fix explicit dataset: FROM and FROM NAMED clause

When using a FROM or FROM NAMED clause: redefine entirely the query's RDF dataset.
Include only the graphs in FROM clause in the query's default graph
Include only the graphs in the FROM NAMED clause in the query's named graphs
Try to load external graphs only if they don't already exist in the given ConjunctiveGraph

rdflib/plugins/sparql/evaluate.py

@@ -661,36 +661,12 @@ def evalQuery(
         :doc:`Security Considerations </security_considerations>`
         documentation.
     """
+    main = query.algebra
 
     initBindings = dict((Variable(k), v) for k, v in (initBindings or {}).items())
 
-    ctx = QueryContext(graph, initBindings=initBindings)
+    ctx = QueryContext(graph, initBindings=initBindings, datasetClause=main.datasetClause)
 
     ctx.prologue = query.prologue
-    main = query.algebra
-
-    if main.datasetClause:
-        if ctx.dataset is None:
-            raise Exception(
-                "Non-conjunctive-graph doesn't know about "
-                + "graphs! Try a query without FROM (NAMED)."
-            )
-
-        ctx = ctx.clone()  # or push/pop?
-
-        firstDefault = False
-        for d in main.datasetClause:
-            if d.default:
-                if firstDefault:
-                    # replace current default graph
-                    dg = ctx.dataset.get_context(BNode())
-                    ctx = ctx.pushGraph(dg)
-                    firstDefault = True
-
-                ctx.load(d.default, default=True)
-
-            elif d.named:
-                g = d.named
-                ctx.load(g, default=False)
 
     return evalPart(ctx, main)

rdflib/plugins/sparql/sparql.py

@@ -255,6 +255,7 @@ def __init__(
         graph: Optional[Graph] = None,
         bindings: Optional[Union[Bindings, FrozenBindings, List[Any]]] = None,
         initBindings: Optional[Mapping[str, Identifier]] = None,
+        datasetClause=None
     ):
         self.initBindings = initBindings
         self.bindings = Bindings(d=bindings or [])
@@ -264,11 +265,25 @@ def __init__(
         self.graph: Optional[Graph]
         self._dataset: Optional[ConjunctiveGraph]
         if isinstance(graph, ConjunctiveGraph):
-            self._dataset = graph
-            if rdflib.plugins.sparql.SPARQL_DEFAULT_GRAPH_UNION:
-                self.graph = self.dataset
+            if datasetClause:
+                self._dataset = ConjunctiveGraph()
+                self.graph = Graph()
+                for d in datasetClause:
+                    if d.default:
+                        self.graph += graph.get_context(d.default)
+                        if not graph.get_context(d.default):
+                            self.load(d.default, default=True)
+                    elif d.named:
+                        namedGraphs = Graph(store=self.dataset.store, identifier=d.named)
+                        namedGraphs += graph.get_context(d.named)
+                        if not graph.get_context(d.named):
+                            self.load(d.named, default=False)
             else:
-                self.graph = self.dataset.default_context
+                self._dataset = graph
+                if rdflib.plugins.sparql.SPARQL_DEFAULT_GRAPH_UNION:
+                    self.graph = self.dataset
+                else:
+                    self.graph = self.dataset.default_context
         else:
             self._dataset = None
             self.graph = graph

test/test_sparql/test_dataset_exclusive.py

@@ -0,0 +1,57 @@
+from rdflib.graph import ConjunctiveGraph
+from rdflib.term import URIRef
+import pytest
+from typing import Generator
+from test.utils.sparql_checker import ctx_configure_rdflib
+
+graph = ConjunctiveGraph()
+# Adding into default graph
+graph.add((URIRef("urn:s0"), URIRef("urn:p0"), URIRef("urn:o0")))
+# Adding into named graphs
+graph.add((URIRef("urn:s1"), URIRef("urn:p1"), URIRef("urn:o1"), URIRef("urn:g1")))
+graph.add((URIRef("urn:s2"), URIRef("urn:p2"), URIRef("urn:o2"), URIRef("urn:g2")))
+graph.add((URIRef("urn:s3"), URIRef("urn:p3"), URIRef("urn:o3"), URIRef("urn:g3")))
+
+
+# Set SPARQL_DEFAULT_GRAPH_UNION to false to make dataset inclusive
+# Set it back at the end of the test
+@pytest.fixture(scope="module", autouse=True)
+def configure_rdflib() -> Generator[None, None, None]:
+    with ctx_configure_rdflib():
+        yield None
+
+
+# Test implicit exlusive dataset
+def test_exclusive():
+    results = list(graph.query("SELECT ?s ?p ?o WHERE {?s ?p ?o}"))
+    assert results == [(URIRef('urn:s0'), URIRef('urn:p0'), URIRef('urn:o0'))]
+
+
+# Test explicit default graph with exclusive dataset
+def test_from():
+    results = list(graph.query("SELECT ?s ?p ?o FROM <urn:g1> WHERE {?s ?p ?o}"))
+    assert results == [(URIRef('urn:s1'), URIRef('urn:p1'), URIRef('urn:o1'))]
+
+
+# Test explicit named graphs with exclusive dataset
+def test_from_named():
+    results = list(graph.query("SELECT ?g ?s ?p ?o FROM NAMED <urn:g1> WHERE {graph ?g {?s ?p ?o}}"))
+    assert results == [(URIRef('urn:g1'), URIRef('urn:s1'), URIRef('urn:p1'), URIRef('urn:o1'))]
+
+
+# Test that we can use from and from named in the same query
+def test_from_and_from_named():
+    query = """
+        SELECT ?g ?s ?p ?o
+        FROM <urn:g1>
+        FROM NAMED <urn:g2>
+        WHERE {
+            {?s ?p ?o}
+            UNION {graph ?g {?s ?p ?o}}
+        } ORDER BY ?s
+    """
+    results = list(graph.query(query))
+    assert results == [
+        (None, URIRef('urn:s1'), URIRef('urn:p1'), URIRef('urn:o1')),
+        (URIRef('urn:g2'), URIRef('urn:s2'), URIRef('urn:p2'), URIRef('urn:o2'))
+        ]

