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RDFLib/sparqlwrapper: A wrapper for a remote SPARQL endpoint

SPARQL Endpoint interface to Python

SPARQLWrapper is a simple Python wrapper around a SPARQL service to remotely execute your queries. It helps by creating the query invocation and, optionally, converting the result into more manageable formats.

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.

You can use SPARQLWrapper either as a Python command line script or as a Python package.

To use as a command line script, you will need to install SPARQLWrapper and then a command line script called rqw (spaRQl Wrapper) will be available within the Python environment into which it is installed. run $ rql -h to see all the script's options.

Here are a series of examples of different queries executed via SPARQLWrapper as a python package.

Simple use of this module is as follows where a live SPARQL endpoint is given and the JSON return format is used:

from SPARQLWrapper import SPARQLWrapper, JSON

sparql = SPARQLWrapper(
    "http://vocabs.ardc.edu.au/repository/api/sparql/"
    "csiro_international-chronostratigraphic-chart_geologic-time-scale-2020"
)
sparql.setReturnFormat(JSON)

# gets the first 3 geological ages
# from a Geological Timescale database,
# via a SPARQL endpoint
sparql.setQuery("""
    PREFIX gts: <http://resource.geosciml.org/ontology/timescale/gts#>

    SELECT *
    WHERE {
        ?a a gts:Age .
    }
    ORDER BY ?a
    LIMIT 3
    """
)

try:
    ret = sparql.queryAndConvert()

    for r in ret["results"]["bindings"]:
        print(r)
except Exception as e:
    print(e)

This should print out something like this:

{'a': {'type': 'uri', 'value': 'http://resource.geosciml.org/classifier/ics/ischart/Aalenian'}}
{'a': {'type': 'uri', 'value': 'http://resource.geosciml.org/classifier/ics/ischart/Aeronian'}}
{'a': {'type': 'uri', 'value': 'http://resource.geosciml.org/classifier/ics/ischart/Albian'}}

The above result is the response from the given endpoint, retrieved in JSON, and converted to a Python object, ret, which is then iterated over and printed.

This query gets a boolean response from DBPedia's SPARQL endpoint:

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())

You should see something like:

<?xml version="1.0" ?>
<sparql
    xmlns="http://www.w3.org/2005/sparql-results#"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://www.w3.org/2001/sw/DataAccess/rf1/result2.xsd">
<head/>
    <boolean>true</boolean>
</sparql>

CONSTRUCT queries return RDF, so queryAndConvert() here produces an RDFlib Graph object which is then serialized to the Turtle format for printing:

from SPARQLWrapper import SPARQLWrapper

sparql = SPARQLWrapper("http://dbpedia.org/sparql")

sparql.setQuery("""
    PREFIX dbo: <http://dbpedia.org/ontology/>
    PREFIX sdo: <https://schema.org/>

    CONSTRUCT {
      ?lang a sdo:Language ;
      sdo:alternateName ?iso6391Code .
    }
    WHERE {
      ?lang a dbo:Language ;
      dbo:iso6391Code ?iso6391Code .
      FILTER (STRLEN(?iso6391Code)=2) # to filter out non-valid values
    }
    LIMIT 3
""")

results = sparql.queryAndConvert()
print(results.serialize())

Results from this query should look something like this:

@prefix schema: <https://schema.org/> .

<http://dbpedia.org/resource/Arabic> a schema:Language ;
    schema:alternateName "ar" .

<http://dbpedia.org/resource/Aragonese_language> a schema:Language ;
    schema:alternateName "an" .

<http://dbpedia.org/resource/Uruguayan_Spanish> a schema:Language ;
    schema:alternateName "es" .

Like CONSTRUCT queries, DESCRIBE queries also produce RDF results, so this example produces an RDFlib Graph object which is then serialized into the JSON-LD format and printed:

from SPARQLWrapper import SPARQLWrapper

sparql = SPARQLWrapper("http://dbpedia.org/sparql")
sparql.setQuery("DESCRIBE <http://dbpedia.org/resource/Asturias>")

results = sparql.queryAndConvert()
print(results.serialize(format="json-ld"))

The result for this example is large but starts something like this:

[
    {
        "@id": "http://dbpedia.org/resource/Mazonovo",
        "http://dbpedia.org/ontology/subdivision": [
            {
                "@id": "http://dbpedia.org/resource/Asturias"
            }
    ],
...

UPDATE queries write changes to a SPARQL endpoint, so we can't easily show a working example here. However, if https://example.org/sparql really was a working SPARQL endpoint that allowed updates, the following code might work:

from SPARQLWrapper import SPARQLWrapper, POST, DIGEST

sparql = SPARQLWrapper("https://example.org/sparql")
sparql.setHTTPAuth(DIGEST)
sparql.setCredentials("some-login", "some-password")
sparql.setMethod(POST)

sparql.setQuery("""
    PREFIX dbp:  <http://dbpedia.org/resource/>
    PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

    WITH <http://example.graph>
    DELETE {
       dbo:Asturias rdfs:label "Asturies"@ast
    }
    """
)

results = sparql.query()
print results.response.read()

If the above code really worked, it would delete the triple dbo:Asturias rdfs:label "Asturies"@ast from the graph http://example.graph.

