vix_utils provides command line tools and a a Python API for preparing data for analysing the VIX Futures and Cash Term structures. Term Structure data can be exported to excel (.xslx), csv, and pickle formats.
It take awhile to load the data into a dataframe for the futures history, even though most of it is cached.
Any futures which are not expired, are read every time a program is run (at least the results are cached for the remainder of the program).
some logic to avoid rebuilding the dataframe, as long as all futures downloaded are current to the end of the most recent close of trading, would speed this up immensely.
I think the easiest way to to look at the last trade date in the cached data stored in skinny.pkl.
Only if the most recent close of trading is more recent that the last recorded trade date (say be 30 minutes since there will be delay before CBOE publishes the current day), then rebuild the dataframe in async_load_vix_term_structure.
It take awhile to load the data into a dataframe for the futures history, even though most of it is cached.
Any futures which are not expired, are read every time a program is run (at least the results are cached for the remainder of the program).
some logic to avoid rebuilding the dataframe, as long as all futures downloaded are current to the end of the most recent close of trading, would speed this up immensely.
I think the easiest way to to look at the last trade date in the cached data stored in skinny.pkl.
Only if the most recent close of trading is more recent that the last recorded trade date (say be 30 minutes since there will be delay before CBOE publishes the current day), then rebuild the dataframe in async_load_vix_term_structure.