def sched_timeout(self):
#start timer operations after the filter has started actual filtering
self.start_timer_event.wait()
while True:
#wait
time.sleep(self.config.timeout)
#wait for signal from main thread: the signal is send if the specified no. of packets is met
self.notif_timer_event.wait()
if self.config.rules_count < Rule.num_of_rules():
with self.lock:
self.config.incr_rules_count = \
self.config.incr_rules_count if((Rule.num_of_rules() - self.config.rules_count) > self.config.incr_rules_count) \
else (Rule.num_of_rules() - self.config.rules_count)
self.config.update()
#clear event
self.notif_timer_event.clear()
#reset pkt_count
self.pkt_count = 0
if self.config.rules_count == Rule.num_of_rules():
print(" # all rules defined have been added.")
#stop timer incase all rules have been added to self._rules
#resume capture
print(' # resuming capture.\n')
print(" ", end="")
print("src".ljust(20) + "dst".ljust(20) + "protocol".ljust(10) + "ttl".ljust(10) + "action".ljust(15) + \
"memory(MBs)".ljust(15) + "cummulative cpu time(secs)")
print(" ", end="")
print(('-' * 116))
else:
#stop timer, all defined rules have been added
break
def __init__(self, rules_db):
Rule.__init__(
self, [],
expression_from_list(
[rules_db.add_constant_by_name("atom"),
Variable("X")]), rules_db.add_constant_by_name("atom_rule"),
"(built-in)", rules_db)
def get_mode_one_config(parser, p_result):
issues = ''
if not p_result.rules_count:
issues += " - no. of rules not provided.\n"
if not p_result.rule_nums:
issues += " - rule numbers (comma-seperated) not provided.\n"
if issues:
print('[-] issues:\n' + issues)
parser.print_usage()
sys.exit(0)
if p_result.rules_count == 'all':
p_result.rules_count = Rule.num_of_rules()
p_result.rules = list(Rule.get_all_rules().keys())
else:
p_result.rule_nums = [
int(i) for i in p_result.rule_nums.split(',') if i
]
p_result.rules_count = len(p_result.rule_nums)
print(' # initializing rules', end='')
p_result.rules = Rule.get_rules_from_nums(p_result.rule_nums)
return ModeOneFilterConfig(p_result)
def update_rules(self):
"""
create a new list of random rules.
"""
self.rule_nums = Rule.get_rules_randomly(self.rules_count)
print(' # initializing rules.', end=' ')
self.rules = Rule.get_rules_from_nums(self.rule_nums)
def execute(self):
ListRules().execute()
operator = input(
"Choose operator to apply to rules(number).\n1. Any \n2. All\nChoose: "
)
try:
operator = int(operator)
except ValueError:
print("Choose numbers\n 1. Any \n2. All\n ")
rules_to_apply = []
while True:
ListRules().execute()
rule = input(
"Rule Name to apply or done in case you wish to execute now: ")
rule = rule.strip()
if rule == "done":
break
if self.fetch_rule(rule):
if rule not in rules_to_apply:
rules_to_apply.append(rule)
else:
print("Could not find rule")
ListAction().execute()
action_name = input("Action to apply. Choose by name: ")
action_types = [
action.action_name for action in ActionType.__subclasses__()
]
if action_name not in action_types:
print("Could not find the action")
if action_name == 'move':
move_folder = input("Where should I move the emails: ")
else:
move_folder = None
result_ids = set()
for rule in rules_to_apply:
rule = Rule(rule)
rule.from_json(rule.rule_file)
result = rule.fetch_for_rule()
new_result_ids = set([message.gmail_id for message in result])
if operator == 1:
result_ids.union(new_result_ids)
else:
if len(result_ids) == 0:
result_ids = new_result_ids
else:
result_ids.intersection(new_result_ids)
actions = [
action for action in ActionType.__subclasses__()
if action.action_name == action_name
]
action = actions[0]
action().apply(result_ids, move_folder=move_folder)
def backup(args):
with open(args.config) as config_file:
config = json.load(config_file)
