def test_side_effects(self):
statics.load_statics(globals())
connection = DriverRemoteConnection('ws://localhost:45940/gremlin',
'g')
#
g = Graph().traversal().withRemote(connection)
###
t = g.V().hasLabel("project").name.iterate()
assert 0 == len(t.side_effects.keys())
try:
m = t.side_effects["m"]
raise Exception(
"Accessing a non-existent key should throw an error")
except KeyError:
pass
###
t = g.V().out("created").groupCount("m").by("name")
results = t.toSet()
assert 2 == len(results)
assert Vertex(3) in results
assert Vertex(5) in results
assert 1 == len(t.side_effects.keys())
assert "m" in t.side_effects.keys()
m = t.side_effects["m"]
assert isinstance(m, dict)
assert 2 == len(m)
assert 3 == m["lop"]
assert 1 == m["ripple"]
assert isinstance(m["lop"], long)
assert isinstance(m["ripple"], long)
###
t = g.V().out("created").groupCount("m").by("name").name.aggregate("n")
results = t.toSet()
assert 2 == len(results)
assert "lop" in results
assert "ripple" in results
assert 2 == len(t.side_effects.keys())
assert "m" in t.side_effects.keys()
assert "n" in t.side_effects.keys()
n = t.side_effects.get("n")
assert isinstance(n, dict)
assert 2 == len(n)
assert "lop" in n.keys()
assert "ripple" in n.keys()
assert 3 == n["lop"]
assert 1 == n["ripple"]
t = g.withSideEffect('m', 32).V().map(lambda: "x: x.sideEffects('m')")
results = t.toSet()
assert 1 == len(results)
assert 32 == list(results)[0]
assert 32 == t.side_effects['m']
assert 1 == len(t.side_effects.keys())
try:
x = t.side_effects["x"]
raise Exception(
"Accessing a non-existent key should throw an error")
except KeyError:
pass
connection.close()
def test_traversals(self):
statics.load_statics(globals())
connection = DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')
assert "remoteconnection[ws://localhost:8182/gremlin,g]" == str(connection)
g = Graph().traversal().withRemote(connection)
assert long(6) == g.V().count().toList()[0]
#
assert Vertex(1) == g.V(1).next()
assert 1 == g.V(1).id().next()
assert Traverser(Vertex(1)) == g.V(1).nextTraverser()
assert 1 == len(g.V(1).toList())
assert isinstance(g.V(1).toList(), list)
results = g.V().repeat(out()).times(2).name
results = results.toList()
assert 2 == len(results)
assert "lop" in results
assert "ripple" in results
#
assert 10 == g.V().repeat(both()).times(5)[0:10].count().next()
assert 1 == g.V().repeat(both()).times(5)[0].count().next()
assert 0 == g.V().repeat(both()).times(5)[0:0].count().next()
assert 4 == g.V()[2:].count().next()
assert 2 == g.V()[:2].count().next()
# todo: need a traversal metrics deserializer
g.V().out().profile().next()
connection.close()
def test_side_effect_close(self):
connection = DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')
g = Graph().traversal().withRemote(connection)
t = g.V().aggregate('a').aggregate('b')
t.toList()
# The 'a' key should return some side effects
results = t.side_effects.get('a')
assert results
# Close result is None
results = t.side_effects.close()
assert not results
# Shouldn't get any new info from server
# 'b' isn't in local cache
results = t.side_effects.get('b')
assert not results
# But 'a' should still be cached locally
results = t.side_effects.get('a')
assert results
# 'a' should have been added to local keys cache, but not 'b'
results = t.side_effects.keys()
assert len(results) == 1
a, = results
assert a == 'a'
# Try to get 'b' directly from server, should throw error
with pytest.raises(Exception):
t.side_effects.value_lambda('b')
connection.close()
def test_traversals(self):
statics.load_statics(globals())
connection = DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')
assert "remoteconnection[ws://localhost:8182/gremlin,g]" == str(
connection)
#
g = Graph().traversal().withRemote(connection)
#
assert 6L == g.V().count().toList()[0]
#
assert Vertex(1) == g.V(1).next()
assert 1 == g.V(1).id().next()
assert Traverser(Vertex(1)) == g.V(1).nextTraverser()
assert 1 == len(g.V(1).toList())
assert isinstance(g.V(1).toList(), list)
#
results = g.V().repeat(out()).times(2).name.toList()
assert 2 == len(results)
assert "lop" in results
assert "ripple" in results
#
assert 10 == g.V().repeat(both()).times(5)[0:10].count().next()
assert 1 == g.V().repeat(both()).times(5)[0].count().next()
assert 0 == g.V().repeat(both()).times(5)[0:0].count().next()
assert 4 == g.V()[2:].count().next()
assert 2 == g.V()[:2].count().next()
# todo: need a traversal metrics deserializer
g.V().out().profile().next()
connection.close()
def test_strategies(self):
statics.load_statics(globals())
connection = DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')
#
g = Graph().traversal().withRemote(connection). \
withStrategies(TraversalStrategy("SubgraphStrategy",
{"vertices": __.hasLabel("person"),
"edges": __.hasLabel("created")}))
assert 4 == g.V().count().next()
assert 0 == g.E().count().next()
assert 1 == g.V().label().dedup().count().next()
assert "person" == g.V().label().dedup().next()
#
g = Graph().traversal().withRemote(connection). \
withStrategies(SubgraphStrategy(vertices=__.hasLabel("person"), edges=__.hasLabel("created")))
assert 4 == g.V().count().next()
assert 0 == g.E().count().next()
assert 1 == g.V().label().dedup().count().next()
assert "person" == g.V().label().dedup().next()
#
g = g.withoutStrategies(SubgraphStrategy). \
withComputer(workers=4, vertices=__.has("name", "marko"), edges=__.limit(0))
assert 1 == g.V().count().next()
assert 0 == g.E().count().next()
assert "person" == g.V().label().next()
assert "marko" == g.V().name.next()
#
g = Graph().traversal().withRemote(connection).withComputer()
assert 6 == g.V().count().next()
assert 6 == g.E().count().next()
connection.close()
def create_vertices(term: str, entities: list):
"""
Creates vertices to graph term to entities
"""
graph = Graph()
connection = DriverRemoteConnection(
f'wss://{os.environ["NEPTUNE_ENDPOINT"]}:8182/gremlin', 'g')
g = graph.traversal().withRemote(connection)
# Check if a vertex has been created for the term
term_vertex = g.V().has("term", "value", term)
term_vertex = term_vertex.next() if term_vertex.hasNext() else g.addV(
"term").property("value", term).next()
# Create an entity vertex for each and link to term
for e in entities:
entity_vertex = g.V().has("entity", "value", e)
entity_vertex = entity_vertex.next() if entity_vertex.hasNext() else \
g.addV("entity") \
.property("value", e["entity"]) \
.property("score", e["score"]) \
.property("type", e["type"]).next()
g.V(term_vertex).addE("has_entity").to(entity_vertex).iterate()
connection.close()
def go():
conn = DriverRemoteConnection(
'ws://localhost:45940/gremlin', 'gmodern', pool_size=4)
g = Graph().traversal().withRemote(conn)
yield gen.sleep(0)
assert len(g.V().toList()) == 6
conn.close()
def test_side_effect_close(self):
connection = DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')
g = Graph().traversal().withRemote(connection)
t = g.V().aggregate('a').aggregate('b')
t.toList()
# The 'a' key should return some side effects
results = t.side_effects.get('a')
assert results
# Close result is None
results = t.side_effects.close()
assert not results
# Shouldn't get any new info from server
# 'b' isn't in local cache
results = t.side_effects.get('b')
assert not results
# But 'a' should still be cached locally
results = t.side_effects.get('a')
assert results
# 'a' should have been added to local keys cache, but not 'b'
results = t.side_effects.keys()
assert len(results) == 1
a, = results
assert a == 'a'
# Try to get 'b' directly from server, should throw error
with pytest.raises(Exception):
t.side_effects.value_lambda('b')
connection.close()
def setup_graph(conn_string=DEFAULT_LOCAL_CONNECTION_STRING):
"""
Establish the connection to a property graph service using the connection string and return the gremlin graph.
