Is there a way to use only the Q500US stocks as pipelien input?
I know I can use a filter, but that way the pipeline iterates througth 8000 stocks and then filters out the results. Im looking for a way to avoid iterating througth that many stocks.
Is there a way to use only the Q500US stocks as pipelien input?
I know I can use a filter, but that way the pipeline iterates througth 8000 stocks and then filters out the results. Im looking for a way to avoid iterating througth that many stocks.
Adding a screen to a pipeline only limits the rows in the resulting dataframe and doesn't generally limit the time pipeline factors spend computing. To reduce the calculation time, one can add a mask to individual factors. Something like this
my_universe = Q500US()
dollar_volume = AverageDollarVolume(window_length=10, mask=my_universe)
That will only pass the assets in 'my_universe' to the factor and therefore only calculate for those assets. Most factors, including custom factors, accept the mask
parameter. There are a small few that don't (eg SimpleBeta
). It's really the compute function
in factors where all the computation is done. Limit the assets being passed to the factors and one can limit those computations.
Actually a trick I like to use for testing out a pipeline is to use a universe of just one or two assets. This often speeds up a pipeline and cuts down time debugging. Like this
# comment out the full universe when debugging / comment out the static universe in the final code
# my_universe = Q500US()
my_universe = StaticAssets(symbols(['AAPL']))
dollar_volume = AverageDollarVolume(window_length=10, mask=my_universe)
Good question.
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