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Add dataNormalizationMode parameter to every history api method overload (#7208)
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This commit is contained in:
Jhonathan Abreu
2023-04-25 16:19:39 -04:00
committed by GitHub
parent c8a646c0f0
commit 8943dc6535
3 changed files with 401 additions and 43 deletions
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Algorithm/QCAlgorithm.Python.cs
+21 -14
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@@ -847,13 +847,14 @@ namespace QuantConnect.Algorithm
/// <param name="fillForward">True to fill forward missing data, false otherwise</param>
/// <param name="extendedMarketHours">True to include extended market hours data, false otherwise</param>
/// <param name="dataMappingMode">The contract mapping mode to use for the security history request</param>
/// <param name="dataNormalizationMode">The price scaling mode to use for the securities history</param>
/// <returns>A python dictionary with pandas DataFrame containing the requested historical data</returns>
[DocumentationAttribute(HistoricalData)]
public PyObject History(PyObject tickers, int periods, Resolution? resolution = null, bool? fillForward = null,
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null)
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null, DataNormalizationMode? dataNormalizationMode = null)
{
var symbols = tickers.ConvertToSymbolEnumerable();
return GetDataFrame(History(symbols, periods, resolution, fillForward, extendedMarketHours, dataMappingMode));
return GetDataFrame(History(symbols, periods, resolution, fillForward, extendedMarketHours, dataMappingMode, dataNormalizationMode));
}
/// <summary>
@@ -866,13 +867,14 @@ namespace QuantConnect.Algorithm
/// <param name="fillForward">True to fill forward missing data, false otherwise</param>
/// <param name="extendedMarketHours">True to include extended market hours data, false otherwise</param>
/// <param name="dataMappingMode">The contract mapping mode to use for the security history request</param>
/// <param name="dataNormalizationMode">The price scaling mode to use for the securities history</param>
/// <returns>A python dictionary with pandas DataFrame containing the requested historical data</returns>
[DocumentationAttribute(HistoricalData)]
public PyObject History(PyObject tickers, TimeSpan span, Resolution? resolution = null, bool? fillForward = null,
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null)
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null, DataNormalizationMode? dataNormalizationMode = null)
{
var symbols = tickers.ConvertToSymbolEnumerable();
return GetDataFrame(History(symbols, span, resolution, fillForward, extendedMarketHours, dataMappingMode));
return GetDataFrame(History(symbols, span, resolution, fillForward, extendedMarketHours, dataMappingMode, dataNormalizationMode));
}
/// <summary>
@@ -953,17 +955,18 @@ namespace QuantConnect.Algorithm
/// <param name="fillForward">True to fill forward missing data, false otherwise</param>
/// <param name="extendedMarketHours">True to include extended market hours data, false otherwise</param>
/// <param name="dataMappingMode">The contract mapping mode to use for the security history request</param>
/// <param name="dataNormalizationMode">The price scaling mode to use for the securities history</param>
/// <returns>pandas.DataFrame containing the requested historical data</returns>
[DocumentationAttribute(HistoricalData)]
public PyObject History(PyObject type, PyObject tickers, int periods, Resolution? resolution = null, bool? fillForward = null,
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null)
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null, DataNormalizationMode? dataNormalizationMode = null)
{
var symbols = tickers.ConvertToSymbolEnumerable();
CheckPeriodBasedHistoryRequestResolution(symbols, resolution);
var requestedType = type.CreateType();
var requests = CreateBarCountHistoryRequests(symbols, requestedType, periods, resolution, fillForward, extendedMarketHours,
dataMappingMode);
dataMappingMode, dataNormalizationMode);
return GetDataFrame(History(requests.Where(x => x != null)), requestedType);
}
@@ -979,12 +982,13 @@ namespace QuantConnect.Algorithm
/// <param name="fillForward">True to fill forward missing data, false otherwise</param>
/// <param name="extendedMarketHours">True to include extended market hours data, false otherwise</param>
/// <param name="dataMappingMode">The contract mapping mode to use for the security history request</param>
/// <param name="dataNormalizationMode">The price scaling mode to use for the securities history</param>