:param conn_string: connection parameter
:return: gremlin graph
"""
try:
graph = Graph()
logging.debug('Trying To Connect')
# new style
connection = DriverRemoteConnection(conn_string, 'g')
connection.close()
connection = DriverRemoteConnection(conn_string, 'g')
logging.debug('Connected')
# The connection should be closed on shut down to close open connections with connection.close()
# g = graph.traversal().withRemote(connection) # Deprecated instantiation of traversal
g = traversal().withRemote(connection)
logging.info('Successfully connected to the graph server')
except Exception as e: # Shouldn't really be so broad
logging.error("Could not connect to the Gremlin server. Run for example:" \
"\n'docker run --rm --name janusgraph-default janusgraph/janusgraph:latest' OR" \
"\n'docker run --name gremlin-server -p 8182:8182 tinkerpop/gremlin-server'")
raise ConnectionError("Could not connect to the Gremlin server.")
return g
def go():
conn = DriverRemoteConnection(
'ws://localhost:45940/gremlin', 'gmodern', pool_size=4)
g = traversal().withRemote(conn)
yield gen.sleep(0)
assert len(g.V().toList()) == 6
conn.close()
def lambda_handler(event, context):
graph = Graph()
uid1 = event["userId1"]
uid2 = event["userId2"]
remoteConn = DriverRemoteConnection('ws://neptunedbinstance-3f8bwqre3vsy.cft44vxyghsh.us-east-1.neptune.amazonaws.com:8182/gremlin','g')
g = graph.traversal().withRemote(remoteConn)
friends= g.V().hasLabel('User').has('uid', uid1).\
both('FRIEND').aggregate('friends'). \
valueMap().toList()
list2 = []
for item in friends:
uid = item["uid"]
list2.append(uid[0])
if uid2 in list2:
return {
'statusCode': 400
}
a=g.V().hasLabel('User').has('uid', uid1).next()
b=g.V().hasLabel('User').has('uid', uid2).next()
g.V(a).addE('FRIEND').to(b).iterate()
remoteConn.close()
# TODO implement
return {
'statusCode': 200
}
def test_strategies(self):
statics.load_statics(globals())
connection = DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')
#
g = Graph().traversal().withRemote(connection). \
withStrategies(TraversalStrategy("SubgraphStrategy",
{"vertices": __.hasLabel("person"),
"edges": __.hasLabel("created")}))
assert 4 == g.V().count().next()
assert 0 == g.E().count().next()
assert 1 == g.V().label().dedup().count().next()
assert "person" == g.V().label().dedup().next()
#
g = Graph().traversal().withRemote(connection). \
withStrategies(SubgraphStrategy(vertices=__.hasLabel("person"), edges=__.hasLabel("created")))
assert 4 == g.V().count().next()
assert 0 == g.E().count().next()
assert 1 == g.V().label().dedup().count().next()
assert "person" == g.V().label().dedup().next()
#
g = g.withoutStrategies(SubgraphStrategy). \
withComputer(workers=4, vertices=__.has("name", "marko"), edges=__.limit(0))
assert 1 == g.V().count().next()
assert 0 == g.E().count().next()
assert "person" == g.V().label().next()
assert "marko" == g.V().name.next()
#
g = Graph().traversal().withRemote(connection).withComputer()
assert 6 == g.V().count().next()
assert 6 == g.E().count().next()
connection.close()
def main():
graph = Graph()
remote = DriverRemoteConnection('ws://' + os.environ['DB_ENDPOINT'] + ':8182/gremlin', 'g')
g = graph.traversal().withRemote(remote)
seed_users(g)
remote.close()
def handle_request():
try:
remote_connection = DriverRemoteConnection("ws://localhost:45940/gremlin", "g")
g = traversal().withRemote(remote_connection)
g.V().limit(1).toList()
remote_connection.close()
return True
except RuntimeError:
return False
def test_side_effects(self):
statics.load_statics(globals())
connection = DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')
#
g = Graph().traversal().withRemote(connection)
###
t = g.V().hasLabel("project").name.iterate()
assert 0 == len(t.side_effects.keys())
try:
m = t.side_effects["m"]
raise Exception("Accessing a non-existent key should throw an error")
except KeyError:
pass
###
t = g.V().out("created").groupCount("m").by("name")
results = t.toSet()
assert 2 == len(results)
assert Vertex(3) in results
assert Vertex(5) in results
assert 1 == len(t.side_effects.keys())
assert "m" in t.side_effects.keys()
m = t.side_effects["m"]
assert isinstance(m, dict)
assert 2 == len(m)
assert 3 == m["lop"]
assert 1 == m["ripple"]
assert isinstance(m["lop"], long)
assert isinstance(m["ripple"], long)
###
t = g.V().out("created").groupCount("m").by("name").name.aggregate("n")
results = t.toSet()
assert 2 == len(results)
assert "lop" in results
assert "ripple" in results
assert 2 == len(t.side_effects.keys())
assert "m" in t.side_effects.keys()
assert "n" in t.side_effects.keys()
n = t.side_effects.get("n")
assert isinstance(n, dict)
assert 2 == len(n)
assert "lop" in n.keys()
assert "ripple" in n.keys()
assert 3 == n["lop"]
assert 1 == n["ripple"]
t = g.withSideEffect('m', 32).V().map(lambda: "x: x.sideEffects('m')")
results = t.toSet()
assert 1 == len(results)
assert 32 == list(results)[0]
assert 32 == t.side_effects['m']
assert 1 == len(t.side_effects.keys())
try:
x = t.side_effects["x"]
raise Exception("Accessing a non-existent key should throw an error")
except KeyError:
pass
connection.close()
def actors(request):
graph = Graph()
remoteConn = DriverRemoteConnection('ws://<neptune endpoint>:8182/gremlin',
'g')
g = graph.traversal().withRemote(remoteConn)
myList = g.V().has(
'title', request.POST['movie_name']).in_().limit(40).values().toList()
remoteConn.close()
context = {'movie': request.POST['movie_name'], 'actors': myList}
return render(request, 'polls/movie-results.html', context)
def lambda_handler(event, context):
print(event)
graph = Graph()
table = dynamodb_client.Table('user')
tmp = table.scan()
dict1 = {}
for item in tmp['Items']:
dict1[item['UID']] = []
pair = (item['firstName'], item['lastName'], item['pic_url'])
dict1[item['UID']].append(pair)
print(dict1)
remoteConn = DriverRemoteConnection(
'ws://neptunedbinstance-3f8bwqre3vsy.cft44vxyghsh.us-east-1.neptune.amazonaws.com:8182/gremlin',
'g')
g = graph.traversal().withRemote(remoteConn)
