dataset re-work for 7.0 release

docs/intro_to_parsing.rst

@@ -116,8 +116,8 @@ Working with multi-graphs
 -------------------------
 
 To read and query multi-graphs, that is RDF data that is context-aware, you need to use rdflib's
-:class:`rdflib.ConjunctiveGraph` or :class:`rdflib.Dataset` class. These are extensions to :class:`rdflib.Graph` that
-know all about quads (triples + graph IDs).
+:class:`rdflib.Dataset` class. This is an extension to :class:`rdflib.Graph` that know all about
+quads (triples + graph IDs).
 
 If you had this multi-graph data file (in the ``trig`` format, using new-style ``PREFIX`` statement (not the older
 ``@prefix``):

docs/merging.rst

@@ -25,7 +25,7 @@ In RDFLib, blank nodes are given unique IDs when parsing, so graph merging can b
 ``graph`` now contains the merged graph of ``input1`` and ``input2``. 
 
 
-.. note:: However, the set-theoretic graph operations in RDFLib are assumed to be performed in sub-graphs of some larger data-base (for instance, in the context of a :class:`~rdflib.graph.ConjunctiveGraph`) and assume shared blank node IDs, and therefore do NOT do *correct* merging, i.e.:: 
+.. note:: However, the set-theoretic graph operations in RDFLib are assumed to be performed in sub-graphs of some larger data-base (for instance, in the context of a :class:`~rdflib.graph.Dataset`) and assume shared blank node IDs, and therefore do NOT do *correct* merging, i.e.:: 
 
 		  from rdflib import Graph
 

docs/persistence.rst

@@ -37,7 +37,7 @@ In most cases, passing the name of the store to the Graph constructor is enough:
 
 
 Most stores offering on-disk persistence will need to be opened before reading or writing.
-When peristing a triplestore, rather than a ConjuntiveGraph quadstore, you need to specify
+When peristing a triplestore, rather than a Dataset quadstore, you need to specify
 an identifier with which you can open the graph:
 
 .. code-block:: python
@@ -73,6 +73,7 @@ More store implementations are available in RDFLib extension projects:
  * `rdflib-sqlalchemy <https://github.com/RDFLib/rdflib-sqlalchemy>`_, which supports stored on a wide-variety of RDBMs backends, 
  * `rdflib-leveldb <https://github.com/RDFLib/rdflib-leveldb>`_ - a store on to of Google's `LevelDB <https://code.google.com/p/leveldb/>`_ key-value store. 
  * `rdflib-kyotocabinet <https://github.com/RDFLib/rdflib-kyotocabinet>`_ - a store on to of the `Kyoto Cabinet <http://fallabs.com/kyotocabinet/>`_ key-value store. 
+ * `rdflib-sqlitelsm <https://github.com/RDFLib/rdflib-sqlitelsm>`_ - a store on to of the `SQLite LSM <https://sqlite.org/src4/doc/trunk/www/lsm.wiki>`_ key-value store. 
 
 Example
 ^^^^^^^

docs/plugin_parsers.rst

@@ -33,15 +33,15 @@ xml       :class:`~rdflib.plugins.parsers.rdfxml.RDFXMLParser`
 
 Multi-graph IDs
 ---------------
-Note that for correct parsing of multi-graph data, e.g. Trig, HexT, etc., into a ``ConjunctiveGraph`` or a ``Dataset``,
-as opposed to a context-unaware ``Graph``, you will need to set the ``publicID`` of the ``ConjunctiveGraph`` a 
-``Dataset`` to the identifier of the ``default_context`` (default graph), for example::
+Note that for correct parsing of multi-graph data, e.g. Trig, HexT, etc., into a a ``Dataset``,
+as opposed to a context-unaware ``Graph``, you will need to set the ``publicID`` of the  
+``Dataset`` to the identifier of the ``default_graph``, for example::
 
     d = Dataset()
     d.parse(
         data=""" ... """, 
         format="trig", 
-        publicID=d.default_context.identifier
+        publicID=d.default_graph.identifier
     )
 
 (from the file tests/test_serializer_hext.py)

examples/berkeleydb_example.py

@@ -3,7 +3,7 @@
 
 Example 1: simple actions
 
-* creating a ConjunctiveGraph using the BerkeleyDB Store
+* creating a Dataset using the BerkeleyDB Store
 * adding triples to it
 * counting them
 * closing the store, emptying the graph
@@ -16,17 +16,17 @@
 * does not delete the DB at the end so you can see it on disk
 """
 import os
-from rdflib import ConjunctiveGraph, Namespace, Literal
+from rdflib import Dataset, Namespace, Literal
 from rdflib.store import NO_STORE, VALID_STORE
 from tempfile import mktemp
 
 
 def example_1():
-    """Creates a ConjunctiveGraph and performs some BerkeleyDB tasks with it"""
+    """Creates a Dataset and performs some BerkeleyDB tasks with it"""
     path = mktemp()
 
     # Declare we are using a BerkeleyDB Store
-    graph = ConjunctiveGraph("BerkeleyDB")
+    graph = Dataset("BerkeleyDB")
 
     # Open previously created store, or create it if it doesn't exist yet
     # (always doesn't exist in this example as using temp file location)
@@ -64,7 +64,7 @@ def example_1():
     graph = None
 
