/*
 * 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 NUnit.Framework;
using Python.Runtime;
using QuantConnect.Data;
using QuantConnect.Python;
using System;
using System.Collections.Generic;

namespace QuantConnect.Tests.Python
{
    [TestFixture]
    public partial class PandasConverterTests
    {
        // Over complicating it on purpose to test the expanding of nested classes
        private class BarOpen
        {
            public decimal Open { get; set; }
            public BarOpen(decimal open)
            {
                Open = open;
            }
        }

        private class BarHigh
        {
            public decimal High { get; set; }
            public BarHigh(decimal high)
            {
                High = high;
            }
        }

        private class BarLow
        {
            public decimal Low { get; set; }
            public BarLow(decimal low)
            {
                Low = low;
            }
        }

        private class BarClose
        {
            public decimal Close { get; set; }
            public BarClose(decimal close)
            {
                Close = close;
            }
        }

        private class CustomBar
        {
            public BarOpen Open { get; set; }
            public BarHigh High { get; set; }
            public BarLow Low { get; set; }
            public BarClose Close { get; set; }
        }

        private class CustomTradeBar : BaseData
        {
            public CustomBar Prices { get; set; }

            public decimal Volume { get; set; }

            public CustomTradeBar(Symbol symbol, decimal open, decimal high, decimal low, decimal close, decimal volume)
            {
                Symbol = symbol;
                Prices = new CustomBar
                {
                    Open = new BarOpen(open),
                    High = new BarHigh(high),
                    Low = new BarLow(low),
                    Close = new BarClose(close),
                };
                Volume = volume;
            }
        }

        [Test]
        public void ExpandsNestedClassesIntoDataFrameColumns()
        {
            var converter = new PandasConverter();
            var data = new List<CustomTradeBar>
            {
                new CustomTradeBar(Symbols.IBM, 101m, 102m, 100m, 101m, 10m),
                new CustomTradeBar(Symbols.IBM, 102m, 103m, 101m, 101m, 9m),
                new CustomTradeBar(Symbols.IBM, 99m, 100m, 98m, 99m, 10m),
            };

            dynamic dataFrame = converter.GetDataFrame(data);

            var expectedColumnNames = new List<string>() { "open", "high", "low", "close", "volume" };

            AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
        }

        private class CustomQuoteBar : BaseData
        {
            public CustomBar Bid { get; set; }

            public decimal BidSize { get; set; }

            public CustomBar Ask { get; set; }

            public decimal AskSize { get; set; }

            public CustomQuoteBar(Symbol symbol, decimal bidOpen, decimal bidHigh, decimal bidLow, decimal bidClose, decimal bidSize,
                decimal askOpen, decimal askHigh, decimal askLow, decimal askClose, decimal askSize)
            {
                Symbol = symbol;
                Bid = new CustomBar
                {
                    Open = new BarOpen(bidOpen),
                    High = new BarHigh(bidHigh),
                    Low = new BarLow(bidLow),
                    Close = new BarClose(bidClose),
                };
                BidSize = bidSize;
                Ask = new CustomBar
                {
                    Open = new BarOpen(askOpen),
                    High = new BarHigh(askHigh),
                    Low = new BarLow(askLow),
                    Close = new BarClose(askClose),
                };
                AskSize = askSize;
            }
        }

        [Test]
        public void ExpandsNestedClassesIntoDataFrameColumnsWithDuplicateNames()
        {
            var converter = new PandasConverter();
            var data = new List<CustomQuoteBar>
            {
                new CustomQuoteBar(Symbols.IBM, 101m, 102m, 100m, 101m, 10m, 101m, 102m, 100m, 101m, 10m),
                new CustomQuoteBar(Symbols.IBM, 102m, 103m, 101m, 101m, 9m, 102m, 103m, 101m, 101m, 9m),
                new CustomQuoteBar(Symbols.IBM, 99m, 100m, 98m, 99m, 10m, 99m, 100m, 98m, 99m, 10m),
            };

            dynamic dataFrame = converter.GetDataFrame(data);

            var expectedColumnNames = new List<string>() {
                "bidopen", "bidhigh", "bidlow", "bidclose", "bidsize",
                "askopen", "askhigh", "asklow", "askclose", "asksize"
            };

            AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
        }

        public class TestInnerData1
        {
            public decimal DecimalValue1 { get; set; }
            public string StringValue1 { get; set; }

        }

        [PandasNonExpandable]
        public class TestInnerData2
        {
            public decimal DecimalValue2 { get; set; }
            public string StringValue2 { get; set; }
        }

        public class TestData1 : BaseData
        {
            public TestInnerData1 TestInnerData1 { get; set; }
            public TestInnerData2 TestInnerData2 { get; set; }

            [PandasNonExpandable]
            public TestInnerData1 TestInnerData3 { get; set; }

            public TestData1(Symbol symbol, decimal decimalValue1, string stringValue1, decimal decimalValue2, string stringValue2,
                decimal decimalValue3, string stringValue3)
            {
                Symbol = symbol;
                TestInnerData1 = new TestInnerData1
                {
                    DecimalValue1 = decimalValue1,
                    StringValue1 = stringValue1,
                };
                TestInnerData2 = new TestInnerData2
                {
                    DecimalValue2 = decimalValue2,
                    StringValue2 = stringValue2,
                };
                TestInnerData3 = new TestInnerData1
                {
                    DecimalValue1 = decimalValue3,
                    StringValue1 = stringValue3,
                };
            }
        }

