chore: import upstream snapshot with attribution
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wehub-resource-sync
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/*
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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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*/
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using NUnit.Framework;
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using Python.Runtime;
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using QuantConnect.Data;
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using QuantConnect.Python;
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using System;
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using System.Collections.Generic;
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namespace QuantConnect.Tests.Python
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{
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[TestFixture]
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public partial class PandasConverterTests
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{
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// Over complicating it on purpose to test the expanding of nested classes
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private class BarOpen
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{
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public decimal Open { get; set; }
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public BarOpen(decimal open)
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{
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Open = open;
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}
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}
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private class BarHigh
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{
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public decimal High { get; set; }
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public BarHigh(decimal high)
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{
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High = high;
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}
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}
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private class BarLow
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{
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public decimal Low { get; set; }
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public BarLow(decimal low)
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{
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Low = low;
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}
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}
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private class BarClose
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{
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public decimal Close { get; set; }
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public BarClose(decimal close)
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{
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Close = close;
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}
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}
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private class CustomBar
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{
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public BarOpen Open { get; set; }
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public BarHigh High { get; set; }
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public BarLow Low { get; set; }
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public BarClose Close { get; set; }
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}
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private class CustomTradeBar : BaseData
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{
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public CustomBar Prices { get; set; }
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public decimal Volume { get; set; }
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public CustomTradeBar(Symbol symbol, decimal open, decimal high, decimal low, decimal close, decimal volume)
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{
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Symbol = symbol;
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Prices = new CustomBar
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{
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Open = new BarOpen(open),
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High = new BarHigh(high),
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Low = new BarLow(low),
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Close = new BarClose(close),
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};
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Volume = volume;
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}
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}
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[Test]
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public void ExpandsNestedClassesIntoDataFrameColumns()
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{
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var converter = new PandasConverter();
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var data = new List<CustomTradeBar>
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{
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new CustomTradeBar(Symbols.IBM, 101m, 102m, 100m, 101m, 10m),
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new CustomTradeBar(Symbols.IBM, 102m, 103m, 101m, 101m, 9m),
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new CustomTradeBar(Symbols.IBM, 99m, 100m, 98m, 99m, 10m),
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};
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dynamic dataFrame = converter.GetDataFrame(data);
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var expectedColumnNames = new List<string>() { "open", "high", "low", "close", "volume" };
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AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
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}
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private class CustomQuoteBar : BaseData
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{
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public CustomBar Bid { get; set; }
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public decimal BidSize { get; set; }
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public CustomBar Ask { get; set; }
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public decimal AskSize { get; set; }
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public CustomQuoteBar(Symbol symbol, decimal bidOpen, decimal bidHigh, decimal bidLow, decimal bidClose, decimal bidSize,
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decimal askOpen, decimal askHigh, decimal askLow, decimal askClose, decimal askSize)
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{
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Symbol = symbol;
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Bid = new CustomBar
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{
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Open = new BarOpen(bidOpen),
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High = new BarHigh(bidHigh),
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Low = new BarLow(bidLow),
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Close = new BarClose(bidClose),
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};
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BidSize = bidSize;
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Ask = new CustomBar
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{
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Open = new BarOpen(askOpen),
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High = new BarHigh(askHigh),
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Low = new BarLow(askLow),
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Close = new BarClose(askClose),
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};
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AskSize = askSize;
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}
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}
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[Test]
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public void ExpandsNestedClassesIntoDataFrameColumnsWithDuplicateNames()
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{
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var converter = new PandasConverter();
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var data = new List<CustomQuoteBar>
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{
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new CustomQuoteBar(Symbols.IBM, 101m, 102m, 100m, 101m, 10m, 101m, 102m, 100m, 101m, 10m),
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new CustomQuoteBar(Symbols.IBM, 102m, 103m, 101m, 101m, 9m, 102m, 103m, 101m, 101m, 9m),
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new CustomQuoteBar(Symbols.IBM, 99m, 100m, 98m, 99m, 10m, 99m, 100m, 98m, 99m, 10m),
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};
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dynamic dataFrame = converter.GetDataFrame(data);
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var expectedColumnNames = new List<string>() {
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"bidopen", "bidhigh", "bidlow", "bidclose", "bidsize",
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"askopen", "askhigh", "asklow", "askclose", "asksize"
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};
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AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
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}
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public class TestInnerData1
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{
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public decimal DecimalValue1 { get; set; }
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public string StringValue1 { get; set; }
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}
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[PandasNonExpandable]
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public class TestInnerData2
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{
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public decimal DecimalValue2 { get; set; }
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public string StringValue2 { get; set; }
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}
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public class TestData1 : BaseData
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{
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public TestInnerData1 TestInnerData1 { get; set; }
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public TestInnerData2 TestInnerData2 { get; set; }
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[PandasNonExpandable]
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public TestInnerData1 TestInnerData3 { get; set; }
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public TestData1(Symbol symbol, decimal decimalValue1, string stringValue1, decimal decimalValue2, string stringValue2,
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decimal decimalValue3, string stringValue3)
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{
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Symbol = symbol;
