204 lines
7.9 KiB
C#
204 lines
7.9 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using QuantConnect.Data;
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using QuantConnect.Data.Market;
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using QuantConnect.Interfaces;
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using System;
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using System.Collections.Generic;
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using System.Linq;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm demonstrating use of map files with India data
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="India data" />
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/// <meta name="tag" content="regression test" />
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/// <meta name="tag" content="rename event" />
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/// <meta name="tag" content="map" />
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/// <meta name="tag" content="mapping" />
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/// <meta name="tag" content="map files" />
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public class IndiaDataRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _mappingSymbol, _splitAndDividendSymbol;
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private bool _initialMapping;
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private bool _executionMapping;
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private bool _receivedWarningEvent;
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private bool _receivedOccurredEvent;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetAccountCurrency("INR"); //Set Account Currency
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SetStartDate(2004, 5, 20); //Set Start Date
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SetEndDate(2016, 7, 26); //Set End Date
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_mappingSymbol = AddEquity("3MINDIA", Resolution.Daily, Market.India).Symbol;
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_splitAndDividendSymbol = AddEquity("CCCL", Resolution.Daily, Market.India).Symbol;
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}
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/// <summary>
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/// Raises the data event.
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/// </summary>
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/// <param name="dividends">Data.</param>
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public override void OnDividends(Dividends dividends)
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{
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if (dividends.ContainsKey(_splitAndDividendSymbol))
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{
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var dividend = dividends[_splitAndDividendSymbol];
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if (Time.Date == new DateTime(2010, 06, 15) &&
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(dividend.Price != 0.5m || dividend.ReferencePrice != 88.8m || dividend.Distribution != 0.5m))
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{
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throw new RegressionTestException("Did not receive expected dividend values");
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}
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}
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}
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/// <summary>
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/// Raises the data event.
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/// </summary>
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/// <param name="splits">Splits.</param>
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public override void OnSplits(Splits splits)
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{
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if (splits.ContainsKey(_splitAndDividendSymbol))
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{
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var split = splits[_splitAndDividendSymbol];
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if (split.Type == SplitType.Warning)
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{
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_receivedWarningEvent = true;
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}
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else if (split.Type == SplitType.SplitOccurred)
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{
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_receivedOccurredEvent = true;
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if (split.Price != 421m || split.ReferencePrice != 421m || split.SplitFactor != 0.2m)
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{
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throw new RegressionTestException("Did not receive expected split values");
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}
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}
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}
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}
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/// <summary>
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/// Checks the symbol change event
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/// </summary>
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public override void OnSymbolChangedEvents(SymbolChangedEvents symbolsChanged)
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{
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if (symbolsChanged.ContainsKey(_mappingSymbol))
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{
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var mappingEvent = symbolsChanged.Single(x => x.Key.SecurityType == SecurityType.Equity).Value;
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Log($"{Time} - Ticker changed from: {mappingEvent.OldSymbol} to {mappingEvent.NewSymbol}");
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if (Time.Date == new DateTime(1999, 01, 01))
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{
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_initialMapping = true;
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}
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else if (Time.Date == new DateTime(2004, 06, 15))
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{
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if (mappingEvent.NewSymbol == "3MINDIA"
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&& mappingEvent.OldSymbol == "BIRLA3M")
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{
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_executionMapping = true;
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}
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}
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}
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}
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/// <summary>
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/// Final step of the algorithm
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/// </summary>
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public override void OnEndOfAlgorithm()
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{
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if (_initialMapping)
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{
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throw new RegressionTestException("The ticker generated the initial rename event");
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}
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if (!_executionMapping)
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{
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throw new RegressionTestException("The ticker did not rename throughout the course of its life even though it should have");
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}
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if (!_receivedOccurredEvent)
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{
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throw new RegressionTestException("Did not receive expected split event");
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}
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if (!_receivedWarningEvent)
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{
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throw new RegressionTestException("Did not receive expected split warning event");
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}
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public long DataPoints => 23036;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "0"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "100000"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "0"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "₹0.00"},
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{"Estimated Strategy Capacity", "₹0"},
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{"Lowest Capacity Asset", ""},
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{"Portfolio Turnover", "0%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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