rule = Rule(config)
if args.dryrun:
# dryrun does not work anymore ('it is dry-run now)
raise NotImplementedError('dryrun does not work anymore (it is dry-run now)')
rule.options.dryrun = args.dryrun
now = datetime.datetime.now()
rsync_command = ['rsync'] + rule.get_optional_args(now) + rule.get_positional_args(now)
# create dirs fro log files
success_filepath = rule.log.get_sucess_filepath(now)
if not args.debug and success_filepath:
make_dirpath(success_filepath)
progress_filepath = rule.log.get_progress_filepath(now)
if args.verbose or args.debug or not progress_filepath:
progress_file = sys.stdout
else:
make_dirpath(progress_filepath)
progress_file = open(progress_filepath, "w")
error_filepath = rule.log.get_error_filepath(now)
if args.verbose or args.debug or not error_filepath:
error_file = sys.stderr
else:
make_dirpath(error_filepath)
error_file = open(error_filepath, 'w') if error_filepath else PIPE
# process
if args.debug:
print(' '.join(rsync_command))
else:
rsync_process = Popen(rsync_command, stdout=progress_file, stderr=error_file)
rsync_process.wait()
# some cleaning
if progress_filepath and exists(progress_filepath):
remove(progress_filepath)
if error_filepath and exists(error_filepath):
is_errors = not stat(error_filepath).st_size == 0
if not is_errors:
remove(error_filepath)
user_message = 'sucessfull save of {}.'.format(rule.source.dirpath)
else:
with open(error_filepath, 'r') as error_file:
last_error = error_file.readlines()[-1].decode()
user_message = 'finished with errors on save of {}: {}'.format(rule.source.dirpath, last_error)
else:
user_message = 'done'
notify_command = ['synodsmnotify', '@administrators', 'Backup {}'.format(basename(realpath(rule.source.dirpath))), user_message]
call(notify_command)
logging.debug('done')
class Test(object):
# default
f1 = Rule("f1", to_field="__f1", required=False, allowed_none=True)
f2 = Rule("f2",
to_field="__f2",
required=False,
allowed_none=False)
f3 = Rule("f3", to_field="__f3", required=True, allowed_none=False)
f4 = Rule("f4", to_field="__f4", required=True, allowed_none=True)
def get_mode_four_config(parser, p_result):
issues = ''
if not p_result.rules_count_range:
issues += ' - rules count range not provided.\n'
else:
try:
nr = [int(i) for i in p_result.rules_count_range.split('-')]
if nr[0] < 1 or nr[1] > Rule.num_of_rules():
issues += ' - invalid rules count range.\n'
else:
# set ranges
p_result.rules_count_range = tuple(nr)
except ValueError:
issues += ' - invalid rules count range.\n'
if not p_result.timeout_range:
issues += ' - timeout range not provided.\n'
else:
try:
tr = [int(i) for i in p_result.timeout_range.split('-')]
if tr[0] < 1:
issues += ' - invalid timeout range.\n'
else:
# set ranges
p_result.timeout_range = tuple(tr)
except ValueError:
issues += ' - invalid timeout range.\n'
if issues:
print('[-] issues:\n' + issues)
parser.print_usage()
sys.exit(0)
# initial timeout
print(' # generating random timeout.')
p_result.timeout = random.randint(p_result.timeout_range[0],
p_result.timeout_range[1])
# initial rules count - random from range
print(' # generating random rules count (no. of rules).')
p_result.rules_count = random.randint(p_result.rules_count_range[0],
p_result.rules_count_range[1])
# initial rule numbers
print(' # generating rule numbers randomly.')
p_result.rule_nums = Rule.get_rules_randomly(p_result.rules_count)
# adds a new member variable
# initial list of rules
print(' # initializing rules.', end=' ')
p_result.rules = Rule.get_rules_from_nums(p_result.rule_nums)
return ModeFourFilterConfig(p_result)
def update_rules(self):
"""
Set rules count to a new random value and create a new list
of random rules.
"""
print(' # generating new rules count.')
