# 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>
### Live Trading Functionality Demonstration algorithm including SMS, Email and Web hook notifications.
### </summary>
### <meta name="tag" content="live trading" />
### <meta name="tag" content="alerts" />
### <meta name="tag" content="sms alerts" />
### <meta name="tag" content="web hooks" />
### <meta name="tag" content="email alerts" />
### <meta name="tag" content="runtime statistics" />

class LiveTradingFeaturesAlgorithm(QCAlgorithm):

 ### Initialize the Algorithm and Prepare Required Data
 def initialize(self):

 self.set_start_date(2013, 10, 7)
 self.set_end_date(2013, 10, 11)
 self.set_cash(25000)

 ##Equity Data for US Markets
 self.add_security(SecurityType.EQUITY, 'IBM', Resolution.SECOND)

 ##FOREX Data for Weekends: 24/6
 self.add_security(SecurityType.FOREX, 'EURUSD', Resolution.MINUTE)

 ##Custom/Bitcoin Live Data: 24/7
 self.add_data(Bitcoin, 'BTC', Resolution.SECOND, TimeZones.UTC)

 ##if the algorithm is connected to the brokerage
 self.is_connected = True

 ### Raises the data event
 def on_data(self, data):
 if (not self.portfolio['IBM'].hold_stock) and data.contains_key('IBM'):
 quantity = int(np.floor(self.portfolio.margin_remaining / data['IBM'].close))
 self.market_order('IBM',quantity)
 self.debug('Purchased IBM on ' + str(self.time.strftime("%m/%d/%Y")))
 self.notify.email("myemail@gmail.com", "Test", "Test Body", "test attachment")

 if "BTC" in data:
 btcData = data['BTC']
 if self.live_mode:
 self.set_runtime_statistic('BTC', str(btcData.close))

 if not self.portfolio.hold_stock:
 self.market_order('BTC', 100)

 ##Send a notification email/SMS/web request on events:
 self.notify.email("myemail@gmail.com", "Test", "Test Body", "test attachment")
 self.notify.sms("+11233456789", str(btcData.time) + ">> Test message from live BTC server.")
 self.notify.web("http://api.quantconnect.com", str(btcData.time) + ">> Test data packet posted from live BTC server.")
 self.notify.ftp("ftp.quantconnect.com", "username", "password", "path/to/file.txt",
 str(btcData.time) + ">> Test file from live BTC server.")
 self.notify.sftp("ftp.quantconnect.com", "username", "password", "path/to/file.txt",
 str(btcData.time) + ">> Test file from live BTC server.")
 self.notify.sftp("ftp.quantconnect.com", "username", "privatekey", "optionalprivatekeypassphrase", "path/to/file.txt",
 str(btcData.time) + ">> Test file from live BTC server.")

 # Brokerage message event handler. This method is called for all types of brokerage messages.
 def on_brokerage_message(self, message_event):
 self.debug(f"Brokerage meesage received - {message_event.to_string()}")

 # Brokerage disconnected event handler. This method is called when the brokerage connection is lost.
 def on_brokerage_disconnect(self):
 self.is_connected = False
 self.debug(f"Brokerage disconnected!")

 # Brokerage reconnected event handler. This method is called when the brokerage connection is restored after a disconnection.
 def on_brokerage_reconnect(self):
 self.is_connected = True
 self.debug(f"Brokerage reconnected!")

###Custom Data Type: Bitcoin data from Quandl - http://www.quandl.com/help/api-for-bitcoin-data
class Bitcoin(PythonData):

 def get_source(self, config, date, is_live_mode):
 if is_live_mode:
 return SubscriptionDataSource("https://www.bitstamp.net/api/ticker/", SubscriptionTransportMedium.REST)

 return SubscriptionDataSource("https://www.quandl.com/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc", SubscriptionTransportMedium.REMOTE_FILE)


 def reader(self, config, line, date, is_live_mode):
 coin = Bitcoin()
 coin.symbol = config.symbol

 if is_live_mode:
 # Example Line Format:
 # {"high": "441.00", "last": "421.86", "timestamp": "1411606877", "bid": "421.96", "vwap": "428.58", "volume": "14120.40683975", "low": "418.83", "ask": "421.99"}
 try:
 live_btc = json.loads(line)

 # If value is zero, return None
 value = live_btc["last"]
 if value == 0: return None

 coin.time = datetime.now()
 coin.value = value
 coin["Open"] = float(live_btc["open"])
 coin["High"] = float(live_btc["high"])
 coin["Low"] = float(live_btc["low"])
 coin["Close"] = float(live_btc["last"])
 coin["Ask"] = float(live_btc["ask"])
 coin["Bid"] = float(live_btc["bid"])
 coin["VolumeBTC"] = float(live_btc["volume"])
 coin["WeightedPrice"] = float(live_btc["vwap"])
 return coin
 except ValueError:
 # Do nothing, possible error in json decoding
 return None

 # Example Line Format:
 # Date Open High Low Close Volume (BTC) Volume (Currency) Weighted Price
 # 2011年09月13日 5.8 6.0 5.65 5.97 58.37138238, 346.0973893944 5.929230648356
 if not (line.strip() and line[0].isdigit()): return None

 try:
 data = line.split(',')
 coin.time = datetime.strptime(data[0], "%Y-%m-%d")
 coin.value = float(data[4])
 coin["Open"] = float(data[1])
 coin["High"] = float(data[2])
 coin["Low"] = float(data[3])
 coin["Close"] = float(data[4])
 coin["VolumeBTC"] = float(data[5])
 coin["VolumeUSD"] = float(data[6])
 coin["WeightedPrice"] = float(data[7])
 return coin

 except ValueError:
 # Do nothing, possible error in json decoding
 return None