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import json
from rdflib import BNode, ConjunctiveGraph
from rdflib.compare import isomorphic
from rdflib.parser import InputSource
from rdflib.plugins.parsers.jsonld import JsonLDParser, to_rdf
# monkey-patch N-Quads parser via it's underlying W3CNTriplesParser to keep source bnode id:s ..
from rdflib.plugins.parsers.ntriples import W3CNTriplesParser, r_nodeid
from rdflib.plugins.serializers.jsonld import from_rdf
from rdflib.plugins.shared.jsonld.keys import CONTEXT, GRAPH
def _preserving_nodeid(self, bnode_context=None):
if not self.peek("_"):
return False
return BNode(self.eat(r_nodeid).group(1))
DEFAULT_PARSER_VERSION = 1.0
def make_fake_urlinputsource(input_uri, format=None, suite_base=None, options={}):
local_url = input_uri.replace("https://w3c.github.io/json-ld-api/tests/", "./")
if (index := local_url.find("#")) > -1:
# Strip off the optional fragment identifier
local_url = local_url[0:index]
try:
f = open(local_url, "rb")
except FileNotFoundError:
f = None
source = InputSource(input_uri)
source.setPublicId(input_uri)
source.setByteStream(f)
source.url = input_uri
source.links = []
if local_url.endswith((".jsonld", ".jldt")):
source.content_type = "application/ld+json"
elif local_url.endswith(".html"):
source.content_type = "text/html"
else:
source.content_type = "application/json"
source.format = format
if options:
if "httpLink" in options:
source.links.append(options["httpLink"])
if "contentType" in options:
source.content_type = options["contentType"]
if "redirectTo" in options:
redir = suite_base + options["redirectTo"]
local_redirect = redir.replace(
"https://w3c.github.io/json-ld-api/tests/", "./"
)
if f:
f.close()
try:
f = open(local_redirect, "rb")
except FileNotFoundError:
f = None
source.setByteStream(f)
source.url = redir
source.setPublicId(redir)
source.setSystemId(redir)
return source
def do_test_json(suite_base, cat, num, inputpath, expectedpath, context, options):
input_uri = suite_base + inputpath
input_graph = ConjunctiveGraph()
if cat == "remote-doc":
input_src = make_fake_urlinputsource(
input_uri, format="json-ld", suite_base=suite_base, options=options
)
p = JsonLDParser()
p.parse(
input_src,
input_graph,
base=input_src.getPublicId(),
context_data=context,
generalized_rdf=True,
)
else:
input_obj = _load_json(inputpath)
to_rdf(
input_obj,
input_graph,
base=input_uri,
context_data=context,
generalized_rdf=True,
)
expected_json = _load_json(expectedpath)
use_native_types = True # CONTEXT in input_obj
result_json = from_rdf(
input_graph,
context,
base="./", # deliberately set base different to the input base
use_native_types=options.get("useNativeTypes", use_native_types),
use_rdf_type=options.get("useRdfType", False),
)
def _prune_json(data):
if CONTEXT in data:
data.pop(CONTEXT)
if GRAPH in data:
data = data[GRAPH]
# def _remove_empty_sets(obj):
return data
expected_json = _prune_json(expected_json)
result_json = _prune_json(result_json)
_compare_json(expected_json, result_json)
def do_test_parser(suite_base, cat, num, inputpath, expectedpath, context, options):
input_uri = suite_base + inputpath
input_obj = _load_json(inputpath)
old_nodeid = W3CNTriplesParser.nodeid
# monkey patch nodeid fn in NTriplesParser
W3CNTriplesParser.nodeid = _preserving_nodeid
try:
expected_graph = _load_nquads(expectedpath)
finally:
W3CNTriplesParser.nodeid = old_nodeid
result_graph = ConjunctiveGraph()
requested_version = options.get("specVersion")
version = DEFAULT_PARSER_VERSION
if requested_version:
if requested_version == "json-ld-1.1":
version = 1.1
