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While it works, when I am in a JupyterHub instance hosted on AWS and want to grab the bestrefs from existing S3 buckets, I can't think of a way to do it without bypassing CRDS interface (e.g., manually parsing FITS header and constructing URIs for each reference file).
Currently, ASB has all HST reference files uploaded at S3://stpubdata/hst/public/references/. For example:
In an R&D effort over at https://jira.stsci.edu/browse/JUSI-8 and trying to run ACS pipeline in a notebook, I see commands like:
While it works, when I am in a JupyterHub instance hosted on AWS and want to grab the bestrefs from existing S3 buckets, I can't think of a way to do it without bypassing CRDS interface (e.g., manually parsing FITS header and constructing URIs for each reference file).
Currently, ASB has all HST reference files uploaded at
S3://stpubdata/hst/public/references/
. For example:s3://stpubdata/hst/public/references/hst_wfc3_bpixtab_0260.rmap
s3://stpubdata/hst/public/references/2ck1856fi_bpx.fits
I am wondering if it is a reasonable request to have CRDS have a "cloud" option like
astroquery.mast
does; see Python snippet in https://mast-labs.stsci.io/2018/06/hst-public-data-on-aws .cc @stscicrawford @ivastar
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