chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
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+# 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)
+'''