     # reopen the graph
-    graph = ConjunctiveGraph("BerkeleyDB")
+    graph = Dataset("BerkeleyDB")
 
     graph.open(path, create=False)
 
@@ -103,7 +103,7 @@ def example_2():
     import json
     import base64
 
-    g = ConjunctiveGraph("BerkeleyDB")
+    g = Dataset("BerkeleyDB")
     g.open("gsg_vocabs", create=True)
 
     # gsq_vocabs = "https://api.github.com/repos/geological-survey-of-queensland/vocabularies/git/trees/master"

examples/conjunctive_graphs.py

@@ -1,6 +1,6 @@
 """
-An RDFLib ConjunctiveGraph is an (unnamed) aggregation of all the Named Graphs
-within a Store. The :meth:`~rdflib.graph.ConjunctiveGraph.get_context`
+An RDFLib Dataset is a means of working with a set of Named Graphs
+within a Store. The :meth:`~rdflib.graph.Dataset.graph`
 method can be used to get a particular named graph for use, such as to add
 triples to, or the default graph can be used.
 
@@ -9,10 +9,10 @@
 """
 
 from rdflib import Namespace, Literal, URIRef
-from rdflib.graph import Graph, ConjunctiveGraph
+from rdflib.graph import Graph, Dataset
 from rdflib.plugins.stores.memory import Memory
 
-if __name__ == "__main__":
+def test_dataset_example():
 
     LOVE = Namespace("http://love.com#")
     LOVERS = Namespace("http://love.com/lovers/")
@@ -25,25 +25,25 @@
 
     store = Memory()
 
-    g = ConjunctiveGraph(store=store)
+    g = Dataset(store=store, default_union=True)
     g.bind("love", LOVE)
     g.bind("lovers", LOVERS)
 
     # Add a graph containing Mary's facts to the Conjunctive Graph
-    gmary = Graph(store=store, identifier=cmary)
+    gmary = g.graph(cmary)
     # Mary's graph only contains the URI of the person she loves, not his cute name
     gmary.add((mary, LOVE.hasName, Literal("Mary")))
     gmary.add((mary, LOVE.loves, john))
 
     # Add a graph containing John's facts to the Conjunctive Graph
-    gjohn = Graph(store=store, identifier=cjohn)
+    gjohn = g.graph(cjohn)
     # John's graph contains his cute name
     gjohn.add((john, LOVE.hasCuteName, Literal("Johnny Boy")))
 
     # Enumerate contexts
     print("Contexts:")
     for c in g.contexts():
-        print(f"-- {c.identifier} ")
+        print(f"-- {c} ")
     print("===================")
     # Separate graphs
     print("John's Graph:")
@@ -63,3 +63,7 @@
         xx = x
     print("Q: Who does Mary love?")
     print("A: Mary loves {}".format(xx))
+
+if __name__ == "__main__":
+    test_dataset_example()
+

examples/datasets.py

@@ -1,9 +1,9 @@
 """
-An RDFLib Dataset is a slight extension to ConjunctiveGraph: it uses simpler terminology
+An RDFLib Dataset uses simpler terminology than the old ConjunctiveGraph
 and has a few additional convenience method extensions, for example add() can be used to
 add quads directly to a specific Graph within the Dataset.
 
-This example file shows how to decalre a Dataset, add content to it, serialise it, query it
+This example file shows how to declare a Dataset, add content to it, serialise it, query it
 and remove things from it.
 """
 

examples/swap_primer.py

@@ -5,7 +5,7 @@
 http://www.w3.org/2000/10/swap/Primer
 """
 
-from rdflib import ConjunctiveGraph, Namespace, Literal
+from rdflib import Dataset, Namespace, Literal
 from rdflib.namespace import OWL, DC
 
 if __name__ == "__main__":
@@ -14,7 +14,7 @@
     # Here we create a "Graph" of our work.
     # Think of it as a blank piece of graph paper!
 
-    primer = ConjunctiveGraph()
+    primer = Dataset()
     myNS = Namespace("https://example.com/")
 
     primer.add((myNS.pat, myNS.knows, myNS.jo))
@@ -59,7 +59,7 @@
     # with a fresh new graph.
 
     del primer
-    primer = ConjunctiveGraph()
+    primer = Dataset(default_union=True)
 
     # Lets start with a verbatim string straight from the primer text:
 
@@ -117,7 +117,7 @@
 
     print()
     print("Printing bigger example's triples:")
-    for i in [(x, y, z) for x, y, z in primer]:
+    for i in [(x, y, z, c) for x, y, z, c in primer]:
         print(i)
 
     # or spit it back out (mostly) the way we created it:

examples/transitive.py

@@ -44,7 +44,7 @@
 """
 
 if __name__ == "__main__":
-    from rdflib import ConjunctiveGraph, URIRef
+    from rdflib import Dataset, URIRef
 
     person = URIRef("ex:person")
     dad = URIRef("ex:d")
@@ -56,7 +56,7 @@
 
     parent = URIRef("ex:parent")
 
-    g = ConjunctiveGraph()
+    g = Dataset()
     g.add((person, parent, dad))
     g.add((person, parent, mom))
     g.add((dad, parent, momOfDad))