Files
quantconnect--lean/Algorithm.Python/CustomDataPropertiesRegressionAlgorithm.py
T
Louis Szeto c2ad893f32 pep8 conversion of python algos #5 (#7943)
* pep8 conversion

* Fix: detect python object of python classes derived from c# classes

* Minor PEP8 updates/fixes

---------

Co-authored-by: Jhonathan Abreu <jdabreu25@gmail.com>
2024-04-18 15:53:32 -03:00

127 lines
5.8 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 AlgorithmImports import *
### <summary>
### Regression test to demonstrate setting custom Symbol Properties and Market Hours for a custom data import
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="importing data" />
### <meta name="tag" content="custom data" />
### <meta name="tag" content="crypto" />
### <meta name="tag" content="regression test" />
class CustomDataPropertiesRegressionAlgorithm(QCAlgorithm):
def initialize(self):
self.set_start_date(2011,9,13) # Set Start Date
self.set_end_date(2015,12,1) # Set End Date
self.set_cash(100000) # Set Strategy Cash
# Define our custom data properties and exchange hours
self.ticker = 'BTC'
properties = SymbolProperties("Bitcoin", "USD", 1, 0.01, 0.01, self.ticker)
exchange_hours = SecurityExchangeHours.always_open(TimeZones.NEW_YORK)
# Add the custom data to our algorithm with our custom properties and exchange hours
self.bitcoin = self.add_data(Bitcoin, self.ticker, properties, exchange_hours)
# Verify our symbol properties were changed and loaded into this security
if self.bitcoin.symbol_properties != properties :
raise Exception("Failed to set and retrieve custom SymbolProperties for BTC")
# Verify our exchange hours were changed and loaded into this security
if self.bitcoin.exchange.hours != exchange_hours :
raise Exception("Failed to set and retrieve custom ExchangeHours for BTC")
# For regression purposes on AddData overloads, this call is simply to ensure Lean can accept this
# with default params and is not routed to a breaking function.
self.add_data(Bitcoin, "BTCUSD")
def on_data(self, data):
if not self.portfolio.invested:
if data['BTC'].close != 0 :
self.order('BTC', self.portfolio.margin_remaining/abs(data['BTC'].close + 1))
def on_end_of_algorithm(self):
#Reset our Symbol property value, for testing purposes.
self.symbol_properties_database.set_entry(Market.USA, self.market_hours_database.get_database_symbol_key(self.bitcoin.symbol), SecurityType.BASE,
SymbolProperties.get_default("USD"))
class Bitcoin(PythonData):
'''Custom Data Type: Bitcoin data from Quandl - http://www.quandl.com/help/api-for-bitcoin-data'''
def get_source(self, config, date, is_live_mode):
if is_live_mode:
return SubscriptionDataSource("https://www.bitstamp.net/api/ticker/", SubscriptionTransportMedium.REST)
#return "http://my-ftp-server.com/futures-data-" + date.to_string("Ymd") + ".zip"
# OR simply return a fixed small data file. Large files will slow down your backtest
return SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc&api_key=WyAazVXnq7ATy_fefTqm", 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
# 2011-09-13 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.end_time = coin.time + timedelta(days=1)
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