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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.
*/
using Python.Runtime;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using System;
using System.Collections.Generic;
namespace QuantConnect.Algorithm.Framework.Alphas
{
/// <summary>
/// Provides an implementation of <see cref="IAlphaModel"/> that wraps a <see cref="PyObject"/> object
/// </summary>
public class AlphaModelPythonWrapper : IAlphaModel
{
private readonly dynamic _model;
/// <summary>
/// Constructor for initialising the <see cref="IAlphaModel"/> class with wrapped <see cref="PyObject"/> object
/// </summary>
/// <param name="model">>Model that generates alpha</param>
public AlphaModelPythonWrapper(PyObject model)
{
using (Py.GIL())
{
foreach (var attributeName in new[] { "Update", "OnSecuritiesChanged" })
{
if (!model.HasAttr(attributeName))
{
throw new NotImplementedException($"IAlphaModel.{attributeName} must be implemented. Please implement this missing method on {model.GetPythonType()}");
}
}
}
_model = model;
}
/// <summary>
/// Updates this alpha model with the latest data from the algorithm.
/// This is called each time the algorithm receives data for subscribed securities
/// </summary>
/// <param name="algorithm">The algorithm instance</param>
/// <param name="data">The new data available</param>
/// <returns>The new insights generated</returns>
public IEnumerable<Insight> Update(QCAlgorithmFramework algorithm, Slice data)
{
using (Py.GIL())
{
var insights = _model.Update(algorithm, data) as PyObject;
foreach (PyObject insight in insights)
{
yield return insight.AsManagedObject(typeof(Insight)) as Insight;
}
}
}
/// <summary>
/// Event fired each time the we add/remove securities from the data feed
/// </summary>
/// <param name="algorithm">The algorithm instance that experienced the change in securities</param>
/// <param name="changes">The security additions and removals from the algorithm</param>
public void OnSecuritiesChanged(QCAlgorithmFramework algorithm, SecurityChanges changes)
{
using (Py.GIL())
{
_model.OnSecuritiesChanged(algorithm, changes);
}
}
}
}