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Hello!
I want to develop an algorithm for trading Bitcoins. For this purpose I need to import the data.
According to the documentation ( https://www.quantconnect.com/docs#python ) you need to create your own class (subclass of PythonData) in order to access custom data. That subclass must override the GetSource and Reader methods:
class Weather(PythonData):
''' Weather based rebalancing'''
def GetSource(self, config, date, isLive):
source = "https://www.wunderground.com/history/airport/{0}/{1}/1/1/CustomHistory.html?dayend=31&monthend=12&yearend={1}&format=1".format(config.Symbol, date.year);
return SubscriptionDataSource(source, SubscriptionTransportMedium.RemoteFile);
def Reader(self, config, line, date, isLive):
# If first character is not digit, pass
if not (line.strip() and line[0].isdigit()): return None
data = line.split(',')
weather = Weather()
weather.Symbol = config.Symbol
weather.Time = datetime.strptime(data[0], '%Y-%m-%d') + timedelta(hours=20) # Make sure we only get this data AFTER trading day - don't want forward bias.
weather.Value = decimal.Decimal(data[2])
weather["MaxC"] = float(data[1])
weather["MinC"] = float(data[3])
return weather However, this seems to be a CSV data source, whereas the Quandl Bitcoin data are in JSON format.
What do I need to do in order to be able to use Quandl Bitcoin data in QuantConnect for backtesting?
I found a class PythonQuandl.cs in the same directory as PythonData, but unfortunately no documentation on how to use it.
Thanks in advance
Dmitri Pisarenko
Alexandre Catarino
Please checkout CustomDataRegressionAlgorithm.
It is an example using CSV data from Quandl and JSON data from BitStamp.
Petio Petrov
Hello,
Is there an example of subclassing PythonData for option chains?
Thank you
Shile Wen
Hi Petio,
We have built-in support for option chain data here.
Best,
Shile Wen
Petio Petrov
Thanks Shile, but I was refering to adding custom options data by implementing the `PythonData` class.
Alexandre Catarino
Hi Petio Petrov ,
There is no example of subclassing PythonData to create options data since QuantConnect supports that data.
It should be implemented similarly to the example above.
Please note that options have some particularities that are handled under-the-hood by the algorithm that will not work with a custom data type.
Dmitri Pisarenko
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