加快/改善循环的构建/性能

Question

I am failrly new in Python. I wrote a script and I am surprised of the time it take to go through a particular loop compare to the rest of my code.

Can someone tell me what is inefficient in the code I wrote and maybe how to improve the speed ?

Here is the loop in question : (BT_Histos and Histos_Last_Rebal are dataframes with dates in index and columns of floats. Portfolio and Portfolio_Last_Rebal are dataframes same index as the 2 previous one that i am filling through the loop. weights is just a list)

Udl_Perf=BT_Histos/Histos_Last_Rebal-1

for i in range(1,len(BT_Histos.index)):
    """tricky because isin doesn't work with timestamp"""
    test_date=pd.Series(Portfolio.index[i-1])

    if test_date.isin(Rebalancing_Dates)[0]:
        Portfolio_Last_Rebal.loc[Portfolio_Last_Rebal.index[i],'PortSeries']=Portfolio.loc[Portfolio.index[i-1],'PortSeries']
    else:
        Portfolio_Last_Rebal.loc[Portfolio_Last_Rebal.index[i],'PortSeries']=Portfolio_Last_Rebal.loc[Portfolio_Last_Rebal.index[i-1],'PortSeries']

    Portfolio.loc[Portfolio.index[i],'PortSeries']=Portfolio_Last_Rebal.loc[Portfolio_Last_Rebal.index[i],'PortSeries']*(1+sum(Udl_Perf.iloc[i]*weights))

Thanks!

Answer 1

If you really want it to be fast then first implement it in while loop.

Second the length variable which you will use, define the type in advance using Mypy library , in this you need Python 3.5+ version installed.

Also if every iteration is unique then you can use multithreading using threading library . Get eg in this git repo