Address reviews

- Keep old QB.Indicator methods for backwards compatibility
- Rename new API to IndicatorHistory, matching
  FutureHistory/OptionHistory
- Add new regression algorithms
- Minor improvement to DynamicData so it supports snake name access

Algorithm.CSharp/IndicatorHistoryRegressionAlgorithm.cs

@@ -0,0 +1,149 @@
+/*
+ * 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.Collections.Generic;
+using System.Linq;
+using QuantConnect.Data;
+using QuantConnect.Indicators;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression algorithm asserting the behavior of the indicator history api
+    /// </summary>
+    public class IndicatorHistoryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _symbol;
+
+        /// <summary>
+        /// Initialize the data and resolution you require for your strategy
+        /// </summary>
+        public override void Initialize()
+        {
+            SetStartDate(2013, 1, 1);
+            SetEndDate(2014, 12, 31);
+
+            _symbol = AddEquity("SPY", Resolution.Daily).Symbol;
+        }
+
+        public void OnData(Slice slice)
+        {
+            var bollingerBands = new BollingerBands("BB", 20, 2.0m, MovingAverageType.Simple);
+
+            if (bollingerBands.Window.IsReady)
+            {
+                throw new RegressionTestException("Unexpected ready bollinger bands state");
+            }
+
+            var indicatorHistory = IndicatorHistory(bollingerBands, _symbol, 50);
+
+            if (!bollingerBands.Window.IsReady)
+            {
+                throw new RegressionTestException("Unexpected not ready bollinger bands state");
+            }
+
+            // we ask for 50 data points
+            if (indicatorHistory.Count != 50)
+            {
+                throw new RegressionTestException($"Unexpected indicators values {indicatorHistory.Count}");
+            }
+
+            foreach (var indicatorDataPoints in indicatorHistory)
+            {
+                var upperBand = ((dynamic)indicatorDataPoints).UpperBand;
+                Debug($"BB @{indicatorDataPoints.Current}: middleband: {indicatorDataPoints["middleband"]} upperBand {upperBand}");
+
+                if (indicatorDataPoints == 0)
+                {
+                    throw new RegressionTestException($"Unexpected indicators point {indicatorDataPoints}");
+                }
+            }
+
+            var currentValues = indicatorHistory.Current;
+            if (currentValues.Count != 50 || currentValues.Any(x => x.Value == 0))
+            {
+                throw new RegressionTestException($"Unexpected indicators current values {currentValues.Count}");
+            }
+            var upperBandPoints = indicatorHistory["UpperBand"];
+            if (upperBandPoints.Count != 50 || upperBandPoints.Any(x => x.Value == 0))
+            {
+                throw new RegressionTestException($"Unexpected indicators upperBandPoints values {upperBandPoints.Count}");
+            }
+
+            // We are done now!
+            Quit();
+        }
+
+        /// <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, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 9;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 70;
+
+        /// <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%"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}

Algorithm.Python/IndicatorHistoryRegressionAlgorithm.py

@@ -0,0 +1,62 @@
+# 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.
+
+from AlgorithmImports import *
+
+### <summary>
+### Regression algorithm asserting the behavior of the indicator history api
+### </summary>
+class IndicatorHistoryRegressionAlgorithm(QCAlgorithm):
+    '''Regression algorithm asserting the behavior of the indicator history api'''
+
+    def initialize(self):
+        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
+        self.set_start_date(2013, 1, 1)
+        self.set_end_date(2014, 12, 31)
+
+        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
+
+    def on_data(self, slice: Slice):
+        self.bollinger_bands = BollingerBands("BB", 20, 2.0, MovingAverageType.SIMPLE)
+
+        if self.bollinger_bands.window.is_ready:
+            raise ValueError("Unexpected ready bollinger bands state")
+
+        indicatorHistory = self.indicator_history(self.bollinger_bands, self._symbol, 50)
+
+        self.debug(f"indicatorHistory: {indicatorHistory}")
+
+        self.debug(f"data_frame: {indicatorHistory.data_frame}")
+
+        if not self.bollinger_bands.window.is_ready:
+            raise ValueError("Unexpected not ready bollinger bands state")
+
+        # we ask for 50 data points
+        if indicatorHistory.count != 50:
+            raise ValueError(f"Unexpected indicators values {indicatorHistory.count}")
+
+        for indicatorDataPoints in indicatorHistory:
+            middle_band = indicatorDataPoints["middle_band"]
+            self.debug(f"BB @{indicatorDataPoints.current}: middle_band: {middle_band} upper_band: {indicatorDataPoints.upper_band}")
+            if indicatorDataPoints == 0:
+                raise ValueError(f"Unexpected indicators point {indicatorDataPoints}")
+
+        currentValues = indicatorHistory.current
+        if len(currentValues) != 50 or len([x for x in currentValues if x.value == 0]) > 0:
+            raise ValueError(f"Unexpected indicators current values {len(currentValues)}")
+        upperBandPoints = indicatorHistory["upper_band"]
+        if len(upperBandPoints) != 50 or len([x for x in upperBandPoints if x.value == 0]) > 0:
+            raise ValueError(f"Unexpected indicators upperBandPoints values {len(upperBandPoints)}")
+
+        # We are done now!
+        self.quit()