SPARQL Endpoint interface to Python¶
About¶
SPARQLWrapper is a simple Python wrapper around a SPARQL service to remotelly execute your queries. It helps in creating the query invokation and, possibly, convert the result into a more manageable format.
Installation & Distribution¶
You can install SPARQLWrapper from PyPi:
$ pip install sparqlwrapper
You can install SPARQLWrapper from GitHub:
$ pip install git+https://github.com/rdflib/sparqlwrapper#egg=sparqlwrapper
You can install SPARQLWrapper from Debian:
$ sudo apt-get install python-sparqlwrapper
Note
Be aware that there could be a gap between the latest version of SPARQLWrapper and the version available as Debian package.
Also, the source code of the package can be downloaded
in .zip
and .tar.gz
formats from GitHub SPARQLWrapper releases.
Documentation is included in the distribution.
How to use¶
First steps¶
The simplest usage of this module looks as follows (using the default, ie, XML return format, and special URI for the SPARQL Service):
from SPARQLWrapper import SPARQLWrapper
queryString = "SELECT * WHERE { ?s ?p ?o. }"
sparql = SPARQLWrapper("http://example.org/sparql")
sparql.setQuery(queryString)
try :
ret = sparql.query()
# ret is a stream with the results in XML, see <http://www.w3.org/TR/rdf-sparql-XMLres/>
except :
deal_with_the_exception()
If SPARQLWrapper("http://example.org/sparql",returnFormat=SPARQLWrapper.JSON)
was used, the result would be in
JSON format instead of XML.
SELECT example¶
from SPARQLWrapper import SPARQLWrapper, JSON
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
sparql.setQuery("""
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
WHERE { <http://dbpedia.org/resource/Asturias> rdfs:label ?label }
""")
sparql.setReturnFormat(JSON)
results = sparql.query().convert()
for result in results["results"]["bindings"]:
print(result["label"]["value"])
print('---------------------------')
for result in results["results"]["bindings"]:
print('%s: %s' % (result["label"]["xml:lang"], result["label"]["value"]))
ASK example¶
from SPARQLWrapper import SPARQLWrapper, XML
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
sparql.setQuery("""
ASK WHERE {
<http://dbpedia.org/resource/Asturias> rdfs:label "Asturias"@es
}
""")
sparql.setReturnFormat(XML)
results = sparql.query().convert()
print(results.toxml())
CONSTRUCT example¶
from SPARQLWrapper import SPARQLWrapper, RDFXML
from rdflib import Graph
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
sparql.setQuery("""
PREFIX dbo: <http://dbpedia.org/ontology/>
PREFIX schema: <http://schema.org/>
CONSTRUCT {
?lang a schema:Language ;
schema:alternateName ?iso6391Code .
}
WHERE {
?lang a dbo:Language ;
dbo:iso6391Code ?iso6391Code .
FILTER (STRLEN(?iso6391Code)=2) # to filter out non-valid values
}
""")
sparql.setReturnFormat(RDFXML)
results = sparql.query().convert()
print(results.serialize(format='xml'))
DESCRIBE example¶
from SPARQLWrapper import SPARQLWrapper, N3
from rdflib import Graph
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
sparql.setQuery("""
DESCRIBE <http://dbpedia.org/resource/Asturias>
""")
sparql.setReturnFormat(N3)
results = sparql.query().convert()
g = Graph()
g.parse(data=results, format="n3")
print(g.serialize(format='n3'))
SPARQL UPDATE example¶
from SPARQLWrapper import SPARQLWrapper, POST, DIGEST
sparql = SPARQLWrapper("https://example.org/sparql-auth")
sparql.setHTTPAuth(DIGEST)
sparql.setCredentials("login", "password")
sparql.setMethod(POST)
sparql.setQuery("""
WITH <http://example.graph>
DELETE
{ <http://dbpedia.org/resource/Asturias> rdfs:label "Asturies"@ast }
""")
results = sparql.query()
print results.response.read()
SPARQLWrapper2 example¶
There is also a SPARQLWrapper2
class that works with JSON SELECT
results only and wraps the results to make processing of average queries
a bit simpler.
from SPARQLWrapper import SPARQLWrapper2
sparql = SPARQLWrapper2("http://dbpedia.org/sparql")
sparql.setQuery("""
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
WHERE { <http://dbpedia.org/resource/Asturias> rdfs:label ?label }
""")
for result in sparql.query().bindings:
print('%s: %s' % (result["label"].lang, result["label"].value))
Return formats¶
The expected return formats differs from the query type (SELECT
, ASK
, CONSTRUCT
, DESCRIBE
…).
Note
From the SPARQL specification, The response body of a successful query operation with a 2XX response is either:
SELECT
andASK
: a SPARQL Results Document in XML, JSON, or CSV/TSV format.DESCRIBE
andCONSTRUCT
: an RDF graph serialized, for example, in the RDF/XML syntax, or an equivalent RDF graph serialization.
The package, though it does not contain a full SPARQL parser, makes an attempt to determine the query type when the query is set. This should work in most of the cases (but there is a possibility to set this manually, in case something goes wrong).
