def generate_classifier(self):
inner_classifier = self.policies[0].compile()
classifier = Classifier([])
for r in inner_classifier.rules:
action = r.actions[0]
if action == identity:
classifier.rules.append(Rule(r.match,[drop]))
elif action == drop:
classifier.rules.append(Rule(r.match,[identity]))
else:
raise TypeError # TODO MAKE A CompileError TYPE
return classifier
def json_to_classifier(fname, qdict, multistage):
from pyretic.core.classifier import Rule, Classifier
data = json.loads(fname)
rules = []
for sw_tbl in data:
switch_id = sw_tbl['switch_id']
for rule in sw_tbl['tbl']:
prio = rule['priority']
m = create_match(rule['pattern'], switch_id)
action = create_action(rule['action'], multistage)
queries = get_queries_from_names(rule['queries'], qdict)
if rule['queries']:
pyrule = Rule(m, action | queries, [None], "netkat_query")
else:
pyrule = Rule(m, action | queries, [None], "netkat")
rules.append((prio, pyrule))
#rules.sort()
rules = [v for (k,v) in rules]
return Classifier(rules)
def json_to_classifier(fname, qdict, multistage, vlan_offset_nbits):
from pyretic.core.classifier import Rule, Classifier
data = json.loads(fname)
rules = []
for sw_tbl in data:
switch_id = sw_tbl['switch_id']
for rule in sw_tbl['tbl']:
prio = rule['priority']
m = create_match(rule['pattern'], switch_id, vlan_offset_nbits)
(action, susp_vlan) = create_action(rule['action'], multistage,
vlan_offset_nbits)
if susp_vlan:
action = adjust_vlan_fields(m, action)
# This check allows classifier construction to proceed whether or
# not there's a "queries" field in the rule.
if 'queries' in rule and rule['queries']:
queries = get_queries_from_names(rule['queries'], qdict)
pyrule = Rule(m, queries | action, [None], "netkat_query")
else:
pyrule = Rule(m, action, [None], "netkat")
rules.append((prio, pyrule))
#rules.sort()
rules = [v for (k, v) in rules]
return Classifier(rules)
def generate_classifier(self):
return Classifier([Rule(identity,{self})])
def generate_classifier(self):
return Classifier([Rule(identity,{Controller})])
def generate_classifier(self):
if self.has_virtual_headers:
r = Rule(identity,{Controller})
else:
r = Rule(identity,{self})
return Classifier([r])
def generate_classifier(self):
r1 = Rule(self,{identity})
r2 = Rule(identity,set())
return Classifier([r1, r2])
def generate_classifier(self):
r1 = Rule(self,[identity])
r2 = Rule(identity,[drop])
return Classifier([r1, r2])
