>

### Algorithm demonstrating FOREX asset types and requesting history on them in bulk. As FOREX uses

### QuoteBars you should request slices

### </summary>

### <meta name="tag" content="using data" />

### <meta name="tag" content="history and warm up" />

### <meta name="tag" content="history" />

### <meta name="tag" content="forex" />

class BasicTemplateForexAlgorithm(QCAlgorithm):

def initialize(self):

# Set the cash we'd like to use for our backtest

self.set_cash(100000)

# Start and end dates for the backtest.

self.set_start_date(2013, 10, 7)

self.set_end_date(2013, 10, 11)

# Add FOREX contract you want to trade

# find available contracts here https://www.quantconnect.com/data#forex/oanda/cfd

self.add_forex("EURUSD", Resolution.MINUTE)

self.add_forex("GBPUSD", Resolution.MINUTE)

self.add_forex("EURGBP", Resolution.MINUTE)

self.history(5, Resolution.DAILY)

self.history(5, Resolution.HOUR)

self.history(5, Resolution.MINUTE)

history = self.history(TimeSpan.from_seconds(5), Resolution.SECOND)

for data in sorted(history, key=lambda x: x.time):

for key in data.keys():

self.log(str(key.value) + ": " + str(data.time) + " > " + str(data[key].value))

def on_data(self, data):

# Print to console to verify that data is coming in

for key in data.keys():

self.log(str(key.value) + ": " + str(data.time) + " > " + str(data[key].value))