self.rules_count = random.randint(self.rules_count_range[0],
self.rules_count_range[1])
#print(' # generating %d r')
self.rule_nums = Rule.get_rules_randomly(self.rules_count)
print(' # initializing rules.', end=' ')
self.rules = Rule.get_rules_from_nums(self.rule_nums)
def execute(self):
list_rule = ListRules()
print("The list of rules to choose from, Please choose the name:")
list_rule.execute()
rule = input("Describe the rule: ")
rule_file = rule + '.json'
if not os.path.isfile(rule_file):
print("Could not find the rule by the name {}".format(rule))
exit()
rule = Rule(rule).from_json(rule_file)
print(rule.render())
def update_rules(message):
global rules
rules = message
rules_given_id.clear()
print("update rules given id {}".format(rules_given_id))
for r in rules:
print(r)
rule = Rule(r, enabled=r['enabled'])
print(rule.root)
print(rule.evaluate())
rule.execute()
print('updating rules')
print(rules)
update_admin() # to send the new rules status
def __init__(self, list_of_players):
'''
@param: list_of_players: a list of players
@return: none
'''
self.lastgame_round_players = list_of_players
self.players = list_of_players
self.rule_checker = Rule()
self.board = Board([], [])
self.loser = []
self.log = []
if len(list_of_players) > 5 or len(list_of_players) < 3:
raise Exception("Incorrect number of players")
colors = ["white", "black", "red", "green", "blue"]
self.avatar_player = {}
for i in range(len(list_of_players)):
self.avatar_player[list_of_players[i]] = Avatar(colors[i], None)
def __init__(self, rules: list, implications: list, membership_function: dict, domain: tuple):
self.implication = implications
self.membership_function = membership_function
self.domain = domain
AggregationMethods.__init__(self, Mamdani.consequent_filter)
self.rules = [Rule(item.split(), max, min, lambda x: 1-x)
for item in rules]
def __init__(self, learning_rate, no_rules, max_iter):
self.learning_rate = learning_rate
self.max_iter = max_iter
self.rules = [Rule() for _ in range(no_rules)]
self.samples = [
SampleDataFunction(x, y) for x in range(-4, 4)
for y in range(-4, 4)
]
self.sum_w = self.sum_wz = 0
def generate_rules(self):
'''Generate rules from frequent itemsets'''
# start from 2-elements itemsets
for level in self.itemsets[1:]:
for itemset in level:
subsets = Rule.get_subsets(itemset)
for antecedent in subsets:
consequent = itemset.difference(antecedent)
if antecedent and consequent:
rule_support = self.support[itemset]
rule_confidence = rule_support / self.support[antecedent]
if rule_confidence > self.min_confidence:
self.rules.append(Rule(antecedent,
consequent,
rule_support,
rule_confidence))
self.rules.sort(key=lambda rule: rule.confidence)
def get_mode_three_config(parser, p_result):
issues = ''
if not p_result.timeout:
issues += ' - filter timeout not provided.\n'
if not p_result.rules_count:
issues += ' - initial no. of rules not provided.\n'
else:
p_result.rules_count = int(p_result.rules_count)
if not p_result.proto:
issues += ' - protocol not provided.\n'
elif not p_result.proto in PROTOCOLS.keys():
issues += ' - invalid protocol.\n'
else:
pass
if not p_result.max_pkts_count:
issues += ' - max. packet count before incrementing rules not provided.\n'
if not p_result.incr_rules_count:
issues += ' - no. of rules to be incremented after timeout not provided.\n'
elif p_result.rules_count:
if p_result.incr_rules_count > (Rule.num_of_rules() -
p_result.rules_count):
issues += ' - no. of increment rules too high.\n'
else:
pass
if issues:
print('[-] issues:\n' + issues)
parser.print_usage()
sys.exit(0)
print(' # generating random rule numbers.')