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TestInnerData1 = new TestInnerData1
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{
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DecimalValue1 = decimalValue1,
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StringValue1 = stringValue1,
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};
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TestInnerData2 = new TestInnerData2
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{
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DecimalValue2 = decimalValue2,
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StringValue2 = stringValue2,
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};
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TestInnerData3 = new TestInnerData1
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{
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DecimalValue1 = decimalValue3,
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StringValue1 = stringValue3,
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};
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}
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}
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[Test]
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public void DoesNotExpandMarkedPropertiesAndClasses()
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{
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var converter = new PandasConverter();
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var data = new List<TestData1>
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{
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new TestData1(Symbols.IBM, 1m, "Test 1.1", 2m, "Test 1.2", 3m, "Test 1.3"),
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new TestData1(Symbols.IBM, 10m, "Test 2.1", 20m, "Test 2.2", 30m, "Test 2.3"),
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new TestData1(Symbols.IBM, 100m, "Test 3.1", 200m, "Test 3.2", 300m, "Test 3.3"),
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};
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dynamic dataFrame = converter.GetDataFrame(data);
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var expectedColumnNames = new List<string>() { "decimalvalue1", "stringvalue1", "testinnerdata2", "testinnerdata3" };
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AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
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using var _ = Py.GIL();
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foreach (var value in dataFrame["testinnerdata2"])
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{
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Assert.DoesNotThrow(() => value.As<TestInnerData2>());
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}
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foreach (var value in dataFrame["testinnerdata3"])
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{
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Assert.DoesNotThrow(() => value.As<TestInnerData1>());
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}
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}
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private static void AssertDataFrameColumns(dynamic dataFrame, int dataCount, List<string> expectedColumnNames)
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{
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using var _ = Py.GIL();
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Assert.AreEqual(dataCount, dataFrame.shape[0].As<int>());
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Assert.AreEqual(expectedColumnNames.Count, dataFrame.shape[1].As<int>());
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var columnNames = new List<string>();
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foreach (var pandasColumn in dataFrame.columns.to_list())
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{
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columnNames.Add(pandasColumn.__str__().As<string>());
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}
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CollectionAssert.AreEquivalent(expectedColumnNames, columnNames);
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}
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private class TestInnerData3
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{
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public decimal TestValue1 { get; set; }
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public decimal TestValue2 { get; set; }
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[PandasIgnore]
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public decimal IgnoredValue { get; set; }
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}
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private class TestData2 : BaseData
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{
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public TestInnerData3 InnerData { get; set; }
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public string MainValue { get; set; }
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public TestData2(Symbol symbol, string mainValue, decimal testValue1, decimal testValue2, decimal ignoredValue)
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{
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Symbol = symbol;
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MainValue = mainValue;
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InnerData = new TestInnerData3()
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{
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TestValue1 = testValue1,
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TestValue2 = testValue2,
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IgnoredValue = ignoredValue
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};
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}
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}
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[Test]
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public void OmitsPropertiesMarkedToBeIgnored()
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{
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var converter = new PandasConverter();
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var data = new List<TestData2>
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{
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new TestData2(Symbols.IBM, "Main value 1", 10m, 200m, 5m),
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new TestData2(Symbols.IBM, "Main value 2", 20m, 300m, 10m),
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new TestData2(Symbols.IBM, "Main value 3", 30m, 400m, 15m),
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};
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dynamic dataFrame = converter.GetDataFrame(data);
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var expectedColumnNames = new List<string>() { "mainvalue", "testvalue1", "testvalue2" };
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AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
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}
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[PandasIgnoreMembers]
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private class TestIgnoreMembersBaseClass : BaseData
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{
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public decimal Decimal1 { get; set; }
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public decimal Decimal2 { get; set; }
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}
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private class TestIgnoreMembersDerivedClass : TestIgnoreMembersBaseClass
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{
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public decimal Decimal3 { get; set; }
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public decimal Decimal4 { get; set; }
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}
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[Test]
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public void OmitsBaseClassMembers()
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{
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var converter = new PandasConverter();
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var data = new List<TestIgnoreMembersDerivedClass>
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{
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new TestIgnoreMembersDerivedClass { Decimal1 = 1m, Decimal2 = 2m, Decimal3 = 3m, Decimal4 = 4m },
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new TestIgnoreMembersDerivedClass { Decimal1 = 10m, Decimal2 = 20m, Decimal3 = 30m, Decimal4 = 40m },
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new TestIgnoreMembersDerivedClass { Decimal1 = 100m, Decimal2 = 200m, Decimal3 = 300m, Decimal4 = 400m },
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};
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dynamic dataFrame = converter.GetDataFrame(data);
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// BaseData and TestIgnoreMembersBaseClass members are ignored
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var expectedColumnNames = new List<string>() { "decimal3", "decimal4" };
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AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
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}
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private class TestRenameMembersClass : ISymbolProvider
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{
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[PandasColumn("TheSymbol")]
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public Symbol Symbol { get; set; }
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[PandasColumn("Decimal")]
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public decimal DecimalValue { get; set; }
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[PandasColumn("String")]
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public string StringValue { get; set; }
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}
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[Test]
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public void RenamesMemberNames()
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{
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var converter = new PandasConverter();
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var data = new List<TestRenameMembersClass>
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{
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new TestRenameMembersClass { Symbol = Symbols.IBM, DecimalValue = 1m, StringValue = "Test 1" },
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new TestRenameMembersClass { Symbol = Symbols.AAPL, DecimalValue = 10m, StringValue = "Test 2" },
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new TestRenameMembersClass { Symbol = Symbols.SPY, DecimalValue = 100m, StringValue = "Test 3" },
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};
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dynamic dataFrame = converter.GetDataFrame(data);
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var expectedColumnNames = new List<string>() { "thesymbol", "decimal", "string" };
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AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
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}
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}
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}
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