# a=g.V().hasLabel('User').has('uid', '1834389').next()
# b=g.V().hasLabel('User').has('uid', '594112').next()
# g.V(a).addE('Friend').to(b).iterate()
key = event["userId"]
friends= g.V().hasLabel('User').has('uid', key).\
both('FRIEND').aggregate('friends'). \
valueMap().toList()
list2 = []
for item in friends:
tmplist = []
uid = item["uid"]
tmplist.append(uid[0])
for tmp in dict1[uid[0]][0]:
tmplist.append(tmp)
list2.append(tmplist)
return {'statusCode': 200, 'body': list2}
count = 0
recommend_list = {
k: v
for k, v in sorted(recommend.items(), key=lambda item: -item[1])
}
list1 = []
for item in recommend_list:
if item != key:
data = dynamodb.get_item(TableName='user',
Key={'UID': {
'S': str(item)
}})
pair = (str(item), data['Item']['firstName']['S'],
data['Item']['lastName']['S'],
data['Item']['pic_url']['S'])
list1.append(pair)
count += 1
if (count == 3):
break
print(list1)
remoteConn.close()
# TODO implement
return {'statusCode': 200, 'body': list1}
def movies(request):
graph = Graph()
remoteConn = DriverRemoteConnection('ws://<path to neptune>:8182/gremlin',
'g')
g = graph.traversal().withRemote(remoteConn)
#print(g.V().limit(2).toList())
myList = g.V().has(
'name', request.POST['actor_name']).out().limit(40).values().toList()
remoteConn.close()
context = {'actor': request.POST['actor_name'], 'movies': myList}
return render(request, 'polls/movie-results.html', context)
def main():
graph = Graph()
remote = DriverRemoteConnection(
'ws://' + os.environ['DB_ENDPOINT'] + ':8182/gremlin', 'g')
g = graph.traversal().withRemote(remote)
print('Flushing existing vertices in local db...')
flush(g)
print('Done.')
remote.close()
def _executor(self, q, loop):
try:
connection = DriverRemoteConnection('ws://localhost:45940/gremlin',
'g',
loop=loop)
g = Graph().traversal().withRemote(connection)
assert len(g.V().toList()) == 6
except:
q.put(sys.exc_info()[0])
else:
q.put('success!')
connection.close()
def separation(request):
statics.load_statics(globals())
inputs = [x.strip() for x in request.POST['actor_names'].split(',')]
graph = Graph()
remoteConn = DriverRemoteConnection(
'ws://<neptune endpoint>.com:8182/gremlin', 'g')
g = graph.traversal().withRemote(remoteConn)
myList = g.V().has(
'name', inputs[0]).repeat(out().in_().simplePath()).until(
has('name',
inputs[1])).path().by('name').by('title').limit(40).toList()
remoteConn.close()
context = {'actors': request.POST['actor_names'], 'separation': myList}
return render(request, 'polls/movie-results.html', context)
def kg_testing(inst=1, M=10, N=5, testing=False):
# number of data points and properties
m = M
p = N
if p > const.MAX_FEATURES:
p = const.MAX_FEATURES
# define the number of splits of each property
s = p if p <= const.MAX_SPLITS else const.MAX_SPLITS
# uniformly sample values between 0 and 1 as the data set
dat = np.random.sample(size=(m, p))
# create column names (normally obtained by var.dtype.names)
#
# use an explicit dict to make sure that the order is preserved
coln = [("col" + str(i), (i - 1)) for i in range(1, p + 1)]
# create the data for the sample knowledge graph (only one brain)
kgdat = create_kg(inst, dat, s, [[int(i) for i in np.asarray(coln)[:, 1]]])
# populate the knowledge graph into the remote DB
#
# instantiate a JanusGraph object
graph = Graph()
# connection to the remote server
conn = DriverRemoteConnection(url_kg(inst), 'g')
# get the remote graph traversal
g = graph.traversal().withRemote(conn)
# we only want to process the right brain
print(kg(const.V, inst, coln, kgdat, g, False, testing))
# after building the knowledge graph, use the output of ocr to test the GloVe write
#
# call cognitive to produce the ocr output
oret = ocr_testing()
# get the location of the glove file
src = cfg["instances"][inst]["src"]["index"]
typ = cfg["instances"][inst]["src"]["types"]["glove"]
gfl = cfg["instances"][inst]["sources"][src][typ]["connection"]["file"]
# call extendglove to produce the GloVe output and transform it to an array
# with the first term in each row being the key and all other terms are values
rdat = extendglove(oret[0][0], gfl[0])
rdat = [(k, v) for k, v in list(rdat.items())[0:M]]
# write the glove output to the knowledge graph
print(kg(const.ENTS, inst, coln, rdat, g, False, testing))
# get the ocr data ... using the real way to get the ocr data here
typ = cfg["instances"][inst]["src"]["types"]["ocrf"]
pdfs = cfg["instances"][inst]["sources"][src][typ]["connection"]["files"]
cdat = cognitive(const.OCR, pdfs, inst, False, testing)
# write the ocr data to the graph
print(kg(const.CONS, inst, coln, cdat[1:], g, True, testing))
# close the connection
conn.close()
# test the thought function with the default number of predictions 3
print(thought(inst, coln))
def main():
connection = DriverRemoteConnection('ws://localhost:8182/gremlin',
'{0}_traversal'.format('bandi'))
# g = traversal().withRemote(connection)
c = client.Client('ws://localhost:8182/gremlin',
'{0}_traversal'.format('bandi'))
results = c.submit(
'g.V().group().by(label).by(properties().group().by(key).by(value().map{it.get().getClass()}))'
).all().result()
nodes_info = NodeInfo.from_result(results[0])
encoded = yaml.safe_dump({'nodes': map(lambda e: e.to_dict(), nodes_info)})
print(encoded)
print(NodeInfo.from_dict(yaml.safe_load(encoded)))
connection.close()
def joint_movies(request):
statics.load_statics(globals())
inputs = [x.strip() for x in request.POST['actor_names'].split(',')]
graph = Graph()
remoteConn = DriverRemoteConnection('ws://<neptune endpoint>:8182/gremlin',
'g')
g = graph.traversal().withRemote(remoteConn)
if (len(inputs) == 2):
myList = g.V().has('name', inputs[0]).repeat(out().where(__.in_().has(
'name', inputs[1]))).emit().values().toList()
else:
myList = g.V().has('name', inputs[0]).repeat(out().where(__.in_().has(
'name', inputs[1])).where(__.in_().has(
'name', inputs[2]))).emit().values().toList()
remoteConn.close()
context = {'actor': request.POST['actor_names'], 'movies': myList}
return render(request, 'polls/movie-results.html', context)
def lambda_handler(event, context):
graph = Graph()
