chore: import upstream snapshot with attribution

Algorithm.Python/CustomOptionAssignmentRegressionAlgorithm.py

@@ -0,0 +1,40 @@
+# 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 *
+from OptionAssignmentRegressionAlgorithm import *
+
+### <summary>
+### Regression algorithm asserting we can specify a custom option assignment
+### </summary>
+class CustomOptionAssignmentRegressionAlgorithm(OptionAssignmentRegressionAlgorithm):
+    def initialize(self):
+        self.set_security_initializer(self.custom_security_initializer)
+        super().initialize()
+
+    def custom_security_initializer(self, security):
+        if Extensions.is_option(security.symbol.security_type):
+            # we have to be 10% in the money to get assigned
+            security.set_option_assignment_model(PyCustomOptionAssignmentModel(0.1))
+
+    def on_data(self, data):
+        super().on_data(data)
+
+class PyCustomOptionAssignmentModel(DefaultOptionAssignmentModel):
+    def __init__(self, required_in_the_money_percent):
+        super().__init__(required_in_the_money_percent)
+
+    def get_assignment(self, parameters):
+        result = super().get_assignment(parameters)
+        result.tag = "Custom Option Assignment"
+        return result