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 +1,156 @@
+/*
+ * 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.Globalization;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting that custom data can be sourced from a remote CSV zipped file.
+    /// </summary>
+    public class CustomDataZipFileRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _customDataSymbol;
+        private bool _receivedCustomData;
+
+        public override void Initialize()
+        {
+            SetStartDate(2021, 01, 01);
+            SetEndDate(2021, 12, 31);
+
+            CustomData.Url = GetCustomDataUrl();
+
+            _customDataSymbol = AddData<CustomData>("CustomData", Resolution.Daily).Symbol;
+
+            SetBenchmark(x => 0);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            var data = slice.Get<CustomData>(_customDataSymbol);
+            if (data != null)
+            {
+                Log($"{Time}: {data.Symbol} - {data.Time} - {data.Value}");
+                _receivedCustomData = true;
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (!_receivedCustomData)
+            {
+                throw new RegressionTestException("Custom data was not received");
+            }
+        }
+
+        protected virtual string GetCustomDataUrl()
+        {
+            return @"https://cdn.quantconnect.com/uploads/multi_csv_zipped_file.zip?some=query&for=testing";
+        }
+
+        public class CustomData : BaseData
+        {
+            public static string Url { get; set; }
+
+            public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)
+            {
+                return new SubscriptionDataSource(Url);
+            }
+
+            public override BaseData Reader(SubscriptionDataConfig config, string line, DateTime date, bool isLiveMode)
+            {
+                var csv = line.ToCsv(2);
+
+                try
+                {
+                    return new CustomData()
+                    {
+                        Symbol = config.Symbol,
+                        EndTime = date.Date.AddMilliseconds(Convert.ToInt32(csv[0], CultureInfo.InvariantCulture)).ConvertTo(config.DataTimeZone, config.ExchangeTimeZone),
+                        Value = Convert.ToDecimal(csv[1], CultureInfo.InvariantCulture),
+                    };
+                }
+                catch
+                {
+                    return null;
+                }
+            }
+        }
+
+        /// <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 virtual long DataPoints => 79;
+
+        /// <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", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}