remoteConn = DriverRemoteConnection(
'ws://neptunedbinstance-3f8bwqre3vsy.cft44vxyghsh.us-east-1.neptune.amazonaws.com:8182/gremlin',
'g')
g = graph.traversal().withRemote(remoteConn)
# a=g.V().hasLabel('User').has('uid', '1834389').next()
# b=g.V().hasLabel('User').has('uid', '594112').next()
# g.V(a).addE('Friend').to(b).iterate()
key = event["userId"]
recommend = g.V().hasLabel('User').has('uid', key).\
both('FRIEND').aggregate('friends'). \
both('FRIEND'). \
where(P.without('friends')). \
groupCount().by('uid'). \
next()
friends= g.V().hasLabel('User').has('uid', key).\
both('FRIEND').aggregate('friends'). \
valueMap().toList()
print(friends)
count = 0
recommend_list = {
k: v
for k, v in sorted(recommend.items(), key=lambda item: -item[1])
}
list1 = []
for item in recommend_list:
if item != key:
data = dynamodb.get_item(TableName='user',
Key={'UID': {
'S': str(item)
}})
pair = (str(item), data['Item']['firstName']['S'],
data['Item']['lastName']['S'],
data['Item']['pic_url']['S'])
list1.append(pair)
count += 1
if (count == 10):
break
prediction(key)
print(list1)
remoteConn.close()
return {'statusCode': 200, 'body': list1}
def _executor(q, conn):
close = False
if not conn:
# This isn't a fixture so close manually
close = True
conn = DriverRemoteConnection(
'ws://localhost:45940/gremlin', 'gmodern', pool_size=4)
try:
g = traversal().withRemote(conn)
future = g.V().promise()
t = future.result()
assert len(t.toList()) == 6
except:
q.put(sys.exc_info()[0])
else:
q.put('success!')
# Close conn
if close:
conn.close()
def _executor(q, conn):
close = False
if not conn:
# This isn't a fixture so close manually
close = True
conn = DriverRemoteConnection(
'ws://localhost:45940/gremlin', 'gmodern', pool_size=4)
try:
g = Graph().traversal().withRemote(conn)
future = g.V().promise()
t = future.result()
assert len(t.toList()) == 6
except:
q.put(sys.exc_info()[0])
else:
q.put('success!')
# Close conn
if close:
conn.close()
def get_graph(term: str):
"""
Retrieves all the related entities a term has in Neptune
"""
graph = Graph()
connection = DriverRemoteConnection(
f'wss://{os.environ["NEPTUNE_ENDPOINT"]}:8182/gremlin', 'g')
g = graph.traversal().withRemote(connection)
entities = g.V().has(
"term", "value",
term.upper()).out("has_entity").valueMap(True).toList()
connection.close()
entity_names = set(
) # Use this to filter out repeating entity names, `dedup()` does not working 100% of the time
result = []
for e in entities:
data = {}
if e["value"][0] in entity_names:
continue
else:
entity_names.add(e["value"][0])
for k, v in e.items():
k_str = str(k)
if "T." in k_str:
name = k_str.split(".")[1]
data[name] = v
continue
data[k] = v[0]
result.append(data)
return result
def test_traversals(self):
statics.load_statics(globals())
connection = DriverRemoteConnection('ws://localhost:45940/gremlin',
'g')
assert "remoteconnection[ws://localhost:45940/gremlin,g]" == str(
connection)
g = Graph().traversal().withRemote(connection)
assert long(6) == g.V().count().toList()[0]
#
assert Vertex(1) == g.V(1).next()
assert 1 == g.V(1).id().next()
assert Traverser(Vertex(1)) == g.V(1).nextTraverser()
assert 1 == len(g.V(1).toList())
assert isinstance(g.V(1).toList(), list)
results = g.V().repeat(out()).times(2).name
results = results.toList()
assert 2 == len(results)
assert "lop" in results
assert "ripple" in results
#
assert 10 == g.V().repeat(both()).times(5)[0:10].count().next()
assert 1 == g.V().repeat(both()).times(5)[0:1].count().next()
assert 0 == g.V().repeat(both()).times(5)[0:0].count().next()
assert 4 == g.V()[2:].count().next()
assert 2 == g.V()[:2].count().next()
#
results = g.withSideEffect(
'a', ['josh', 'peter'
]).V(1).out('created').in_('created').values('name').where(
within('a')).toList()
assert 2 == len(results)
assert 'josh' in results
assert 'peter' in results
# todo: need a traversal metrics deserializer
g.V().out().profile().next()
connection.close()
def run_queries(cluster):
cluster_url = 'ws://localhost:%s/gremlin' % cluster['Port']
# test Client API
print('Connecting to Neptune Graph DB cluster URL: %s' % cluster_url)
graph_client = gremlin_client.Client(cluster_url, 'g')
values = '[1,2,3,4]'
print('Submitting values: %s' % values)
result_set = graph_client.submit(values)
future_results = result_set.all()
results = future_results.result()
print('Received values from cluster: %s' % results)
assert results == [1, 2, 3, 4]
future_result_set = graph_client.submitAsync('[1,2,3,4]')
result_set = future_result_set.result()
result = result_set.one()
assert result == [1, 2, 3, 4]
assert result_set.done.done()
graph_client.close()
# test DriverRemoteConnection API
graph = Graph()
conn = DriverRemoteConnection(cluster_url, 'g')
g = graph.traversal().withRemote(conn)
vertices_before = g.V().toList()
print('Existing vertices in the graph: %s' % vertices_before)
print('Adding new vertices "v1" and "v2" to the graph')
g.addV().property('id', 'v1').property('name', 'Vertex 1').next()
g.addV().property('id', 'v2').property('name', 'Vertex 2').next()
vertices_after = g.V().toList()
print('New list of vertices in the graph: %s' % vertices_after)
result = set(vertices_after) - set(vertices_before)
assert len(result) == 2
conn.close()
# col3, col2 is col1
id_0 = name_to_id.get(vals[0], None)
id_1 = name_to_id.get(vals[1], None)
id_2 = name_to_id.get(vals[2], None)
if id_0 is not None:
if id_1 is not None:
g.addE('is').from_(id_1).to(id_0).next()
if id_2 is not None:
g.addE('is').from_(id_2).to(id_0).next()
# col2 knows col3
if id_1 is not None and id_2 is not None:
g.addE('knows').from_(id_1).to(id_2).next()
return
if __name__ == "__main__":
# connect gremlin server
connection = DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')
g = traversal().withRemote(connection)
# remove all vertices and edges in the graph
g.V().drop().iterate()
# g.E().drop().iterate()
# populate data into graph database
alerts = pd.read_csv('../data/alerts.csv', header = None).values
load_data(g, alerts)
connection.close()
print("Data is loaded successfully.")
