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 +1,167 @@
+/*
+ * 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 QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm which reproduces GH issue 3740.
+    /// We assert the methods are triggered at the correct algorithm time
+    /// </summary>
+    public class TimeRulesDefaultTimeZoneRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private int _scheduleEventEveryCallCount;
+        private int _scheduleEventNoonCallCount;
+        private int _scheduleEventMidnightCallCount;
+        private int _selectionMethodCallCount;
+
+        public override void Initialize()
+        {
+            SetStartDate(2017, 01, 01);
+            SetEndDate(2017, 02, 01);
+
+            SetUniverseSelection(new ScheduledUniverseSelectionModel(
+                DateRules.EveryDay(),
+                TimeRules.At(9, 31),
+                SelectSymbolsAt
+            ));
+
+            Schedule.On(DateRules.EveryDay(), TimeRules.Every(TimeSpan.FromHours(6)), () =>
+            {
+                _scheduleEventEveryCallCount++;
+                if (Time.Hour != 0
+                    && Time.Hour != 6
+                    && Time.Hour != 12
+                    && Time.Hour != 18)
+                {
+                    throw new RegressionTestException($"Unexpected every 6 hours scheduled event time: {Time}");
+                }
+            });
+
+            Schedule.On(DateRules.EveryDay(), TimeRules.Noon, () =>
+            {
+                _scheduleEventNoonCallCount++;
+                if (Time.Hour != 12)
+                {
+                    throw new RegressionTestException($"Unexpected Noon scheduled event time: {Time}");
+                }
+            });
+
+            Schedule.On(DateRules.EveryDay(), TimeRules.Midnight, () =>
+            {
+                _scheduleEventMidnightCallCount++;
+                if (Time.Hour != 0)
+                {
+                    throw new RegressionTestException($"Unexpected Midnight scheduled event time: {Time}");
+                }
+            });
+        }
+
+        private IEnumerable<Symbol> SelectSymbolsAt(DateTime dateTime)
+        {
+            _selectionMethodCallCount++;
+            Log($"SelectSymbolsAt {Time}");
+            if (Time.TimeOfDay != new TimeSpan(9, 31, 0))
+            {
+                throw new RegressionTestException($"Expected 'SelectSymbolsAt' to be called at 9:31 algorithm time: {Time}");
+            }
+            yield break;
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_selectionMethodCallCount != 32)
+            {
+                throw new RegressionTestException($"Unexpected universe selection call count: {_selectionMethodCallCount}");
+            }
+            if (_scheduleEventEveryCallCount != 127)
+            {
+                throw new RegressionTestException($"Unexpected scheduled event call count: {_scheduleEventEveryCallCount}");
+            }
+            if (_scheduleEventNoonCallCount != 32)
+            {
+                throw new RegressionTestException($"Unexpected scheduled event call count: {_scheduleEventNoonCallCount}");
+            }
+            if (_scheduleEventMidnightCallCount != 32)
+            {
+                throw new RegressionTestException($"Unexpected scheduled event call count: {_scheduleEventMidnightCallCount}");
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 186;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
+        /// </summary>
+        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
+        {
+            {"Total Orders", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-3.017"},
+            {"Tracking Error", "0.053"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}