1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
|
from rdflib import Graph
from test.data import BOB, CHEESE, HATES, LIKES, MICHEL, PIZZA, TAREK
class TestGraphSlice:
def test_slice(self):
"""
We pervert the slice object,
and use start, stop, step as subject, predicate, object
all operations return generators over full triples
"""
def sl(x, y):
return len(list(x)) == y
def soe(x, y):
return set([a[2] for a in x]) == set(y) # equals objects
g = Graph()
g.add((TAREK, LIKES, PIZZA))
g.add((TAREK, LIKES, CHEESE))
g.add((MICHEL, LIKES, PIZZA))
g.add((MICHEL, LIKES, CHEESE))
g.add((BOB, LIKES, CHEESE))
g.add((BOB, HATES, PIZZA))
g.add((BOB, HATES, MICHEL)) # gasp!
# Single terms are all trivial:
# single index slices by subject, i.e. return triples((x,None,None))
# tell me everything about "TAREK"
sl(g[TAREK], 2)
# single slice slices by s,p,o, with : used to split
# tell me everything about "TAREK" (same as above)
sl(g[TAREK::], 2)
# give me every "LIKES" relationship
sl(g[:LIKES:], 5)
# give me every relationship to PIZZA
sl(g[::PIZZA], 3)
# give me everyone who LIKES PIZZA
sl(g[:LIKES:PIZZA], 2)
# does TAREK like PIZZA?
assert g[TAREK:LIKES:PIZZA] is True
# More intesting is using paths
# everything hated or liked
sl(g[: HATES | LIKES], 7)
|
