[jmuhlich]

Hi Andrew! Looking into similar requirements I came across Feather and fst. They both basically let you efficiently slice into compressed on-disk DataFrames. Feather already supports Python, but fst is just for C++ and R at the moment.

https://blog.rstudio.com/2016/03/29/feather/

http://www.fstpackage.org/ https://github.com/fstpackage/fstlib

[dalke]

Thanks Jeremy. I looked at Feature, and the underlying Arrow format, but couldn't figure out how to implement a row-id-label-to-row-index dictionary. The only "dictionary" I saw was for categorical data.

I had the same issue with fstlib - how do I handle id lookups?

Any pointers?

[jmuhlich]

Sorry, I thought Feather supported random row access but it turns out it only supports random column access.

For fst, I only played with the R interface, which would be called like this to retrieve row 12345 from the "fingerprint" column:

  read_fst("library.fst", columns="fingerprint", from=12345, to=12345)

However fst didn't offer a raw/binary column datatype last I checked, which is frustrating. It has chr (string) but R can't have embedded NUL bytes in strings, so that was a dead-end for efficient storage of binary fingerprints for R. I didn't check if the underlying fstlib structures accept NULs in string columns.

[dalke]

Thanks for confirming that. Looks like I'll need to look elsewhere for the next chemfp fingerprint file format.

[jdnier]

Latest info on Feather and related pyarrow: http://arrow.apache.org/docs/python/ipc.html#feather-format