/// <returns>pandas.DataFrame containing the requested historical data</returns>
[DocumentationAttribute(HistoricalData)]
public PyObject History(PyObject type, PyObject tickers, TimeSpan span, Resolution? resolution = null, bool? fillForward = null,
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null)
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null, DataNormalizationMode? dataNormalizationMode = null)
{
return History(type, tickers, Time - span, Time, resolution, fillForward, extendedMarketHours, dataMappingMode);
return History(type, tickers, Time - span, Time, resolution, fillForward, extendedMarketHours, dataMappingMode, dataNormalizationMode);
}
/// <summary>
@@ -998,14 +1002,15 @@ namespace QuantConnect.Algorithm
/// <param name="fillForward">True to fill forward missing data, false otherwise</param>
/// <param name="extendedMarketHours">True to include extended market hours data, false otherwise</param>
/// <param name="dataMappingMode">The contract mapping mode to use for the security history request</param>
/// <param name="dataNormalizationMode">The price scaling mode to use for the securities history</param>
/// <returns>pandas.DataFrame containing the requested historical data</returns>
[DocumentationAttribute(HistoricalData)]
public PyObject History(PyObject type, Symbol symbol, DateTime start, DateTime end, Resolution? resolution = null, bool? fillForward = null,
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null)
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null, DataNormalizationMode? dataNormalizationMode = null)
{
var requestedType = type.CreateType();
var requests = CreateDateRangeHistoryRequests(new [] { symbol }, requestedType, start, end, resolution, fillForward,
extendedMarketHours, dataMappingMode);
extendedMarketHours, dataMappingMode, dataNormalizationMode);
if (requests.IsNullOrEmpty())
{
throw new ArgumentException($"No history data could be fetched. " +
@@ -1027,10 +1032,11 @@ namespace QuantConnect.Algorithm
/// <param name="fillForward">True to fill forward missing data, false otherwise</param>
/// <param name="extendedMarketHours">True to include extended market hours data, false otherwise</param>
/// <param name="dataMappingMode">The contract mapping mode to use for the security history request</param>
/// <param name="dataNormalizationMode">The price scaling mode to use for the securities history</param>
/// <returns>pandas.DataFrame containing the requested historical data</returns>
[DocumentationAttribute(HistoricalData)]
public PyObject History(PyObject type, Symbol symbol, int periods, Resolution? resolution = null, bool? fillForward = null,
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null)
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null, DataNormalizationMode? dataNormalizationMode = null)
{
resolution = GetResolution(symbol, resolution);
CheckPeriodBasedHistoryRequestResolution(new[] { symbol }, resolution);
@@ -1038,7 +1044,7 @@ namespace QuantConnect.Algorithm
var marketHours = GetMarketHours(symbol);
var start = _historyRequestFactory.GetStartTimeAlgoTz(symbol, periods, resolution.Value, marketHours.ExchangeHours,
marketHours.DataTimeZone, extendedMarketHours);
return History(type, symbol, start, Time, resolution, fillForward, extendedMarketHours, dataMappingMode);
return History(type, symbol, start, Time, resolution, fillForward, extendedMarketHours, dataMappingMode, dataNormalizationMode);
}
/// <summary>
@@ -1052,12 +1058,13 @@ namespace QuantConnect.Algorithm
/// <param name="fillForward">True to fill forward missing data, false otherwise</param>
/// <param name="extendedMarketHours">True to include extended market hours data, false otherwise</param>
/// <param name="dataMappingMode">The contract mapping mode to use for the security history request</param>
/// <param name="dataNormalizationMode">The price scaling mode to use for the securities history</param>
/// <returns>pandas.DataFrame containing the requested historical data</returns>
[DocumentationAttribute(HistoricalData)]
public PyObject History(PyObject type, Symbol symbol, TimeSpan span, Resolution? resolution = null, bool? fillForward = null,
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null)
bool? extendedMarketHours = null, DataMappingMode? dataMappingMode = null, DataNormalizationMode? dataNormalizationMode = null)
{
return History(type, symbol, Time - span, Time, resolution, fillForward, extendedMarketHours, dataMappingMode);
return History(type, symbol, Time - span, Time, resolution, fillForward, extendedMarketHours, dataMappingMode, dataNormalizationMode);
}
/// <summary>