Files
quantconnect--lean/Common/Python/PandasConverter.cs
T
Jhonathan Abreu df308cc2a7
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
Make PandasConverter.GetIndicatorDataFrame accept Python dictionary (#6365)
* Overload PandasConverter.GetIndicatorDataFrame to accept a Python dict

* Shared implementation code for PandasConverter.GetIndicatorDataFrame overloads

* Added documentation for private shared methods used by PandasConverter.GetIndicatorDataFrame

* Added unit tests for PandasConverter.GetIndicatorDataFrame

* Added unit tests for PandasConverter.GetIndicatorDataFrame Dictionary overload

* Address change requests

* Address change requests
2022-06-01 19:57:51 -03:00

231 lines
8.6 KiB
C#

/*
* 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 Python.Runtime;
using QuantConnect.Data;
using QuantConnect.Indicators;
using System;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Python
{
/// <summary>
/// Collection of methods that converts lists of objects in pandas.DataFrame
/// </summary>
public class PandasConverter
{
private static dynamic _pandas;
/// <summary>
/// Creates an instance of <see cref="PandasConverter"/>.
/// </summary>
public PandasConverter()
{
if (_pandas == null)
{
using (Py.GIL())
{
_pandas = Py.Import("pandas");
}
}
}
/// <summary>
/// Converts an enumerable of <see cref="Slice"/> in a pandas.DataFrame
/// </summary>
/// <param name="data">Enumerable of <see cref="Slice"/></param>
/// <returns><see cref="PyObject"/> containing a pandas.DataFrame</returns>
public PyObject GetDataFrame(IEnumerable<Slice> data)
{
var maxLevels = 0;
var sliceDataDict = new Dictionary<Symbol, PandasData>();
foreach (var slice in data)
{
foreach (var key in slice.Keys)
{
var baseData = slice[key];
PandasData value;
if (!sliceDataDict.TryGetValue(key, out value))
{
sliceDataDict.Add(key, value = new PandasData(baseData));
maxLevels = Math.Max(maxLevels, value.Levels);
}
if (value.IsCustomData)
{
value.Add(baseData);
}
else
{
var ticks = slice.Ticks.ContainsKey(key) ? slice.Ticks[key] : null;
var tradeBars = slice.Bars.ContainsKey(key) ? slice.Bars[key] : null;
var quoteBars = slice.QuoteBars.ContainsKey(key) ? slice.QuoteBars[key] : null;
value.Add(ticks, tradeBars, quoteBars);
}
}
}
using (Py.GIL())
{
if (sliceDataDict.Count == 0)
{
return _pandas.DataFrame();
}
var dataFrames = sliceDataDict.Select(x => x.Value.ToPandasDataFrame(maxLevels));
return _pandas.concat(dataFrames.ToArray(), Py.kw("sort", true));
}
}
/// <summary>
/// Converts an enumerable of <see cref="IBaseData"/> in a pandas.DataFrame
/// </summary>
/// <param name="data">Enumerable of <see cref="Slice"/></param>
/// <returns><see cref="PyObject"/> containing a pandas.DataFrame</returns>
public PyObject GetDataFrame<T>(IEnumerable<T> data)
where T : IBaseData
{
PandasData sliceData = null;
foreach (var datum in data)
{
if (sliceData == null)
{
sliceData = new PandasData(datum);
}
sliceData.Add(datum);
}
using (Py.GIL())
{
// If sliceData is still null, data is an empty enumerable
// returns an empty pandas.DataFrame
if (sliceData == null)
{
return _pandas.DataFrame();
}
return sliceData.ToPandasDataFrame();
}
}
/// <summary>
/// Converts a dictionary with a list of <see cref="IndicatorDataPoint"/> in a pandas.DataFrame
/// </summary>
/// <param name="data">Dictionary with a list of <see cref="IndicatorDataPoint"/></param>
/// <returns><see cref="PyObject"/> containing a pandas.DataFrame</returns>
public PyObject GetIndicatorDataFrame(IDictionary<string, List<IndicatorDataPoint>> data)
{
using (Py.GIL())
{
var pyDict = new PyDict();
foreach (var kvp in data)
{
AddSeriesToPyDict(kvp.Key, kvp.Value, pyDict);
}
return MakeIndicatorDataFrame(pyDict);
}
}
/// <summary>
/// Converts a dictionary with a list of <see cref="IndicatorDataPoint"/> in a pandas.DataFrame
/// </summary>
/// <param name="data"><see cref="PyObject"/> that should be a dictionary (convertible to PyDict) of string to list of <see cref="IndicatorDataPoint"/></param>
/// <returns><see cref="PyObject"/> containing a pandas.DataFrame</returns>
public PyObject GetIndicatorDataFrame(PyObject data)
{
using (Py.GIL())
{
using var inputPythonType = data.GetPythonType();
var inputTypeStr = inputPythonType.ToString();
var targetTypeStr = nameof(PyDict);
PyObject currentKvp = null;
try
{
using var pyDictData = new PyDict(data);
using var seriesPyDict = new PyDict();
targetTypeStr = $"{nameof(String)}: {nameof(List<IndicatorDataPoint>)}";
foreach (var kvp in pyDictData.Items())
{
currentKvp = kvp;
AddSeriesToPyDict(kvp[0].As<string>(), kvp[1].As<List<IndicatorDataPoint>>(), seriesPyDict);
}
return MakeIndicatorDataFrame(seriesPyDict);
}
catch (Exception e)
{
if (currentKvp != null)
{
inputTypeStr = $"{currentKvp[0].GetPythonType()}: {currentKvp[1].GetPythonType()}";
}
throw new ArgumentException(
$"ConvertToDictionary cannot be used to convert a {inputTypeStr} into {targetTypeStr}. Reason: {e.Message}",
e
);
}
}
}
/// <summary>
/// Returns a string that represent the current object
/// </summary>
/// <returns></returns>
public override string ToString()
{
return _pandas == null
? "pandas module was not imported."
: _pandas.Repr();
}
/// <summary>
/// Creates a series from a list of <see cref="IndicatorDataPoint"/> and adds it to the
/// <see cref="PyDict"/> as the value of the given <paramref name="key"/>
/// </summary>
/// <param name="key">Key to insert in the <see cref="PyDict"/></param>
/// <param name="points">List of <see cref="IndicatorDataPoint"/> that will make up the resulting series</param>
/// <param name="pyDict"><see cref="PyDict"/> where the resulting key-value pair will be inserted into</param>
private void AddSeriesToPyDict(string key, List<IndicatorDataPoint> points, PyDict pyDict)
{
var index = new List<DateTime>();
var values = new List<double>();
foreach (var point in points)
{
index.Add(point.EndTime);
values.Add((double) point.Value);
}
pyDict.SetItem(key.ToLowerInvariant(), _pandas.Series(values, index));
}
/// <summary>
/// Converts a <see cref="PyDict"/> of string to pandas.Series in a pandas.DataFrame
/// </summary>
/// <param name="pyDict"><see cref="PyDict"/> of string to pandas.Series</param>
/// <returns><see cref="PyObject"/> containing a pandas.DataFrame</returns>
private PyObject MakeIndicatorDataFrame(PyDict pyDict)
{
return _pandas.DataFrame(pyDict, columns: pyDict.Keys().Select(x => x.As<string>().ToLowerInvariant()).OrderBy(x => x));
}
}
}