There is also a SPARQLWrapper2 class that works with JSON SELECT results only and wraps the results to make processing of average queries even simpler.

from SPARQLWrapper import SPARQLWrapper2

sparql = SPARQLWrapper2("http://dbpedia.org/sparql")
sparql.setQuery("""
    PREFIX dbp:  <http://dbpedia.org/resource/>
    PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

    SELECT ?label
    WHERE {
        dbp:Asturias rdfs:label ?label
    }
    LIMIT 3
    """
                )

for result in sparql.query().bindings:
    print(f"{result['label'].lang}, {result['label'].value}")

The above should print out something like:

en, Asturias
ar, أشتورية
ca, Astúries

The expected return formats differs per 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:

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:

There are two ways to generate this conversion:

For example, in the code below:

try :
    sparql.setReturnFormat(SPARQLWrapper.JSON)
    ret = sparql.query()
    d = ret.convert()
except Exception as e:
    print(e)

the value of d is a Python dictionary of the query result, based on the SPARQL Query Results JSON Format.

Partial interpretation of the results

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 :class:`SPARQLWrapper.SmartWrapper.Bindings` class can perform some simple steps in decoding the JSON return results. If :class:`SPARQLWrapper.SmartWrapper.SPARQLWrapper2` is used instead of :class:`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

sparql = SPARQLWrapper2("http://example.org/sparql")
sparql.setQuery("""
    SELECT ?subj ?prop
    WHERE {
        ?subj ?prop ?obj
    }
    """
)

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(f"{binding['subj'].value}, {binding['subj'].type}")
        print(f"{binding['prop'].value}, {binding['prop'].type}")
except Exception as e:
    print(e)

To make this type of code even easier to realize, the [] and in operators are also implemented on the result of :class:`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

sparql = SPARQLWrapper2("http://example.org/sparql")
sparql.setQuery("""
    SELECT ?subj ?obj ?opt
    WHERE {
        ?subj <http://a.b.c> ?obj .
        OPTIONAL {
            ?subj <http://d.e.f> ?opt
        }
    }
    """
)

try:
    ret = sparql.query()
    print(ret.variables)  # this is an array consisting of "subj", "obj", "opt"
    if ("subj", "prop", "opt") in ret:
        # there is at least one binding covering the optional "opt", too
        bindings = ret["subj", "obj", "opt"]
        # bindings is an array of dictionaries with the full bindings
        for b in bindings:
            subj = b["subj"].value
            o = b["obj"].value
            opt = b["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("subj")  # an array of Value instances
    ...
except Exception as e:
    print(e)

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 combinations 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.

SPARQL Endpoint Implementations

From SPARQL 1.1 Specification:

The response body of a successful query operation with a 2XX response is either:

The fact is that the parameter key for the choice of the output format is not defined. Virtuoso uses format, Fuseki uses output, rasqual seems to use results, etc... Also, in some cases HTTP Content Negotiation can/must be used.

Website: OpenLink Virtuoso Parameter key: format or output. JSON-LD (application/ld+json): supported (in CONSTRUCT and DESCRIBE). Website: Fuseki Uses: Parameters and Content Negotiation. Parameter key: format or output (Fuseki 1, Fuseki 2). JSON-LD (application/ld+json): supported (in CONSTRUCT and DESCRIBE).

Uses roqet as RDF query utility (see http://librdf.org/rasqal/roqet.html) For variable bindings, the values of FORMAT vary upon what Rasqal supports but include simple for a simple text format (default), xml for the SPARQL Query Results XML format, csv for SPARQL CSV, tsv for SPARQL TSV, rdfxml and turtle for RDF syntax formats, and json for a JSON version of the results.

For RDF graph results, the values of FORMAT are ntriples (N-Triples, default), rdfxml-abbrev (RDF/XML Abbreviated), rdfxml (RDF/XML), turtle (Turtle), json (RDF/JSON resource centric), json-triples (RDF/JSON triples) or rss-1.0 (RSS 1.0, also an RDF/XML syntax).

Website: Marklogic Uses: Only content negotiation (no URL parameters). JSON-LD (application/ld+json): NOT supported.

You can use following methods to query triples:

Formats are specified as part of the HTTP Accept headers of the REST request. When you query the SPARQL endpoint with REST Client APIs, you can specify the result output format (See https://docs.marklogic.com/guide/semantics/REST#id_54258. The response type format depends on the type of query and the MIME type in the HTTP Accept header.

This table describes the MIME types and Accept Header/Output formats (MIME type) for different types of SPARQL queries. (See https://docs.marklogic.com/guide/semantics/REST#id_54258 and https://docs.marklogic.com/guide/semantics/loading#id_70682)

Website: AllegroGraph Documentation: https://franz.com/agraph/support/documentation/current/http-protocol.html Uses: Only content negotiation (no URL parameters). Parameter: The server always looks at the Accept header of a request, and tries to generate a response in the format that the client asks for. If this fails, a 406 response is returned. When no Accept, or an Accept of / is specified, the server prefers text/plain, in order to make it easy to explore the interface from a web browser. JSON-LD (application/ld+json): NOT supported. Valid alias for SELECT and ASK: "json", "xml", csv", "tsv" (also "text" and "ascii") Valid alias for DESCRIBE and CONSTRUCT: "xml", "text" (for turtle) Valid alias for SELECT and ASK: "xml", "json" Valid alias for DESCRIBE and CONSTRUCT: "xml", "json" (but it returns unexpected "application/sparql-results+json") Website: Ontop VKG Documentation: <https://ontop-vkg.org/guide/> Uses: Only content negotiation (no URL parameters). Parameter key: If an unexpected parameter is used, the server ignores it.

The RDFLib package is used for RDF parsing.

This package is imported in a lazy fashion, i.e. only when needed. 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.

The source distribution contains:

Community support is available through the RDFlib developer's discussion group rdflib-dev. The archives. from the old mailing list are still available.

Please, report any issue to github.

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).

The SPARQLWrapper package is licensed under W3C license.

The package was greatly inspired by Lee Feigenbaum's similar package for Javascript.

Developers involved:

Organizations involved:

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