/*
 * 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.Python;
using QuantConnect.Securities.Interfaces;

namespace QuantConnect.Securities
{
    /// <summary>
    /// Python Wrapper for custom security data filters from Python
    /// </summary>
    public class SecurityDataFilterPythonWrapper : BasePythonWrapper<ISecurityDataFilter>, ISecurityDataFilter
    {
        /// <summary>
        /// Creates a new instance
        /// </summary>
        /// <param name="dataFilter">The Python class to wrapp</param>
        public SecurityDataFilterPythonWrapper(PyObject dataFilter)
            : base(dataFilter)
        {
        }

        /// <summary>
        /// Performs Filter method from Python instance returning true to accept, or false to fail/reject the data point.
        /// </summary>
        /// <param name="data">BasData data object we're filtering</param>
        /// <param name="vehicle">Security vehicle for filter</param>
        public bool Filter(Security vehicle, BaseData data)
        {
            return InvokeMethod<bool>(nameof(Filter), vehicle, data);
        }
    }
}