This package provides a Python interface to the NFDI4Culture infrastructure.
Project description
Culture Python Package
Latest schema.org : https://schema.org/version/latest/schemaorg-current-https.jsonld
NFDI4Culture
This is a placeholder for the Python tools being developed to manage the infrastructure of NFDI4Culture
Example:
from nfdi4culture import cto
from lidolator import from_file
item = cto.Item()
item.datafeed = "https://nfdi4culture.de/id/E5320"
# Or should we have cto.DataFeed("https://nfdi4culture.de/id/E5320") and the rest happens from there?
# either of the above will set things like .publisher on the Item too.
# and create the relevant schema.DataFeedItem and schema.DataFeed triples?
item.sourcefile = "http://foo.com/bar/baz.oai-pmh?id=123456"
# the update method expects a dict with key-value mappings
# the cto.Item objet knows how to map a key and value to the relevant fields.
# How do we specify this field mapping?
# And do we split it into a NamedNode/Literal difference?
item.update(from_file(filepath))
item.ntriples()
# or
item.turtle()
TODO
- JS is working on scraper
Open Discussion Points
Should we use RDFlib? While it is very much a "batteries included" package, for large datasets (which we increasingly want to create) it is just too slow.
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