Usage
Normally, you will only need to import the base sparrow module
>>> import sparrow
Most of the database backends will not work out of the box.
Since the RDFLib backend is written in python and packaged on pypi,
it is always available, and installed with Sparrow.
Let’s create an in memory rdflib database
>>> db = sparrow.database('rdflib', 'memory')
>>> db
Let’s add some triples to the database, we will use turtle syntax for this.
We’ll make some example statements where we will state that john is a person,
and that his firstname is “John”.
>>> data = """@prefix ex: .
... ex:john a ex:Person; ex:name "John" ."""
Now we can add this to the database. We will need to tell the database in
which context to store the data. The data itself can be either a file or http
based URI, a string of data, or a file-like object.
So, let’s add this to the persons context.
>>> db.add_turtle(StringIO(data), 'persons')
We can now ask the database, which contexts it has:
>>> db.contexts()
[u'persons']
You can store data in as many different contexts as you like, or put everything
in a single context.
Lets do a simple SPARQL query on the database
>>> result = db.select('SELECT ?x {?x "John".}')
We can get the results as a list of dictionaries. This follows the SPARQL
JSON result format.
>>> result
[{u'x': {'type': u'uri', 'value': u'http://example.org#john'}}]
Besides querying, we can also get the data back from the database in any
of the supported formats. We specify which format we want, and which context
to use.
>>> db.get_ntriples('persons').read()
' ...'
If the database backend supports it, you can ask how many triples are in a
context.
>>> db.count('persons')
2
If you want to remove triples, you will need to supply data describing which
triples to remove.
>>> data = ' a .'
>>> db.remove_turtle(data, 'persons')
>>> db.count('persons')
1
You can also remove all triples in a context
>>> db.clear('persons')
>>> db.count('persons')
0
Since the "persons’ context is now empty, it is also removed.
>>> db.contexts()
[]