class JanusGraphClient(object):
""" JanusGraph Client Builder which adds the Serializers for JanusGraph specific objects, predicates etc. """
REMOTE_CONNECTION = None
def __init__(self, version=3.0):
""" Initializing with GraphSON version 3.0
Args:
version (int):
"""
self.graphsonVersion = version
def connect(self,
host="localhost",
port="8182",
traversal_source="g",
**kwargs):
""" Connect to JanusGraph's gremlin-server instance. Takes Host, Port and Graph
Args:
host (str): The HOST of JanusGraph gremlin-server instance. Defaults to localhost
port (str): The PORT of JanusGraph gremlin-server instance. Defaults to 8182.
graph (str): The GraphTraversalSource being exposed from gremlin-server instance. Defaults to g
Keyword Args:
graphson_reader (GraphSONReader): GraphSONReader object with required Deserializers registered
graphson_writer (GraphSONWriter): GraphSONWriter object with required Serializers registered
Raises:
AttributeError: When invalid Keyword arguments is provided. The expected key needs to be
`graphson_reader` and `graphson_writer`.
Returns:
JanusGraphClient
"""
URL = "ws://{}:{}/gremlin".format(host, port)
if not kwargs:
graphson_reader = JanusGraphSONReader().build()
graphson_writer = JanusGraphSONWriter().build()
else:
if "graphson_reader" in kwargs and "graphson_writer" in kwargs:
graphson_reader = kwargs["graphson_reader"]
graphson_writer = kwargs["graphson_writer"]
else:
raise AttributeError(
"Additional parameters if provided needs to be keywords arguments of "
"`graphson_reader` and `graphson_writer`")
self.REMOTE_CONNECTION = DriverRemoteConnection(
URL,
traversal_source,
graphson_reader=graphson_reader,
graphson_writer=graphson_writer)
return self
def get_connection(self):
""" Get the RemoteConnection object, so that same can be used to create GraphTraversalSource.
Returns:
DriverRemoteConnection
"""
return self.REMOTE_CONNECTION
def close(self):
try:
self.REMOTE_CONNECTION.close()
return True
except:
return False
edge = g.V().has('first_name', 'Shane').addE('son_of').to(g.V().has('first_name', 'Edith')).property('known_since','1964').next()
edge = g.V().has('first_name', 'Edith').addE('mother_of').to(g.V().has('first_name', 'Shane')).property('known_since','1964').next()
edge = g.V().has('first_name', 'Shane').addE('husband_of').to(g.V().has('first_name', 'Mary')).property('known_since','1989').next()
edge = g.V().has('first_name', 'Mary').addE('wife_of').to(g.V().has('first_name', 'Shane')).property('known_since','1989').next()
edge = g.V().has('first_name', 'Shane').addE('father_of').to(g.V().has('first_name', 'Betty')).property('known_since','1991').next()
edge = g.V().has('first_name', 'Betty').addE('daughter_of').to(g.V().has('first_name', 'Shane')).property('known_since','1991').next()
edge = g.V().has('first_name', 'Mary').addE('mother_of').to(g.V().has('first_name', 'Betty')).property('known_since','1991').next()
edge = g.V().has('first_name', 'Betty').addE('daughter_of').to(g.V().has('first_name', 'Mary')).property('known_since','1991').next()
#print out all the node's first names
print(g.V().first_name.toList())
#print out all the properties of person whose's first name is Shane
print(g.V().has('person','first_name','Shane').valueMap().next())
#traversing the graph starting with Betty to then Shane to then Edith
print(g.V().has('first_name', 'Betty').out('daughter_of').out('son_of').valueMap().toList())
print("\n\n\n")
#Print out all the nodes
people = g.V().valueMap().toList()
print(people)
#Print out all the connections (edges)
connections = g.E().valueMap().toList()
print(connections)
#Closing the connection
remoteConn.close()
class TrajectoryGraph:
# use for binding
LABEL = "label"
CAMID = "camId"
TIME = "time"
IMAGE = "image"
OUT_V = "outV"
IN_V = "inV"
LIMIT = "limit"
VID = "vid"
FEA = "feature"
CONFIDENCE = "confidence"
INDEX = "index"
def __init__( self ):
self.b = Bindings()
self.graph = Graph()
self.connection = DriverRemoteConnection('ws://130.207.122.57:8182/gremlin','g')
self.g = self.graph.traversal().withRemote(self.connection)
logging.info("Connected")
def addDetection(self, vehId, camId, timestamp, index):
v = self.g.addV(self.b.of(TrajectoryGraph.LABEL, vehId))\
.property(TrajectoryGraph.CAMID, self.b.of(TrajectoryGraph.CAMID, camId))\
.property(TrajectoryGraph.TIME, self.b.of(TrajectoryGraph.TIME, timestamp))\
.property(TrajectoryGraph.INDEX, self.b.of(TrajectoryGraph.INDEX, index))\
.id().next()
logging.info("Trajectory Vertex v[{}] ({}, {}, {}) created.".format(v, vehId, camId, timestamp))
return v
def linkDetection(self, src, dest, confidence):
logging.info("Link vertex v[{}] to v[{}]. Confidence {}".format(src, dest, confidence))
self.g.V(self.b.of(TrajectoryGraph.OUT_V, src))\
.as_("a")\
.V(self.b.of(TrajectoryGraph.IN_V, dest))\
.addE(self.b.of(TrajectoryGraph.LABEL, "next"))\
.from_("a")\
.property(TrajectoryGraph.CONFIDENCE, self.b.of(TrajectoryGraph.CONFIDENCE, confidence))\
.iterate()
def getValueMapById(self,id):
value = self.g.V(self.b.of(TrajectoryGraph.VID, id)).valueMap(True).next()
logging.info("Get detection valuemap {} for V[{}]".format(value.keys(), id))
return value
def getLatestDetectionsByCamId(self, camId,limit):
