This library is an implementation of the JSON-LD specification in Python.
JSON, as specified in RFC7159, is a simple language for representing objects on the Web. Linked Data is a way of describing content across different documents or Web sites. Web resources are described using IRIs, and typically are dereferencable entities that may be used to find more information, creating a "Web of Knowledge". JSON-LD is intended to be a simple publishing method for expressing not only Linked Data in JSON, but for adding semantics to existing JSON.
JSON-LD is designed as a light-weight syntax that can be used to express Linked Data. It is primarily intended to be a way to express Linked Data in JavaScript and other Web-based programming environments. It is also useful when building interoperable Web Services and when storing Linked Data in JSON-based document storage engines. It is practical and designed to be as simple as possible, utilizing the large number of JSON parsers and existing code that is in use today. It is designed to be able to express key-value pairs, RDF data, RDFa data, Microformats data, and Microdata. That is, it supports every major Web-based structured data model in use today.
The syntax does not require many applications to change their JSON, but easily add meaning by adding context in a way that is either in-band or out-of-band. The syntax is designed to not disturb already deployed systems running on JSON, but provide a smooth migration path from JSON to JSON with added semantics. Finally, the format is intended to be fast to parse, fast to generate, stream-based and document-based processing compatible, and require a very small memory footprint in order to operate.
This library aims to conform with the following:
- JSON-LD 1.1, W3C Candidate Recommendation, 2019-12-12 or newer
- JSON-LD 1.1 Processing Algorithms and API, W3C Candidate Recommendation, 2019-12-12 or newer
- JSON-LD 1.1 Framing, W3C Candidate Recommendation, 2019-12-12 or newer
- Working Group test suite
The test runner is often updated to note or skip newer tests that are not yet supported.
PyLD can be installed with a pip package
pip install PyLDDefining a dependency on pyld will not pull in Requests or aiohttp. If you
need one of these for a Document Loader then either depend on the desired
external library directly or define the requirement as PyLD[requests] or
PyLD[aiohttp].
from pyld import jsonld
import json
doc = {
"http://schema.org/name": "Manu Sporny",
"http://schema.org/url": {"@id": "http://manu.sporny.org/"},
"http://schema.org/image": {"@id": "http://manu.sporny.org/images/manu.png"}
}
context = {
"name": "http://schema.org/name",
"homepage": {"@id": "http://schema.org/url", "@type": "@id"},
"image": {"@id": "http://schema.org/image", "@type": "@id"}
}
# compact a document according to a particular context
# see: https://json-ld.org/spec/latest/json-ld/#compacted-document-form
compacted = jsonld.compact(doc, context)
print(json.dumps(compacted, indent=2))
# Output:
# {
# "@context": {...},
# "image": "http://manu.sporny.org/images/manu.png",
# "homepage": "http://manu.sporny.org/",
# "name": "Manu Sporny"
# }
# compact using URLs
jsonld.compact('http://example.org/doc', 'http://example.org/context')
# expand a document, removing its context
# see: https://json-ld.org/spec/latest/json-ld/#expanded-document-form
expanded = jsonld.expand(compacted)
print(json.dumps(expanded, indent=2))
# Output:
# [{
# "http://schema.org/image": [{"@id": "http://manu.sporny.org/images/manu.png"}],
# "http://schema.org/name": [{"@value": "Manu Sporny"}],
# "http://schema.org/url": [{"@id": "http://manu.sporny.org/"}]
# }]
# expand using URLs
jsonld.expand('http://example.org/doc')
# flatten a document
# see: https://json-ld.org/spec/latest/json-ld/#flattened-document-form
flattened = jsonld.flatten(doc)
# all deep-level trees flattened to the top-level
# frame a document
# see: https://json-ld.org/spec/latest/json-ld-framing/#introduction
framed = jsonld.frame(doc, frame)
# document transformed into a particular tree structure per the given frame
# normalize a document using the RDF Dataset Normalization Algorithm
# (URDNA2015), see: https://www.w3.org/TR/rdf-canon/
normalized = jsonld.normalize(
doc, {'algorithm': 'URDNA2015', 'format': 'application/n-quads'})
# normalized is a string that is a canonical representation of the document
# that can be used for hashing, comparison, etc.The default document loader for PyLD uses Requests. In a production environment you may want to setup a custom loader that, at a minimum, sets a timeout value. You can also force requests to use https, set client certs, disable verification, or set other Requests parameters.
jsonld.set_document_loader(jsonld.requests_document_loader(timeout=...))An asynchronous document loader using aiohttp is also available. Please note that this document loader limits asynchronicity to fetching documents only. The processing loops remain synchronous.
jsonld.set_document_loader(jsonld.aiohttp_document_loader(timeout=...))When no document loader is specified, the default loader is set to Requests. If Requests is not available, the loader is set to aiohttp. The fallback document loader is a dummy document loader that raises an exception on every invocation.
Commercial support for this library is available upon request from Digital Bazaar: support@digitalbazaar.com.
The source code for the Python implementation of the JSON-LD API is available at:
https://github.com/digitalbazaar/pyld
This library includes a sample testing utility which may be used to verify that changes to the processor maintain the correct output.
To run the sample tests you will need to get the test suite files by cloning
the json-ld-api, json-ld-framing, and normalization repositories
hosted on GitHub:
- https://github.com/w3c/json-ld-api
- https://github.com/w3c/json-ld-framing
- https://github.com/json-ld/normalization
If the suites repositories are available as sibling directories of the PyLD source directory, then all the tests can be run with the following:
python tests/runtests.pyIf you want to test individual manifest .jsonld files or directories
containing a manifest.jsonld, then you can supply these files or
directories as arguments:
python tests/runtests.py TEST_PATH [TEST_PATH...]The test runner supports different document loaders by setting -l requests
or -l aiohttp. The default document loader is set to Requests.
An EARL report can be generated using the -e or --earl option.
