# 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 QuantConnect.Algorithm.CSharp import *

### <summary>
### Regression algorithm asserting we can specify a custom option exercise model
### </summary>
class CustomOptionExerciseModelRegressionAlgorithm(OptionAssignmentRegressionAlgorithm):
    def Initialize(self):
        self.SetSecurityInitializer(self.CustomSecurityInitializer)
        super().Initialize()

    def CustomSecurityInitializer(self, security):
        if Extensions.IsOption(security.Symbol.SecurityType):
            security.SetOptionExerciseModel(CustomExerciseModel())

    def OnData(self, data):
        super().OnData(data)

class CustomExerciseModel(DefaultExerciseModel):
    def OptionExercise(self, option: Option, order: OptionExerciseOrder):
        order_event = OrderEvent(
            order.Id,
            option.Symbol,
            Extensions.ConvertToUtc(option.LocalTime, option.Exchange.TimeZone),
            OrderStatus.Filled,
            Extensions.GetOrderDirection(order.Quantity),
            0.0,
            order.Quantity,
            OrderFee.Zero,
            "Tag"
        )
        order_event.IsAssignment = False
        return [ order_event ]