def get_distdb_cog(model_id):
if not model_id in M2DDB:
from cog.torque import Graph
dbdir = os.path.join(DB_DIR, model_id, DB_NAMESPACE_DISTS)
dbfn = os.path.join(DB_DIR, model_id,
DB_NAMESPACE_DISTS + '.edgelist.txt')
if not os.path.exists(dbdir): os.makedirs(dbdir)
g = Graph(graph_name=DB_NAMESPACE_DISTS, cog_dir=dbdir)
if os.path.exists(dbfn):
return g.load_edgelist(dbfn, DB_NAMESPACE_DISTS)
M2DDB[model_id] = g
return M2DDB[model_id]
def test_torque_load_csv(self):
csv_file = "test/test-data/books.csv"
if os.path.exists("test-data/books.csv"):
csv_file = "test-data/books.csv"
g = Graph(graph_name="books5")
g.load_csv(csv_file, "isbn")
# print(g.scan())
actual = g.scan(20, 'e')
expected = {
'result': [{
'id': 'ratings_4'
}, {
'id': 'best_book_id'
}, {
'id': 'work_text_reviews_count'
}, {
'id': 'original_publication_year'
}, {
'id': 'average_rating'
}, {
'id': 'ratings_1'
}, {
'id': 'language_code'
}, {
'id': 'image_url'
}, {
'id': 'books_count'
}, {
'id': 'work_ratings_count'
}, {
'id': 'isbn13'
}, {
'id': 'title'
}, {
'id': 'ratings_5'
}, {
'id': 'ratings_3'
}, {
'id': 'small_image_url'
}, {
'id': 'ratings_count'
}, {
'id': 'isbn'
}, {
'id': 'book_id'
}, {
'id': 'authors'
}, {
'id': 'ratings_2'
}]
}
self.assertTrue(actual == expected)
self.assertTrue(
ordered(g.v('Kathryn Stockett').inc().out("title").all()) ==
ordered({'result': [{
'id': 'The Help'
}]}))
g.close()
def setUpClass(cls):
if not os.path.exists("/tmp/" + DIR_NAME):
os.mkdir("/tmp/" + DIR_NAME)
data_dir = "test/test-data/test_func.nq"
# choose appropriate path based on where the test is called from.
if os.path.exists("test-data/test_func.nq"):
data_dir = "test-data/test_func.nq"
TorqueTest.g = Graph(graph_name="people", cog_home=DIR_NAME)
TorqueTest.g.load_triples(data_dir, "people")
print(">>> test setup complete.\n")
def test_aaa_before_all_tests(self):
if not os.path.exists("/tmp/" + DIR_NAME):
os.mkdir("/tmp/" + DIR_NAME)
if os.path.exists("test-data/test.nq"):
loader = Loader("/tmp/" + DIR_NAME)
loader.load_triples("test-data/test.nq", "people")
else:
loader = Loader("/tmp/" + DIR_NAME)
loader.load_triples("test/test-data/test.nq", "people")
TorqueTest.cog = Cog("/tmp/" + DIR_NAME)
TorqueTest.g = Graph(graph_name="people", cog_dir="/tmp/" + DIR_NAME)
def test_torque_2(self):
TorqueTest2.g = Graph(graph_name="better_graph", cog_home=DIR_NAME)
TorqueTest2.g.put("A", "is better than", "B")\
.put("B", "is better than", "C")\
.put("A", "is better than", "D")\
.put("Z", "is better than", "D")\
.put("D", "is smaller than", "F")
expected = {'result': [{'id': 'B'}, {'id': 'D'}]}
actual = TorqueTest2.g.v("A").out(["is better than"]).all()
self.assertTrue(ordered(expected) == ordered(actual))
self.assertTrue(
TorqueTest2.g.v("A").out(["is better than"]).count() == 2)
self.assertTrue(TorqueTest2.g.v().count() == 6)
TorqueTest2.g.close()
def get_distdb_gt(model_id):
if not model_id in M2DDB:
dbdir = os.path.join(DB_DIR, model_id)
dbfn = os.path.join(DB_DIR, model_id, DB_NAMESPACE_DISTS + '.gt')
if not os.path.exists(dbdir): os.makedirs(dbdir)
if os.path.exists(dbfn):
g = load_graph(dbfn, fmt='gt')
else:
g = Graph()
M2DDB[model_id] = g
return M2DDB[model_id]
def test_torque_load_nq(self):
nq_file = "test/test-data/100lines.nq"
if os.path.exists("test-data/100lines.nq"):
nq_file = "test-data/100lines.nq"
g = Graph(graph_name="movies3", cog_path_prefix="/tmp/" + DIR_NAME)
g.load_triples(nq_file, 'movies3')
res = g.v("</en/joe_palma>").inc(["</film/performance/actor>"]).count()
g.close()
self.assertEqual(res, 7)
#reload test
g2 = Graph(graph_name="movies3", cog_path_prefix="/tmp/" + DIR_NAME)
res2 = g2.v("</en/joe_palma>").inc(["</film/performance/actor>"
]).count()
g2.close()
self.assertEqual(res2, 7, "reload test failed.")