wehub-resource-sync
78 lines
3.2 KiB
Python
78 lines
3.2 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>
|
|
### his algorithm sends a list of portfolio targets to custom endpoint
|
|
### </summary>
|
|
### <meta name="tag" content="using data" />
|
|
### <meta name="tag" content="using quantconnect" />
|
|
### <meta name="tag" content="securities and portfolio" />
|
|
class CustomSignalExportDemonstrationAlgorithm(QCAlgorithm):
|
|
|
|
def initialize(self) -> None:
|
|
''' Initialize the date and add all equity symbols present in list _symbols '''
|
|
|
|
self.set_start_date(2013, 10, 7) #Set Start Date
|
|
self.set_end_date(2013, 10, 11) #Set End Date
|
|
self.set_cash(100000) #Set Strategy Cash
|
|
|
|
# Our custom signal export accepts all asset types
|
|
self.add_equity("SPY", Resolution.SECOND)
|
|
self.add_crypto("BTCUSD", Resolution.SECOND)
|
|
self.add_forex("EURUSD", Resolution.SECOND)
|
|
self.add_future_contract(Symbol.create_future("ES", Market.CME, datetime(2023, 12, 15)))
|
|
self.add_option_contract(Symbol.create_option("SPY", Market.USA, OptionStyle.AMERICAN, OptionRight.CALL, 130, datetime(2023, 9, 1)))
|
|
|
|
# Set CustomSignalExport signal export provider.
|
|
self.signal_export.add_signal_export_provider(CustomSignalExport())
|
|
|
|
def on_data(self, data: Slice) -> None:
|
|
'''Buy and hold EURUSD and SPY'''
|
|
for ticker in [ "SPY", "EURUSD", "BTCUSD" ]:
|
|
if not self.portfolio[ticker].invested and self.securities[ticker].has_data:
|
|
self.set_holdings(ticker, 0.5)
|
|
|
|
from requests import post
|
|
class CustomSignalExport:
|
|
def send(self, parameters: SignalExportTargetParameters) -> bool:
|
|
targets = [PortfolioTarget.percent(parameters.algorithm, x.symbol, x.quantity)
|
|
for x in parameters.targets]
|
|
data = [ {'symbol' : x.symbol.value, 'quantity': x.quantity} for x in targets ]
|
|
response = post("http://localhost:5000/", json = data)
|
|
result = response.json()
|
|
success = result.get('success', False)
|
|
parameters.algorithm.log(f"Send #{len(parameters.targets)} targets. Success: {success}")
|
|
return success
|
|
|
|
def dispose(self):
|
|
pass
|
|
|
|
'''
|
|
# To test the algorithm, you can create a simple Python Flask application (app.py) and run flask
|
|
# $ flask --app app run
|
|
|
|
# app.py:
|
|
from flask import Flask, request, jsonify
|
|
from json import loads
|
|
app = Flask(__name__)
|
|
@app.post('/')
|
|
def handle_positions():
|
|
result = loads(request.data)
|
|
print(result)
|
|
return jsonify({'success': True,'message': f'{len(result)} positions received'})
|
|
if __name__ == '__main__':
|
|
app.run(debug=True)
|
|
'''
|