# timelimit support can be considered.
vehIds = self.g.V().has(TrajectoryGraph.CAMID, self.b.of(TrajectoryGraph.CAMID, camId)).order().by(TrajectoryGraph.TIME, Order.decr).limit(self.b.of(TrajectoryGraph.LIMIT, limit)).id().toList()
logging.info("LatestDetections by camera {}: {}".format(camId, vehIds))
return vehIds
def getNextDetectionsById(self, id, limit):
# This can be used to return self
vehIds = self.g.V(self.b.of(TrajectoryGraph.OUT_V, id)).emit().repeat(__.out()).times(self.b.of(TrajectoryGraph.LIMIT, limit)).id().toList()
logging.info("NextDetections from V[{}]: {}".format(id, vehIds))
return vehIds
def getPrevDetectionsById(self, id, limit):
vehIds = self.g.V(self.b.of(TrajectoryGraph.IN_V, id)).repeat(__.in_()).times(limit).emit().id().toList()
vehIds = vehIds[::-1]
logging.info("PrevDetections from V[{}]: {}".format(id, vehIds))
return vehIds
def clear(self):
logging.info("TrajectoryGraph dropped")
self.g.V().drop().iterate()
def shutdown(self):
logging.info("TrajectoryGraph closed")
self.connection.close()
self.g = None
self.graph = None
class GremlinStorageConnector(BaseStorageConnector):
"""Storage Connector for Gremlin databases."""
_g: Optional[Traversal] = None
connection: Optional[DriverRemoteConnection] = None
def __init__(self,
endpoint_url: str,
supports_multiple_labels=False,
test_prefix: str = "",
**kwargs) -> None:
"""Create a GremlinStorageConnector.
Arguments:
endpoint_url: The url of the gremlin endpoint to connect to (e.g. ``ws://localhost:8182``)
supports_multiple_labels: Some GraphDBs (Neptune/Neo4J) support multiple labels on a single vertex.
test_prefix: A prefix that will be prepended to edge and vertex ids to allow scenario separation.
**kwargs: Any unspecified args will be pased to the ``DriverRemoteConnection`` object.
"""
self.endpoint_url = endpoint_url
self.supports_multiple_labels = supports_multiple_labels
self.test_prefix = test_prefix
self.connection_args = kwargs
def init(self) -> None:
...
@property
def g(self) -> Traversal:
if not self.connection:
self.open()
if not self._g:
self._g = traversal().withRemote(self.connection)
return self._g
def open(self) -> DriverRemoteConnection:
if not self.connection:
logger.debug("Opening connection to %s", self.endpoint_url)
self.connection = DriverRemoteConnection(
f"{self.endpoint_url}/gremlin", "g", **self.connection_args)
def close(self) -> None:
logger.debug("Closing gremlin connection")
if self.connection:
self.connection.close()
self.connection = None
self._g = None
def write_resource(self, resource: CloudWandererResource) -> None:
"""Persist a single resource to storage.
Arguments:
resource (CloudWandererResource): The CloudWandererResource to write.
"""
self._write_resource(resource)
self._write_dependent_resource_edges(resource)
def _write_resource(self, resource: CloudWandererResource) -> None:
primary_label = generate_primary_label(resource.urn)
traversal = self._write_vertex(vertex_id=self.generate_vertex_id(
resource.urn),
vertex_labels=[primary_label])
traversal = (traversal.property(
Cardinality.single,
"_cloud_name", resource.urn.cloud_name).property(
Cardinality.single,
"_account_id", resource.urn.account_id).property(
Cardinality.single,
"_region", resource.urn.region).property(
Cardinality.single, "_service",
resource.urn.service).property(
Cardinality.single, "_resource_type",
resource.urn.resource_type).property(
Cardinality.single, "_discovery_time",
resource.discovery_time.isoformat()).property(
Cardinality.single, "_urn",
str(resource.urn)))
for id_part in resource.urn.resource_id_parts:
traversal.property(Cardinality.set_, "_resource_id_parts", id_part)
self._write_properties(
traversal=traversal,
properties=resource.cloudwanderer_metadata.resource_data)
self._write_relationships(resource)
self._clean_up_relationships(urn=resource.urn,
cutoff=resource.discovery_time)
if not resource.urn.is_partial:
self._repoint_vertex_edges(vertex_label=primary_label,
new_resource_urn=resource.urn)
def _write_dependent_resource_edges(
self, resource: CloudWandererResource) -> None:
for dependent_urn in resource.dependent_resource_urns:
logger.debug("Writing dependent resource edge from %s to %s",
resource.urn, dependent_urn)
self._write_edge(
edge_id=self.generate_edge_id(resource.urn, dependent_urn),
edge_label="has",
source_vertex_id=self.generate_vertex_id(resource.urn),
destination_vertex_id=self.generate_vertex_id(dependent_urn),
owner_id=self.generate_vertex_id(resource.urn),
discovery_time=resource.discovery_time,
)
def _clean_up_relationships(self, urn: PartialUrn,
cutoff: datetime) -> None:
logger.debug("Cleaning up edges owned by %s discovered before %s",
self.generate_vertex_id(urn), cutoff)
(self.g.V(self.generate_vertex_id(urn)).bothE().as_("edge").has(
"_edge_owner", self.generate_vertex_id(urn)).where(
__.values("_discovery_time").is_(P.lt(
cutoff.isoformat()))).select("edge").drop()).iterate()
def _write_relationships(self, resource: CloudWandererResource) -> None:
for relationship in resource.relationships:
inferred_partner_urn = relationship.partial_urn
try:
pre_existing_resource_urn = (self._lookup_resource(
relationship.partial_urn).propertyMap().toList()[0]["_urn"]
[0].value)
except IndexError:
pre_existing_resource_urn = None
if pre_existing_resource_urn:
logger.debug(
"Writing relationship with pre_existing_resource_urn %s",
pre_existing_resource_urn)
self._write_relationship_edge(
resource_urn=resource.urn,
relationship_resource_urn=pre_existing_resource_urn,
direction=relationship.direction,
discovery_time=resource.discovery_time,
)
if pre_existing_resource_urn != inferred_partner_urn:
self._delete_relationship_edge(
resource_urn=resource.urn,
relationship_resource_urn=inferred_partner_urn,
direction=relationship.direction,
)
continue
logger.debug("Writing inferred resource %s", inferred_partner_urn)
self._write_resource(
CloudWandererResource(urn=cast(URN, relationship.partial_urn),
resource_data={}))
self._write_relationship_edge(
resource_urn=resource.urn,
relationship_resource_urn=inferred_partner_urn,
direction=relationship.direction,
discovery_time=resource.discovery_time,
)
def _repoint_vertex_edges(
self, vertex_label: str,
new_resource_urn: Union[URN, PartialUrn]) -> None:
# https://tinkerpop.apache.org/docs/current/recipes/#edge-move
resources_of_the_same_type = self.g.V().as_("old_vertex").hasLabel(
vertex_label)
for id_part in new_resource_urn.resource_id_parts:
resources_of_the_same_type.has("_resource_id_parts", id_part)
resources_with_same_id_but_unknown = (resources_of_the_same_type.or_(
__.has("_account_id", "unknown"), __.has("_region",
"unknown"))).toList()
for old_vertex in resources_with_same_id_but_unknown:
# Outbound
old_vertices_outbound_edges = self.g.V(old_vertex).outE().as_("e1")
old_outbound_edges_partner_vertex = old_vertices_outbound_edges.inV(
).as_("b")
new_vertex = old_outbound_edges_partner_vertex.V(
self.generate_vertex_id(new_resource_urn)).as_("new_vertex")
add_old_outbound_edges_to_new_vertex = (
new_vertex.addE("has").to("b").as_("e2").sideEffect(
__.select("e1").properties().unfold().as_("p").select(
"e2").property(
__.select("p").key(),
__.select("p").value())))
add_old_outbound_edges_to_new_vertex.select("e1").drop().iterate()
# Inbound
old_vertices_inbound_edges = self.g.V(old_vertex).select(
"old_vertex").inE().as_("old_inbound_edge")
old_inbound_edges_partner_vertex = old_vertices_inbound_edges.inV(
).as_("c")
new_vertex = old_inbound_edges_partner_vertex.select("new_vertex")
add_old_inbound_edges_to_new_vertex = (new_vertex.addE(
"has").from_("c").as_("new_inbound_edge").sideEffect(
__.select("old_inbound_edge").properties().unfold().as_(
"p").select("new_inbound_edge").property(
__.select("p").key(),
__.select("p").value())))
add_old_inbound_edges_to_new_vertex.select(
"old_inbound_edge").drop().iterate()
# Delete old vertex
self.g.V(old_vertex).drop().iterate()
def _delete_relationship_edge(self, resource_urn: PartialUrn,
relationship_resource_urn: PartialUrn,
direction: RelationshipDirection) -> None:
if direction == RelationshipDirection.INBOUND:
self._delete_edge(
self.generate_edge_id(relationship_resource_urn, resource_urn))
else:
self._delete_edge(
self.generate_edge_id(resource_urn, relationship_resource_urn))
def _write_relationship_edge(
self,
resource_urn: PartialUrn,
relationship_resource_urn: PartialUrn,
direction: RelationshipDirection,
discovery_time: datetime,
) -> None:
logger.debug("Writing edge relationship between %s and %s",
resource_urn, relationship_resource_urn)
if direction == RelationshipDirection.INBOUND:
self._write_edge(
edge_id=self.generate_edge_id(relationship_resource_urn,
resource_urn),
edge_label="has",
source_vertex_id=self.generate_vertex_id(
relationship_resource_urn),
destination_vertex_id=self.generate_vertex_id(resource_urn),
owner_id=self.generate_vertex_id(resource_urn),
discovery_time=discovery_time,
)
else:
self._write_edge(
edge_id=self.generate_edge_id(resource_urn,
relationship_resource_urn),
edge_label="has",
source_vertex_id=self.generate_vertex_id(resource_urn),
destination_vertex_id=self.generate_vertex_id(
relationship_resource_urn),
owner_id=self.generate_vertex_id(resource_urn),
discovery_time=discovery_time,
)
def _lookup_resource(self, partial_urn: PartialUrn) -> Traversal:
vertex_label = generate_primary_label(partial_urn)
logger.debug("looking up resource with label %s", vertex_label)
traversal = (self.g.V().hasLabel(vertex_label).has(
"_cloud_name",
partial_urn.cloud_name).has("_service", partial_urn.service).has(
"_resource_type", partial_urn.resource_type))
for id_part in partial_urn.resource_id_parts:
traversal.has("_resource_id_parts", id_part)
if partial_urn.account_id != "unknown":
traversal.has("_account_id", partial_urn.account_id)
if partial_urn.region != "unknown":
traversal.has("_region", partial_urn.region)
return traversal
def _write_vertex(self, vertex_id: str,
vertex_labels: List[str]) -> Traversal:
logger.debug("Writing vertex %s", vertex_id)
if self.supports_multiple_labels:
vertex_label = "::".join(vertex_labels)
else:
vertex_label = vertex_labels[0]
return self.g.V(vertex_id).fold().coalesce(
__.unfold(),
__.addV(vertex_label).property(T.id, vertex_id))
def _write_properties(self, traversal: Traversal,
properties: Dict[str, Any]) -> Traversal:
logger.debug("Writing properties: %s", properties)
for property_name, property_value in properties.items():
traversal = traversal.property(Cardinality.single,
str(property_name),
str(property_value))
traversal_size = len(str(traversal).encode())
try:
traversal.next()
except RuntimeError as ex:
raise RuntimeError(
"GremlinStorageConnector got a runtime error while saving a property of "
f"{traversal_size} bytes, check your Gremlin server's maxContentLength is larger than this."