Automatic conversion of the results¶
To make processing somewhat easier, the package can do some conversions automatically from the return result. These are:
- for XML, the xml.dom.minidom is used to convert the result stream into a
Python representation of a DOM tree
. - for JSON, the json package to generate a
Python dictionary
. Until version 1.3.1, the simplejson package was used. - for CSV or TSV, a simple
string
. - For RDF/XML and JSON-LD, the RDFLib package is used to convert the result into a
Graph
instance. - For RDF Turtle/N3, a simple
string
.
There are two ways to generate this conversion:
- use
ret.convert()
in the return result fromsparql.query()
in the code above - use
sparql.queryAndConvert()
to get the converted result right away if the intermediate stream is not used
For example, in the code below:
try :
sparql.setReturnFormat(SPARQLWrapper.JSON)
ret = sparql.query()
dict = ret.convert()
except:
deal_with_the_exception()
the value of dict
is a Python dictionary of the query result, based on the SPARQL Query Results JSON Format.
Partial interpretation of the results¶
A further help is to offer an extra, partial interpretation of the results, again to cover
most of the practical use cases.
Based on the SPARQL Query Results JSON Format, the SPARQLWrapper.SmartWrapper.Bindings
class
can perform some simple steps in decoding the JSON return results. If SPARQLWrapper.SmartWrapper.SPARQLWrapper2
is used instead of SPARQLWrapper.Wrapper.SPARQLWrapper
, this result format is generated. Note that this relies on a JSON format only,
ie, it has to be checked whether the SPARQL service can return JSON or not.
Here is a simple code that makes use of this feature:
from SPARQLWrapper import SPARQLWrapper2
queryString = "SELECT ?subj ?prop WHERE { ?subj ?prop ?o. }"
sparql = SPARQLWrapper2("http://example.org/sparql")
sparql.setQuery(queryString)
try :
ret = sparql.query()
print ret.variables # this is an array consisting of "subj" and "prop"
for binding in ret.bindings :
# each binding is a dictionary. Let us just print the results
print "%s: %s (of type %s)" % ("s",binding[u"subj"].value,binding[u"subj"].type)
print "%s: %s (of type %s)" % ("p",binding[u"prop"].value,binding[u"prop"].type)
except:
deal_with_the_exception()
To make this type of code even easier to realize, the []
and in
operators are also implemented
on the result of SPARQLWrapper.SmartWrapper.Bindings
. This can be used to check and find a particular binding (ie, particular row
in the return value). This features becomes particularly useful when the OPTIONAL
feature of SPARQL is used. For example:
from SPARQLWrapper import SPARQLWrapper2
queryString = "SELECT ?subj ?o ?opt WHERE { ?subj <http://a.b.c> ?o. OPTIONAL { ?subj <http://d.e.f> ?opt }}"
sparql = SPARQLWrapper2("http://example.org/sparql")
sparql.setQuery(queryString)
try :
ret = sparql.query()
print ret.variables # this is an array consisting of "subj", "o", "opt"
if (u"subj",u"prop",u"opt") in ret :
# there is at least one binding covering the optional "opt", too
bindings = ret[u"subj",u"o",u"opt"]
# bindings is an array of dictionaries with the full bindings
for b in bindings :
subj = b[u"subj"].value
o = b[u"o"].value
opt = b[u"opt"].value
# do something nice with subj, o, and opt
# another way of accessing to values for a single variable:
# take all the bindings of the "subj"
subjbind = ret.getValues(u"subj") # an array of Value instances
...
except:
deal_with_the_exception()
GET or POST¶
By default, all SPARQL services are invoked using HTTP GET verb. However, POST might be useful if the size of the query extends a reasonable size; this can be set in the query instance.
Note that some combination may not work yet with all SPARQL processors (e.g., there are implementations where POST + JSON return does not work). Hopefully, this problem will eventually disappear.
Development¶
Requirements¶
The RDFLib package is used for RDF parsing.
This package is imported in a lazy fashion, ie, only when needed. Ie, if the user never intends to use the RDF format, the RDFLib package is not imported and the user does not have to install it.
Source code¶
The source distribution contains:
SPARQLWrapper
: the Python package. You should copy the directory somewhere into your PYTHONPATH. Alternatively, you can also run the distutils scripts:python setup.py install
test
: some unit and integrations tests. In order to run the tests some packages have to be installed before. So please install the packages listed in requirements.development.txt:pip install -r requirements.development.txt
scripts
: some scripts to run the package against some SPARQL endpoints.docs
: the documentation.custom_fixers
: 2to3 custom_fixer in order to fix an issue with urllib2._opener.
Community¶
Community support is available through the developer’s discussion group rdflib-dev. The archives. from the old mailing list are still available.
Issues¶
Please, report any issue to github.
Documentation¶
The SPARQLWrapper documentation is available online.
Other interesting documents are the latest SPARQL 1.1 Specification (W3C Recommendation 21 March 2013) and the initial SPARQL Specification (W3C Recommendation 15 January 2008).
License¶
The SPARQLWrapper package is licensed under W3C license.
Acknowledgement¶
The package was greatly inspired by Lee Feigenbaum’s similar package for Javascript.
Developers involved:
- Ivan Herman <http://www.ivan-herman.net>
- Sergio Fernández <http://www.wikier.org>
- Carlos Tejo Alonso <http://www.dayures.net>
- Alexey Zakhlestin <https://indeyets.ru/>
Organizations involved: