chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
5008 changed files with 910633 additions and 0 deletions
@@ -0,0 +1,154 @@
+/*
+ * 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 System;
+using System.Collections.Generic;
+using System.Linq;
+using NUnit.Framework;
+using Python.Runtime;
+using QuantConnect.Algorithm;
+using QuantConnect.Data.Market;
+using QuantConnect.Data.UniverseSelection;
+using QuantConnect.Securities;
+using QuantConnect.Statistics;
+using QuantConnect.Tests.Engine.DataFeeds;
+
+namespace QuantConnect.Tests.Python
+{
+    [TestFixture]
+    public class PythonOptionTests
+    {
+        [Test]
+        public void PythonFilterFunctionReturnsList()
+        {
+            var algorithm = new QCAlgorithm();
+            algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(algorithm));
+            var spyOption = algorithm.AddOption("SPY");
+
+            using (Py.GIL())
+            {
+                //Filter function that returns a list of symbols
+                var module = PyModule.FromString(Guid.NewGuid().ToString(),
+                    "def filter(universe):\n" +
+                    "   universe = universe.WeeklysOnly().Expiration(0, 10)\n" +
+                    "   return [symbol for symbol in universe\n"+
+                    "           if symbol.ID.OptionRight != OptionRight.Put\n" +
+                    "           and universe.Underlying.Price - symbol.ID.StrikePrice < 10]\n"
+                );
+
+                var filterFunction = module.GetAttr("filter");
+                Assert.DoesNotThrow(() => spyOption.SetFilter(filterFunction));
+            }
+
+
+        }
+
+        [Test]
+        public void PythonFilterFunctionReturnsUniverse()
+        {
+            var algorithm = new QCAlgorithm();
+            algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(algorithm));
+            var spyOption = algorithm.AddOption("SPY");
+
+            using (Py.GIL())
+            {
+                //Filter function that returns a OptionFilterUniverse
+                var module = PyModule.FromString(Guid.NewGuid().ToString(),
+                    "def filter(universe):\n" +
+                    "   universe = universe.WeeklysOnly().Expiration(0, 5)\n" +
+                    "   return universe"
+                );
+
+                var filterFunction = module.GetAttr("filter");
+                Assert.DoesNotThrow(() => spyOption.SetFilter(filterFunction));
+            }
+        }
+
+        [Test]
+        public void PythonFilterFunctionReturnsNone()
+        {
+            var algorithm = new QCAlgorithm();
+            algorithm.SubscriptionManager.SetDataManager(new DataManagerStub(algorithm));
+            var spyOption = algorithm.AddOption("SPY");
+
+            using (Py.GIL())
+            {
+                //Filter function that modifies the universe in place and returns None:
+                //the return value is only necessary for chaining
+                var module = PyModule.FromString(Guid.NewGuid().ToString(),
+                    "def filter(universe):\n" +
+                    "   universe.strikes(-20, 20).expiration(0, 10)\n"
+                );
+
+                var filterFunction = module.GetAttr("filter");
+                spyOption.SetFilter(filterFunction);
+            }
+
+            var underlying = new Tick { Value = 10m, Time = new DateTime(2016, 12, 29) };
+            var symbols = new[]
+            {
+                // within the 0-10 days expiration window
+                Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Call, 10, new DateTime(2017, 01, 04)),
+                Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Put, 10, new DateTime(2017, 01, 06)),
+                // beyond the 0-10 days expiration window
+                Symbol.CreateOption("SPY", Market.USA, OptionStyle.American, OptionRight.Call, 10, new DateTime(2017, 01, 20)),
+            };
+
+            var data = symbols.Select(x => new OptionUniverse() { Symbol = x }).ToList();
+            var filtered = spyOption.ContractFilter.Filter(new OptionFilterUniverse(spyOption, data, underlying)).ToList();
+
+            Assert.AreEqual(2, filtered.Count);
+            Assert.AreEqual(symbols[0], filtered[0].Symbol);
+            Assert.AreEqual(symbols[1], filtered[1].Symbol);
+        }
+
+        [Test]
+        public void FilterReturnsUniverseRegression()
+        {
+            var parameter = new RegressionTests.AlgorithmStatisticsTestParameters("FilterUniverseRegressionAlgorithm",
+                new Dictionary<string, string> {
+                    {PerformanceMetrics.TotalOrders, "2"},
+                    {"Average Win", "0%"},
+                    {"Average Loss", "-0.02%"},
+                    {"Compounding Annual Return", "-1.521%"},
+                    {"Drawdown", "0.000%"},
+                    {"Expectancy", "-1"},
+                    {"End Equity", "99979"},
+                    {"Net Profit", "-0.021%"},
+                    {"Sharpe Ratio", "0"},
+                    {"Probabilistic Sharpe Ratio", "0%"},
+                    {"Loss Rate", "100%"},
+                    {"Win Rate", "0%"},
+                    {"Profit-Loss Ratio", "0"},
+                    {"Alpha", "0"},
+                    {"Beta", "0"},
+                    {"Annual Standard Deviation", "0"},
+                    {"Annual Variance", "0"},
+                    {"Information Ratio", "0"},
+                    {"Tracking Error", "0"},
+                    {"Treynor Ratio", "0"},
+                    {"Total Fees", "$1.00"},
+                    {"OrderListHash", "22f0bc8a92f13dfa5d16c507824e2b68"}
+                    },
+                    Language.Python,
+                    AlgorithmStatus.Completed);
+
+            AlgorithmRunner.RunLocalBacktest(parameter.Algorithm,
+                parameter.Statistics,
+                parameter.Language,
+                parameter.ExpectedFinalStatus);
+        }
+    }
+}