Remove Quandl from LEAN (#6110)
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* Remove Quandl from LEAN * Nit changes and CustomLiveDataFeedTests.cs * Resolve conflicts * Remove files related with Quandl * Fix bug * Fix QuantBookHistoryTests.cs * Fix bug * Fix bug * Fix unit tests * Try fix regression tests * Nit changes * Fix bug * Some of the requested changes * The missing changes * Requested changes * Nit changes * Revert "Nit changes" This reverts commit 9800bc5c34f3ac20e30bea7a92dd4a9867213bb5. * Nit changes * Fix bug * Requested changes * Missing file using Quandl to be removed * Nit changes * Not applied nit change * Nit change * Nit change * Add nasdaq-auth-code parameter in config.json * Remove 'quandl-auth-token' from config.json Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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Ricardo Andrés Marino Rojas
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@@ -30,12 +30,11 @@ class HistoryAlgorithm(QCAlgorithm):
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self.SetCash(100000) #Set Strategy Cash
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# Find more symbols here: http://quantconnect.com/data
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self.AddEquity("SPY", Resolution.Daily)
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self.AddData(QuandlFuture,"CHRIS/CME_SP1", Resolution.Daily)
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self.AddData(CustomDataEquity, "IBM", Resolution.Daily)
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# specifying the exchange will allow the history methods that accept a number of bars to return to work properly
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self.Securities["CHRIS/CME_SP1"].Exchange = EquityExchange()
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# we can get history in initialize to set up indicators and such
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self.spyDailySma = SimpleMovingAverage(14)
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self.dailySma = SimpleMovingAverage(14)
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# get the last calendar year's worth of SPY data at the configured resolution (daily)
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tradeBarHistory = self.History([self.Securities["SPY"].Symbol], timedelta(365))
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@@ -56,56 +55,52 @@ class HistoryAlgorithm(QCAlgorithm):
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# we can loop over the return value from these functions and we get TradeBars
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# we can use these TradeBars to initialize indicators or perform other math
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for index, tradeBar in tradeBarHistory.loc["SPY"].iterrows():
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self.spyDailySma.Update(index, tradeBar["close"])
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self.dailySma.Update(index, tradeBar["close"])
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# get the last calendar year's worth of quandl data at the configured resolution (daily)
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quandlHistory = self.History(QuandlFuture, "CHRIS/CME_SP1", timedelta(365))
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self.AssertHistoryCount("History(QuandlFuture, \"CHRIS/CME_SP1\", timedelta(365))", quandlHistory, 250)
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# get the last calendar year's worth of customData data at the configured resolution (daily)
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customDataHistory = self.History(CustomDataEquity, "IBM", timedelta(365))
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self.AssertHistoryCount("History(CustomDataEquity, \"IBM\", timedelta(365))", customDataHistory, 10)
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# get the last 14 bars of SPY at the configured resolution (daily)
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quandlHistory = self.History(QuandlFuture, "CHRIS/CME_SP1", 14)
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self.AssertHistoryCount("History(QuandlFuture, \"CHRIS/CME_SP1\", 14)", quandlHistory, 14)
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# get the last 10 bars of IBM at the configured resolution (daily)
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customDataHistory = self.History(CustomDataEquity, "IBM", 14)
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self.AssertHistoryCount("History(CustomDataEquity, \"IBM\", 14)", customDataHistory, 10)
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# we can loop over the return values from these functions and we'll get Quandl data
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# we can loop over the return values from these functions and we'll get Custom data
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# this can be used in much the same way as the tradeBarHistory above
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self.spyDailySma.Reset()
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for index, quandl in quandlHistory.loc["CHRIS/CME_SP1"].iterrows():
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self.spyDailySma.Update(index, quandl["settle"])
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self.dailySma.Reset()
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for index, customData in customDataHistory.loc["IBM"].iterrows():
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self.dailySma.Update(index, customData["value"])
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# get the last year's worth of all configured Quandl data at the configured resolution (daily)
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#allQuandlData = self.History(QuandlFuture, timedelta(365))
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#self.AssertHistoryCount("History(QuandlFuture, timedelta(365))", allQuandlData, 250)
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# get the last 10 bars worth of Custom data for the specified symbols at the configured resolution (daily)
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allCustomData = self.History(CustomDataEquity, self.Securities.Keys, 14)
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self.AssertHistoryCount("History(CustomDataEquity, self.Securities.Keys, 14)", allCustomData, 10)
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# get the last 14 bars worth of Quandl data for the specified symbols at the configured resolution (daily)
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allQuandlData = self.History(QuandlFuture, self.Securities.Keys, 14)
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self.AssertHistoryCount("History(QuandlFuture, self.Securities.Keys, 14)", allQuandlData, 14)
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# NOTE: Using different resolutions require that they are properly implemented in your data type. If your
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# custom data source has different resolutions, it would need to be implemented in the GetSource and
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# Reader methods properly.