) from ex
def _write_edge(
self,
edge_id: str,
edge_label: str,
source_vertex_id: str,
destination_vertex_id: str,
owner_id: str,
discovery_time: datetime,
) -> Traversal:
logger.debug("Looking for edge %s", edge_id)
edge = self.g.E(edge_id).property("_discovery_time",
discovery_time.isoformat()).toList()
if not edge:
logger.debug("Writing edge between %s and %s", source_vertex_id,
destination_vertex_id)
(self.g.V(source_vertex_id).as_("source").V(destination_vertex_id).
addE(edge_label).from_("source").property(T.id, edge_id).property(
"_edge_owner",
owner_id).property("_discovery_time",
discovery_time.isoformat())).next()
def _delete_edge(self, edge_id: str) -> Traversal:
logger.debug("Deleting edge %s", edge_id)
self.g.E(edge_id).drop().iterate()
def read_all(self) -> Iterator[dict]:
"""Return all records from storage."""
for vertex in self.g.V().has("_urn").valueMap().toList():
yield vertex
def read_resource(self, urn: URN) -> Optional[CloudWandererResource]:
"""Return a resource matching the supplied urn from storage.
Arguments:
urn (URN): The AWS URN of the resource to return
"""
return next(self.read_resources(urn=urn))
def read_resources(
self,
cloud_name: str = None,
account_id: str = None,
region: str = None,
service: str = None,
resource_type: str = None,
urn: Union[URN, PartialUrn] = None,
) -> Iterator["CloudWandererResource"]:
"""Yield a resource matching the supplied urn from storage.
All arguments are optional.
Arguments:
cloud_name: The name of the cloud in question (e.g. ``aws``)
urn: The AWS URN of the resource to return
account_id: Cloud Account ID (e.g. ``111111111111``)
region: AWS region (e.g. ``'eu-west-2'``)
service: Service name (e.g. ``'ec2'``)
resource_type: Resource Type (e.g. ``'instance'``)
"""
if not urn:
urn = PartialUrn(
cloud_name=cloud_name or "unknown",
service=service or "unknown",
account_id=account_id or "unknown",
region=region or "unknown",
resource_type=resource_type or "unknown",
)
for vertex in self._lookup_resource(
partial_urn=urn).propertyMap().toList():
yield CloudWandererResource(
urn=URN.from_string(vertex["_urn"][0].value),
resource_data=_normalise_gremlin_attrs(vertex),
discovery_time=datetime.strptime(
vertex["_discovery_time"][0].value, ISO_DATE_FORMAT),
)
def delete_resource(self, urn: URN) -> None:
"""Delete this resource and all its resource attributes.
Arguments:
urn (URN): The URN of the resource to delete
"""
logger.debug("Deleting resource %s", urn)
self.g.V(self.generate_vertex_id(urn)).drop().iterate()
def delete_resource_of_type_in_account_region(
self,
cloud_name: str,
service: str,
resource_type: str,
account_id: str,
region: str,
cutoff: Optional[datetime],
) -> None:
"""Delete resources of type in account and region unless in list of URNs.
This is used primarily to clean up old resources.
Arguments:
cloud_name: The name of the cloud in question (e.g. ``aws``)
account_id: Cloud Account ID (e.g. ``111111111111``)
region: Cloud region (e.g. ``'eu-west-2'``)
service: Service name (e.g. ``'ec2'``)
resource_type: Resource Type (e.g. ``'instance'``)
cutoff: Delete any resource discovered before this time
"""
partial_urn = PartialUrn(
cloud_name=cloud_name,
service=service,
account_id=account_id,
region=region,
resource_type=resource_type,
)
logger.debug(
"Deleting resources that match %s that were discovered before %s",
partial_urn, cutoff)
traversal = self._lookup_resource(partial_urn=partial_urn)
if cutoff:
traversal.where(
__.values("_discovery_time").is_(P.lt(cutoff.isoformat())))
traversal.drop().iterate()
def generate_vertex_id(self, urn: PartialUrn) -> str:
"""Generate a vertex id.
Arguments:
urn: The URN of the vertex to create.
"""
return f"{self.test_prefix}{urn}"
def generate_edge_id(self, source_urn: PartialUrn,
destination_urn: PartialUrn) -> str:
"""Generate a primary edge id.
Arguments:
source_urn: The URN of the resource we're generating an edge from.
destination_urn: The URN of the resource we're generating an edge to.
"""
logger.debug("Generating edge id: %s", source_urn)
return f"{self.test_prefix}{source_urn}#{destination_urn}"
class GremlinWrapper(object):
def __init__(self, remote_gremlin_server):
self.remote_server = remote_gremlin_server
self.remote_connection = DriverRemoteConnection(
remote_gremlin_server, 'g')
self.g = traversal().withRemote(self.remote_connection)
statics.load_statics(globals())
def add_indigitous_user(self, login, email, name, uid):
# add a user to the gremlin graph
self.g.V() \
.has('indigitous_user', 'uid', uid) \
.fold() \
.coalesce(
unfold(),
addV('indigitous_user') \
.property('name', name) \
.property('uid', uid) \
.property('email', email) \
.property('login', login)) \
.toList()
def add_github_user(self, login, email, name, uid):
# add a user to the gremlin graph
return self.g.V().has('github_user', 'uid', uid) \
.fold() \
.coalesce(
unfold(),
addV('github_user')
.property('name', name) \
.property('uid', uid) \
.property('email', email) \
.property('login', login)) \
.toList()
def add_repository(self, name):
# add a user to the gremlin graph
return self.g.V() \
.has('repository', 'name', name) \
.fold() \
.coalesce(
unfold(),
addV('github_user') \
.property('name', name)) \
.iterate()
def get_list_of_indigitous_users(self):
#get a list of all people through name property.
return self.g.V() \
.hasLabel('indigitous_user') \
.group() \
.by(__.id()) \
.by('email') \
.toList()
def edge_vertices(self, label, from_v, to_v):
# Edge vertices
return self.g.E() \
.hasLabel(label) \
.where(outV().hasId(from_v)) \
.where(inV().hasId(to_v)) \
.fold() \
.coalesce( \
unfold(), \
addE(label) \
.from_(V(from_v)) \
.to(V(to_v))) \
.iterate()
def close(self):
self.remote_connection.close()
results = t.side_effects.get('b')
assert not results
# But 'a' should still be cached locally
results = t.side_effects.get('a')
assert results
# 'a' should have been added to local keys cache, but not 'b'
results = t.side_effects.keys()
assert len(results) == 1
a, = results
assert a == 'a'
# Try to get 'b' directly from server, should throw error
with pytest.raises(Exception):
t.side_effects.value_lambda('b')
connection.close()
if __name__ == '__main__':
test = False
try:
connection = DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')
test = True
connection.close()
except:
print("GremlinServer is not running and this test case will not execute: " + __file__)
if test:
unittest.main()