test/test_sparql/test_dataset_inclusive.py

@@ -0,0 +1,91 @@
+from rdflib.graph import ConjunctiveGraph
+from rdflib.term import URIRef
+
+graph = ConjunctiveGraph()
+# Adding into default graph
+graph.add((URIRef("urn:s0"), URIRef("urn:p0"), URIRef("urn:o0")))
+# Adding into named graphs
+graph.add((URIRef("urn:s1"), URIRef("urn:p1"), URIRef("urn:o1"), URIRef("urn:g1")))
+graph.add((URIRef("urn:s2"), URIRef("urn:p2"), URIRef("urn:o2"), URIRef("urn:g2")))
+graph.add((URIRef("urn:s3"), URIRef("urn:p3"), URIRef("urn:o3"), URIRef("urn:g3")))
+
+
+# Test implicit inclusive dataset
+# As an inclusive dataset, the default graph should contain a merge of all graphs:
+# The default graph  + all the named graphs
+def test_inclusive():
+    results = list(graph.query("SELECT ?s ?p ?o WHERE {?s ?p ?o} ORDER BY ?s"))
+    assert results == [
+        (URIRef('urn:s0'), URIRef('urn:p0'), URIRef('urn:o0')),
+        (URIRef('urn:s1'), URIRef('urn:p1'), URIRef('urn:o1')),
+        (URIRef('urn:s2'), URIRef('urn:p2'), URIRef('urn:o2')),
+        (URIRef('urn:s3'), URIRef('urn:p3'), URIRef('urn:o3'))
+        ]
+
+
+# Test explicit default graph with inclusive dataset
+def test_default_from_1():
+    results = list(graph.query("SELECT ?s ?p ?o FROM <urn:g1> WHERE {?s ?p ?o}"))
+    assert results == [(URIRef('urn:s1'), URIRef('urn:p1'), URIRef('urn:o1'))]
+
+
+# test that we include more than one graph into the default graph
+def test_default_from_2():
+    results = list(graph.query("SELECT ?s ?p ?o FROM <urn:g1> FROM <urn:g2> WHERE {?s ?p ?o} ORDER BY ?s"))
+    assert results == [
+        (URIRef('urn:s1'), URIRef('urn:p1'), URIRef('urn:o1')),
+        (URIRef('urn:s2'), URIRef('urn:p2'), URIRef('urn:o2'))
+        ]
+
+
+# Since there is a FROM clause, we consider RDF dataset explicit
+# Thus if FROM NAMED is not defined, named graph is considered empty set
+def test_named_from():
+    results = list(graph.query("SELECT ?s ?p ?o FROM <urn:g1> WHERE {graph ?g {?s ?p ?o}} ORDER BY ?s"))
+    assert results == [], "no result expected"
+
+
+# Test explicit named graphs with inclusive dataset
+def test_named_from_named_1():
+    results = list(graph.query("SELECT ?g ?s ?p ?o FROM NAMED <urn:g1> WHERE {graph ?g {?s ?p ?o}}"))
+    assert results == [(URIRef('urn:g1'), URIRef('urn:s1'), URIRef('urn:p1'), URIRef('urn:o1'))]
+
+
+# test that we include more than one graph into the named graphs
+def test_named_from_named_2():
+    query = """
+    SELECT ?g ?s ?p ?o
+    FROM NAMED <urn:g1>
+    FROM NAMED <urn:g2>
+    WHERE {
+        graph ?g {?s ?p ?o}
+    } ORDER BY ?g
+    """
+    results = list(graph.query(query))
+    assert results == [
+        (URIRef('urn:g1'), URIRef('urn:s1'), URIRef('urn:p1'), URIRef('urn:o1')),
+        (URIRef('urn:g2'), URIRef('urn:s2'), URIRef('urn:p2'), URIRef('urn:o2'))
+        ]
+
+# Since there is a FROM NAMED clause, we consider RDF dataset explicit
+# Thus if FROM is not defined, default graph is considered empty
+def test_default_from_named():
+    results = list(graph.query("SELECT ?g ?s ?p ?o FROM NAMED <urn:g1> WHERE {?s ?p ?o}"))
+    assert results == [], "no result expected"
+
+
+def test_from_and_from_named():
+    query = """
+        SELECT ?g ?s ?p ?o
+        FROM <urn:g1>
+        FROM NAMED <urn:g2>
+        WHERE {
+            {?s ?p ?o}
+            UNION {graph ?g {?s ?p ?o}}
+        } ORDER BY ?s
+    """
+    results = list(graph.query(query))
+    assert results == [
+        (None, URIRef('urn:s1'), URIRef('urn:p1'), URIRef('urn:o1')),
+        (URIRef('urn:g2'), URIRef('urn:s2'), URIRef('urn:p2'), URIRef('urn:o2'))
+        ]