{ "info": { "author": "Daniel Rech", "author_email": "dr@netsyno.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Environment :: Web Environment", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5" ], "description": "Ldtools\n=======\n\nLdtools is a simple library to handle RDF data in a convenient way.\nIt can be used as a simple ORM for Linked Data Resources and their Origins.\nA resource \"http://dbpedia.org/resource/Karlsruhe\" might be mentioned by different origins.\nLdtools helps to keep track of verified statements (authoritative) about resources and provides an API to query more information about resources.\n\nDifferent rdf triple storage backends are provided for the retrieved data: RestBackend, FileBackend or MemoryBackend\n\nThe CLI ldtools can be used to retrieve information about linked data resources.\n\n\n\nInstallation\n------------\n\nJust use pip::\n\n pip install Ldtools\n\nThis will install all dependencies (argparse, rdflib) needed and provide the command line utility \"ldtools\".\n\nAlternatively, do a git clone and execute python setup.py install/develop.\n\n\n\nHow to use it?\n--------------\n\nVia the commandline, all information within a Linked Data resource can be retrieved by executing::\n\n ldtools http://dbpedia.org/resource/Karlsruhe\n\nFurther options can be utilised to influence whether the URIs that are discovered within the origin should be followed and how deep. Try::\n\n ldtools --help\n\nfor more usage information.\n\nAlternatively, the python console can be used:\n\nFirst, we create an Origin object::\n\n import pprint, rdflib\n from ldtools.resource import Resource\n from ldtools.origin import Origin\n\n uri = \"http://dbpedia.org/resource/Karlsruhe\"\n origin, created = Origin.objects.get_or_create(uri)\n\nProcess it, hopefully discovering more Origins in there (rdfs:seeAlso, owl:sameAs...)::\n\n origin.GET(only_follow_uris=[rdflib.OWL.sameAs,rdflib.RDFS.seeAlso])\n\nIf everything went well, there now is a Resource object for our uri::\n\n resource, created = Resource.objects.get_or_create(uri, origin=origin)\n pprint.pprint(resource.__dict__)\n\nProcess all the other Origins we know about::\n\n Origin.objects.GET_all()\n\nResult: 5 URIs crawled and 500 Resources discovered and processed.\n\n\nWhy?\n----\n\n* The Semantic Web is out there and there is really not enough tools yet to work with Linked Data\n* SPARQL is not needed to get the RAW data from resources, this library demonstrates that. 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