elif requested_version == "json-ld-1.0":
version = 1.0
if cat == "remote-doc":
input_src = make_fake_urlinputsource(
input_uri, format="json-ld", options=options
)
p = JsonLDParser()
p.parse(
input_src,
result_graph,
base=input_uri,
context_data=context,
generalized_rdf=True,
)
else:
to_rdf(
input_obj,
result_graph,
context_data=context,
base=options.get("base", input_uri),
version=version,
generalized_rdf=options.get("produceGeneralizedRdf", False),
)
assert isomorphic(result_graph, expected_graph), "Expected:\n%s\nGot:\n%s" % (
expected_graph.serialize(),
result_graph.serialize(),
)
def do_test_serializer(suite_base, cat, num, inputpath, expectedpath, context, options):
input_uri = suite_base + inputpath
old_nodeid = W3CNTriplesParser.nodeid
# monkey patch nodeid fn in NTriplesParser
W3CNTriplesParser.nodeid = _preserving_nodeid
try:
input_graph = _load_nquads(inputpath)
finally:
W3CNTriplesParser.nodeid = old_nodeid
expected_json = _load_json(expectedpath)
result_json = from_rdf(
input_graph,
context,
base=input_uri,
use_native_types=options.get("useNativeTypes", False),
use_rdf_type=options.get("useRdfType", False),
)
_compare_json(expected_json, result_json)
def do_test_html(suite_base, cat, num, inputpath, expectedpath, context, options):
input_uri = suite_base + inputpath
input_graph = ConjunctiveGraph()
input_src = make_fake_urlinputsource(
input_uri, format="json-ld", suite_base=suite_base, options=options
)
context = _load_json(context) if context else context
# Get test options from the manifest
base = options.get("base", input_src.getPublicId())
extract_all_scripts = options.get("extractAllScripts", False)
p = JsonLDParser()
p.parse(
input_src,
input_graph,
base=base,
context=context,
generalized_rdf=True,
extract_all_scripts=extract_all_scripts,
)
if expectedpath.endswith(".nq"):
expected_graph = _load_nquads(expectedpath)
elif expectedpath.endswith(".jsonld"):
expected_graph = ConjunctiveGraph()
with open(expectedpath) as f:
data = f.read()
expected_graph.parse(data=data, format="json-ld")
# TODO: Change test from graph comparison to json comparison
# The html test cases combine testing for JSON-LD extraction from the HTML
# along with testing for other algorithms (compact/flatten), which we do
# not currently support. In order to test extraction only, we currently
# perform a graph comparison. Consider changing this to a json comparison
# once the processing algorithms are implemented.
assert isomorphic(input_graph, expected_graph), "Expected:\n%s\nGot:\n%s" % (
expected_graph.serialize(),
input_graph.serialize(),
)
def _load_nquads(source):
graph = ConjunctiveGraph()
with open(source) as f:
data = f.read()
graph.parse(data=data, format="nquads")
return graph
def _load_json(source):
with open(source) as f:
return json.load(f)
def _to_ordered(obj):
if isinstance(obj, list):
# NOTE: use type in key to handle mixed
# lists of e.g. bool, int, float.
return sorted(
(_to_ordered(lv) for lv in obj),
key=lambda x: (_ord_key(x), type(x).__name__),
)
if not isinstance(obj, dict):
return obj
return sorted((k, _to_ordered(v)) for k, v in obj.items())
def _ord_key(x):
if isinstance(x, dict) and "@id" in x:
return x["@id"]
else:
return x
def _dump_json(obj):
return json.dumps(
obj, indent=2, separators=(",", ": "), sort_keys=True, check_circular=True
)
def _compare_json(expected, result):
expected = json.loads(_dump_json(expected))
result = json.loads(_dump_json(result))
assert _to_ordered(expected) == _to_ordered(
result
), "Expected JSON:\n%s\nGot:\n%s" % (_dump_json(expected), _dump_json(result))
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