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#customDataHistory = self.History(CustomDataEquity, "IBM", timedelta(7), Resolution.Minute)
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#customDataHistory = self.History(CustomDataEquity, "IBM", 14, Resolution.Minute)
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#allCustomData = self.History(CustomDataEquity, timedelta(365), Resolution.Minute)
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#allCustomData = self.History(CustomDataEquity, self.Securities.Keys, 14, Resolution.Minute)
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#allCustomData = self.History(CustomDataEquity, self.Securities.Keys, timedelta(1), Resolution.Minute)
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#allCustomData = self.History(CustomDataEquity, self.Securities.Keys, 14, Resolution.Minute)
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# NOTE: using different resolutions require that they are properly implemented in your data type, since
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# Quandl doesn't support minute data, this won't actually work, but if your custom data source has
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# different resolutions, it would need to be implemented in the GetSource and Reader methods properly
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#quandlHistory = self.History(QuandlFuture, "CHRIS/CME_SP1", timedelta(7), Resolution.Minute)
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#quandlHistory = self.History(QuandlFuture, "CHRIS/CME_SP1", 14, Resolution.Minute)
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#allQuandlData = self.History(QuandlFuture, timedelta(365), Resolution.Minute)
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#allQuandlData = self.History(QuandlFuture, self.Securities.Keys, 14, Resolution.Minute)
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#allQuandlData = self.History(QuandlFuture, self.Securities.Keys, timedelta(1), Resolution.Minute)
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#allQuandlData = self.History(QuandlFuture, self.Securities.Keys, 14, Resolution.Minute)
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# get the last calendar year's worth of all quandl data
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allQuandlData = self.History(QuandlFuture, self.Securities.Keys, timedelta(365))
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self.AssertHistoryCount("History(QuandlFuture, self.Securities.Keys, timedelta(365))", allQuandlData, 250)
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# get the last calendar year's worth of all customData data
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allCustomData = self.History(CustomDataEquity, self.Securities.Keys, timedelta(365))
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self.AssertHistoryCount("History(CustomDataEquity, self.Securities.Keys, timedelta(365))", allCustomData, 10)
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# we can also access the return value from the multiple symbol functions to request a single
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# symbol and then loop over it
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singleSymbolQuandl = allQuandlData.loc["CHRIS/CME_SP1"]
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self.AssertHistoryCount("allQuandlData.loc[\"CHRIS/CME_SP1\"]", singleSymbolQuandl, 250)
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for quandl in singleSymbolQuandl:
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# do something with 'CHRIS/CME_SP1.QuandlFuture' quandl data
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singleSymbolCustom = allCustomData.loc["IBM"]
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self.AssertHistoryCount("allCustomData.loc[\"IBM\"]", singleSymbolCustom, 10)
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for customData in singleSymbolCustom:
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# do something with 'IBM.CustomDataEquity' customData data
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pass
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quandlSpyLows = allQuandlData.loc["CHRIS/CME_SP1"]["low"]
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self.AssertHistoryCount("allQuandlData.loc[\"CHRIS/CME_SP1\"][\"low\"]", quandlSpyLows, 250)
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for low in quandlSpyLows:
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# do something with 'CHRIS/CME_SP1.QuandlFuture' quandl data
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customDataSpyValues = allCustomData.loc["IBM"]["value"]
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self.AssertHistoryCount("allCustomData.loc[\"IBM\"][\"value\"]", customDataSpyValues, 10)
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for value in customDataSpyValues:
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# do something with 'IBM.CustomDataEquity' value data
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pass
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@@ -124,10 +119,20 @@ class HistoryAlgorithm(QCAlgorithm):
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raise Exception("{} expected {}, but received {}".format(methodCall, expected, count))
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class QuandlFuture(PythonQuandl):
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'''Custom quandl data type for setting customized value column name. Value column is used for the primary trading calculations and charting.'''
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def __init__(self):
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# Define ValueColumnName: cannot be None, Empty or non-existant column name
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# If ValueColumnName is "Close", do not use PythonQuandl, use Quandl:
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# self.AddData[QuandlFuture](self.crude, Resolution.Daily)
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self.ValueColumnName = "Settle"
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class CustomDataEquity(PythonData):
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def GetSource(self, config, date, isLive):
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source = "https://www.dl.dropboxusercontent.com/s/o6ili2svndzn556/custom_data.csv?dl=0"
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return SubscriptionDataSource(source, SubscriptionTransportMedium.RemoteFile)
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def Reader(self, config, line, date, isLive):
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if line == None:
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return None
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customData = CustomDataEquity()
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customData.Symbol = config.Symbol
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csv = line.split(",")
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customData.Time = datetime.strptime(csv[0], '%Y%m%d %H:%M')
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customData.EndTime = customData.Time + timedelta(days=1)
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customData.Value = float(csv[1])
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return customData
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