3. Dynamic parameters passed to cerebro.optstrategy()
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Dynamic parameters passed to cerebro.optstrategy()

  • L

    Dear All,
    I'm familiar with the following syntax:

    cerebro.optstrategy(MyHolyGrailStrategy, period=range(1, 20), )

    But how can I call optstrategy when the parameters to be optimized and their respective ranges are only known at runtime?
    For addstrategy(), I'm using something like

    cerebro.addstrategy(MyHolyGrailStrategy, parameters)

    where parameters is a dictionnary that is received by the _init method of my strategy

    def __init__(self, params):

    But the same approach does not seem to be working here.

    Many thanks in advance
    Kind regards,
    Lamp'

    0
  • L

    ok, found what I was looking for. For the benefits of others...

    d = {'period': [14, 16, 20 , 22, 25, 30], 'period2': [33, 39]}
cerebro.addstrategy(MyHolyGrailStrategy, *[], **d)

    cheers

    0
  • B
    administrators

    Just to be clear, what have you exactly found?

    The signature for addstrategy and optstrategy is clear an documented. It taks *args and *kwargs and where possible some of the keyword arguments are incorporated to the declarative built-in params (see below). The rest is given verbatim to the strategy.

    Note: you probably didn't want to use addstrategy in your last post, given that you obviously pass a combination of parameters meant for optimization.

    @lampalork said in Dynamic parameters passed to cerebro.optstrategy():

    For addstrategy(), I'm using something like

    cerebro.addstrategy(MyHolyGrailStrategy, parameters)

    where parameters is a dictionary that is received by the __init__ method of my strategy

    def __init__(self, params):

    That pattern for example goes against the declarative params provided as a built-in by backtrader and brings absolutely no benefit.

    1
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