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# -*- coding: utf-8 -*-
#
#
# $Date: 2005/11/04 14:06:36 $, by $Author: ivan $, $Revision: 1.1 $
# The documentation of the module, hence the convention for the documentation of methods and classes,
# is based on the epydoc tool. This tool parses Python source files
# and generates API descriptions XHTML.
# The latest release of epydoc (version 2.0) can be
# downloaded from the <a href="http://sourceforge.net/project/showfiles.php?group_id=32455">SourceForge
# download page</a>.
#
#
"""
TODO: merge this first bit from sparql.sparql.py into rest of doc... updating all along the way.
SPARQL implementation on top of RDFLib
Implementation of the <a href="http://www.w3.org/TR/rdf-sparql-query/">W3C SPARQL</a>
language (version April 2005). The basic class here is
supposed to be a superclass of L{rdflib.sparql.sparqlGraph}; it has
been separated only for a better maintainability.
There is a separate
U{description<http://dev.w3.org/cvsweb/%7Echeckout%7E/2004/PythonLib-IH/Doc/sparqlDesc.html>}
for the functionalities.
For a general description of the SPARQL API, see the separate, more
complete
U{description<http://dev.w3.org/cvsweb/%7Echeckout%7E/2004/PythonLib-IH/Doc/sparqlDesc.html>}.
Variables, Imports
==================
The top level (__init__.py) module of the Package imports the
important classes. In other words, the user may choose to use the
following imports only::
from rdflibUtils import myTripleStore
from rdflibUtils import retrieveRDFFiles
from rdflibUtils import SPARQLError
from rdflibUtils import GraphPattern
The module imports and/or creates some frequently used Namespaces, and
these can then be imported by the user like::
from rdflibUtils import ns_rdf
Finally, the package also has a set of convenience string defines for
XML Schema datatypes (ie, the URI-s of the datatypes); ie, one can
use::
from rdflibUtils import type_string
from rdflibUtils import type_integer
from rdflibUtils import type_long
from rdflibUtils import type_double
from rdflibUtils import type_float
from rdflibUtils import type_decimal
from rdflibUtils import type_dateTime
from rdflibUtils import type_date
from rdflibUtils import type_time
from rdflibUtils import type_duration
These are used, for example, in the sparql-p implementation.
The three most important classes in RDFLib for the average user are
Namespace, URIRef and Literal; these are also imported, so the user
can also use, eg::
from rdflibUtils import Namespace, URIRef, Literal
History
=======
- Version 1.0: based on an earlier version of the SPARQL, first
released implementation
- Version 2.0: version based on the March 2005 SPARQL document, also
a major change of the core code (introduction of the separate
L{GraphPattern<rdflibUtils.graphPattern.GraphPattern>} class, etc).
- Version 2.01: minor changes only: - switch to epydoc as a
documentation tool, it gives a much better overview of the classes -
addition of the SELECT * feature to sparql-p
- Version 2.02: - added some methods to
L{myTripleStore<rdflibUtils.myTripleStore.myTripleStore>} to handle
C{Alt} and C{Bag} the same way as C{Seq} - added also methods to
I{add} collections and containers to the triple store, not only
retrieve them
- Version 2.1: adapted to the inclusion of the code into rdflib, thanks to Michel Pelletier
- Version 2.2: added the sorting possibilities; introduced the Unbound class and have a better
interface to patterns using this (in the BasicGraphPattern class)
@author: U{Ivan Herman<http://www.ivan-herman.net>}
@license: This software is available for use under the
U{W3C Software License<http://www.w3.org/Consortium/Legal/2002/copyright-software-20021231>}
@contact: Ivan Herman, ivan@ivan-herman.net
@version: 2.2
"""
from rdflib import URIRef
DESCRIBE=URIRef('http://www.w3.org/TR/rdf-sparql-query/#describe')
__version__ = "2.2"
Debug = False
# Note that the SPARQL draft allows the usage of a different query character, but I decided not to be that
# generous, and keep to one only. I put it into a separate variable to avoid problems if the group decides
# to change the syntax on that detail...
_questChar = "?"
def generateCollectionConstraint(triplets,collection,item) :
"""
Generate a function that can then be used as a global constaint in
sparql to check whether the 'item' is an element of the
'collection' (a.k.a. list). Both collection and item can be a real
resource or a query string. Furthermore, item might be a plain
string, that is then turned into a literal run-time.
The function returns an adapted filter method that can then be
plugged into a sparql request.
@param triplets: the
L{SPARQLGraph<sparqlGraph.SPARQLGraph>} instance
@param collection: is either a query string (that has to be bound
by the query) or an RDFLib Resource representing the collection
@param item: is either a query string (that has to be bound by the
query) or an RDFLib Resource that must be tested to be part of the
collection
@rtype: a function suitable as a sparql filter
@raises SPARQLError: if the collection or the
item parameters are illegal (not valid resources for a collection
or an object)
"""
return isOnCollection(collection,item, triples)
############################################################################################
class Processor(object):
def __init__(self, graph):
pass
def query(self, strOrQuery, initBindings={}, initNs={}, DEBUG=False):
pass
from rdflib.exceptions import Error
##
# SPARQL Error Exception (subclass of the RDFLib Exceptions)
class SPARQLError(Error) :
"""Am SPARQL error has been detected"""
def __init__(self,msg):
Error.__init__(self, ("SPARQL Error: %s." % msg))
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