quantconnect--lean/Algorithm/Alphas/AlphaModelPythonWrapper.cs

/*
 * 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;
using QuantConnect.Python;

namespace QuantConnect.Algorithm.Framework.Alphas
{
    /// <summary>
    /// Provides an implementation of <see cref="IAlphaModel"/> that wraps a <see cref="PyObject"/> object
    /// </summary>
    public class AlphaModelPythonWrapper : AlphaModel
    {
        private readonly dynamic _model;

        /// <summary>
        /// Defines a name for a framework model
        /// </summary>
        public override string Name
        {
            get
            {
                using (Py.GIL())
                {
                    // if the model defines a Name property then use that
                    if (_model.HasAttr("Name"))
                    {
                        return (_model.Name as PyObject).GetAndDispose<string>();
                    }

                    // if the model does not define a name property, use the python type name
                    return (_model.__class__.__name__ as PyObject).GetAndDispose<string>();
                }
            }
        }

        /// <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 override IEnumerable<Insight> Update(QCAlgorithm algorithm, Slice data)
        {
            using (Py.GIL())
            {
                var insights = _model.Update(algorithm, new PythonSlice(data)) as PyObject;
                var iterator = insights.GetIterator();
                foreach (PyObject insight in iterator)
                {
                    yield return insight.GetAndDispose<Insight>();
                }
                iterator.Dispose();
                insights.Dispose();
            }
        }

        /// <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 override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
        {
            using (Py.GIL())
            {
                _model.OnSecuritiesChanged(algorithm, changes);
            }
        }
    }
}