        [Test]
        public void DoesNotExpandMarkedPropertiesAndClasses()
        {
            var converter = new PandasConverter();
            var data = new List<TestData1>
            {
                new TestData1(Symbols.IBM, 1m, "Test 1.1", 2m, "Test 1.2", 3m, "Test 1.3"),
                new TestData1(Symbols.IBM, 10m, "Test 2.1", 20m, "Test 2.2", 30m, "Test 2.3"),
                new TestData1(Symbols.IBM, 100m, "Test 3.1", 200m, "Test 3.2", 300m, "Test 3.3"),
            };

            dynamic dataFrame = converter.GetDataFrame(data);

            var expectedColumnNames = new List<string>() { "decimalvalue1", "stringvalue1", "testinnerdata2", "testinnerdata3" };

            AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);

            using var _ = Py.GIL();

            foreach (var value in dataFrame["testinnerdata2"])
            {
                Assert.DoesNotThrow(() => value.As<TestInnerData2>());
            }

            foreach (var value in dataFrame["testinnerdata3"])
            {
                Assert.DoesNotThrow(() => value.As<TestInnerData1>());
            }
        }

        private static void AssertDataFrameColumns(dynamic dataFrame, int dataCount, List<string> expectedColumnNames)
        {
            using var _ = Py.GIL();

            Assert.AreEqual(dataCount, dataFrame.shape[0].As<int>());
            Assert.AreEqual(expectedColumnNames.Count, dataFrame.shape[1].As<int>());

            var columnNames = new List<string>();
            foreach (var pandasColumn in dataFrame.columns.to_list())
            {
                columnNames.Add(pandasColumn.__str__().As<string>());
            }
            CollectionAssert.AreEquivalent(expectedColumnNames, columnNames);
        }

        private class TestInnerData3
        {
            public decimal TestValue1 { get; set; }

            public decimal TestValue2 { get; set; }

            [PandasIgnore]
            public decimal IgnoredValue { get; set; }
        }

        private class TestData2 : BaseData
        {
            public TestInnerData3 InnerData { get; set; }

            public string MainValue { get; set; }

            public TestData2(Symbol symbol, string mainValue, decimal testValue1, decimal testValue2, decimal ignoredValue)
            {
                Symbol = symbol;
                MainValue = mainValue;
                InnerData = new TestInnerData3()
                {
                    TestValue1 = testValue1,
                    TestValue2 = testValue2,
                    IgnoredValue = ignoredValue
                };
            }
        }

        [Test]
        public void OmitsPropertiesMarkedToBeIgnored()
        {
            var converter = new PandasConverter();
            var data = new List<TestData2>
            {
                new TestData2(Symbols.IBM, "Main value 1", 10m, 200m, 5m),
                new TestData2(Symbols.IBM, "Main value 2", 20m, 300m, 10m),
                new TestData2(Symbols.IBM, "Main value 3", 30m, 400m, 15m),
            };

            dynamic dataFrame = converter.GetDataFrame(data);

            var expectedColumnNames = new List<string>() { "mainvalue", "testvalue1", "testvalue2" };

            AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
        }

        [PandasIgnoreMembers]
        private class TestIgnoreMembersBaseClass : BaseData
        {
            public decimal Decimal1 { get; set; }
            public decimal Decimal2 { get; set; }
        }

        private class TestIgnoreMembersDerivedClass : TestIgnoreMembersBaseClass
        {
            public decimal Decimal3 { get; set; }
            public decimal Decimal4 { get; set; }
        }

        [Test]
        public void OmitsBaseClassMembers()
        {
            var converter = new PandasConverter();
            var data = new List<TestIgnoreMembersDerivedClass>
            {
                new TestIgnoreMembersDerivedClass { Decimal1 = 1m, Decimal2 = 2m, Decimal3 = 3m, Decimal4 = 4m },
                new TestIgnoreMembersDerivedClass { Decimal1 = 10m, Decimal2 = 20m, Decimal3 = 30m, Decimal4 = 40m },
                new TestIgnoreMembersDerivedClass { Decimal1 = 100m, Decimal2 = 200m, Decimal3 = 300m, Decimal4 = 400m },
            };

            dynamic dataFrame = converter.GetDataFrame(data);

            // BaseData and TestIgnoreMembersBaseClass members are ignored
            var expectedColumnNames = new List<string>() { "decimal3", "decimal4" };

            AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
        }

        private class TestRenameMembersClass : ISymbolProvider
        {
            [PandasColumn("TheSymbol")]
            public Symbol Symbol { get; set; }

            [PandasColumn("Decimal")]
            public decimal DecimalValue { get; set; }

            [PandasColumn("String")]
            public string StringValue { get; set; }
        }

        [Test]
        public void RenamesMemberNames()
        {
            var converter = new PandasConverter();
            var data = new List<TestRenameMembersClass>
            {
                new TestRenameMembersClass { Symbol = Symbols.IBM, DecimalValue = 1m, StringValue = "Test 1" },
                new TestRenameMembersClass { Symbol = Symbols.AAPL, DecimalValue = 10m, StringValue = "Test 2" },
                new TestRenameMembersClass { Symbol = Symbols.SPY, DecimalValue = 100m, StringValue = "Test 3" },
            };

            dynamic dataFrame = converter.GetDataFrame(data);

            var expectedColumnNames = new List<string>() { "thesymbol", "decimal", "string" };

            AssertDataFrameColumns(dataFrame, data.Count, expectedColumnNames);
        }
    }
}