nfdi4culture

Name	nfdi4culture JSON
Version	0.3 JSON
	download
home_page	https://nfdi4culture.de/
Summary	This package provides a Python interface to the NFDI4Culture infrastructure.
upload_time	2024-05-31 13:29:21
maintainer	None
docs_url	None
author	Etienne Posthumus
requires_python	<4.0,>=3.7
license	MIT
keywords
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # 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](https://nfdi4culture.de/)

Example:

```python
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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