p_result.rule_nums = Rule.get_rules_randomly(p_result.rules_count)
# adds a new member variable
print(' # initializing rules', end=' ')
p_result.rules = Rule.get_rules_from_nums(p_result.rule_nums)
p_result.proto = PROTOCOLS[p_result.proto]
return ModeThreeFilterConfig(p_result)
def test_metaclass(self):
rule = Rule("Field")
class Test(object):
__metaclass__ = MetaRules
field = rule
self.assertTrue(hasattr(Test, "_fields"))
self.assertEqual(Test._fields, {'field': rule})
self.assertEqual(Test()._fields, {'field': rule})
def get_rules(self):
'''Generate association rules from frequent itemsets'''
rules = []
for itemset in self.itemsets:
# if itemset is one-element, then antecedent or consequent
# will be empty, so skip
if len(itemset) > 1:
subsets = Rule.get_subsets(itemset)
for antecedent in subsets:
consequent = itemset.difference(antecedent)
if antecedent and consequent:
rule_support = self.get_support(itemset)
rule_confidence = rule_support / self.get_support(
antecedent)
if rule_confidence > self.min_confidence:
rules.append(
Rule(antecedent, consequent, rule_support,
rule_confidence))
rules.sort(key=lambda rule: rule.confidence)
return rules
def _load_rules(self, path):
rules = []
with open(path, encoding="utf-8") as f:
for line in f:
if line.isspace():
continue
rule = Rule.from_string(line)
rules.append(rule)
return RuleSet(rules)
def __initialize_rules(self):
self.rules = []
rules = []
try:
with open("rules.json") as rules_file:
rules = json.loads(rules_file.read())
except:
pass
for rule in rules:
self.rules.append(Rule(rule))
def get_mode_five_config(parser, p_result):
issues = ''
if not p_result.t_win_trig:
issues += " - THRESHOLD_WIN_TRIG not specified.\n"
if not p_result.win_size:
issues += " - WINDOW_SIZE not specified.\n"
if not p_result.inactive_cp:
issues += " - INACTIVE_CHECKED% not specified.\n"
if issues:
print('[-] issues:\n' + issues)
parser.print_usage()
sys.exit(0)
p_result.active_p = random.randint(1, (100 - p_result.inactive_cp))
p_result.active_set = Rule.get_rules_randomly(
round(float(Rule.num_of_rules()) * p_result.active_p / 100.0))
print(' # initializing ACTIVE rules.', end=' ')
rtmp = Rule.get_rules_from_nums(p_result.active_set)
p_result.active_rules = {}
for num, rule in zip(p_result.active_set, rtmp):
p_result.active_rules[num] = rule
p_result.inactive_set = Rule.get_new_rules_randomly(\
round(float(Rule.num_of_rules()) * p_result.inactive_cp/100.0), p_result.active_set)
print(' # initializing INACTIVE_CHECKED rules.', end=' ')
rtmp = Rule.get_rules_from_nums(p_result.inactive_set)
p_result.inactive_rules = {}
for num, rule in zip(p_result.inactive_set, rtmp):
p_result.inactive_rules[num] = rule
return ModeFiveFilterConfig(p_result)
def get_mode_two_config(parser, p_result):
issues = ''
if not p_result.timeout:
issues += ' - filter timeout not provided.\n'
if not p_result.rules_count:
issues += ' - no. of rules not provided.\n'
if issues:
print('[-] issues:\n' + issues)
parser.print_usage()
sys.exit(0)
p_result.rules_count = int(p_result.rules_count)
p_result.rule_nums = Rule.get_rules_randomly(p_result.rules_count)
# adds a new member variable
print(' # initializing rules', end=' ')
p_result.rules = Rule.get_rules_from_nums(p_result.rule_nums)
return ModeTwoFilterConfig(p_result)
def add_builtins(rules_db):
rules_db.add_rule(
Rule([],
expression_from_list([
Variable("X"),
rules_db.add_constant_by_name("is"),
Variable("X")
]), rules_db.add_constant_by_name("is_rule"), "(built-in)",
rules_db))
rules_db.add_rule(RuleIsNot(rules_db))
rules_db.add_rule(RuleAtom(rules_db))
rules_db.add_rule(RuleNewAtom(rules_db))
def test(definitions):
from rules import Rule
definitions.set_attribute('Plus', 'Flat')
definitions.set_attribute('Plus', 'Orderless')
definitions.set_attribute('g', 'Orderless')
eval = Evaluation(Symbol('unused'), definitions)
#expr = 'Plus[a,b,c,d,e,f,g,h,i,1,2,3]'
#expr = 'a+b+a+e+a+b+a+e+a+b+a+e+a+b+a+e+f'
#expr = 'a+b+c+d+e+f+g+h+i+j+k+l+a+b'
#pattern = 'x_+x_+b+c+d+e+f+g+h+i+j+k+l'
#expr = 'a+b+c+d+e+f+g+h+i+j+k+l+a+b+b+1+2+3'
#pattern = 'x_+x_+c+d+e+f+g+h+i+j+k+l'
#pattern = 'Plus[x_]'
#expr = 'g[a+b+c+d+e,b,e,d,c,a]'
#pattern = 'g[x__+y_,y_,x__]'
#expr = 'g[a+b+c+d+e,b]'
#pattern = 'g[x__+y_,y_]'
#expr = 'a+a+b'
#pattern = 'x__+x__'
#expr = 'a+b+c'
#pattern = 'x_+y_'
expr = 'Format[a+b]'
pattern = 'Format[Plus[items__]]'
#expr = 'a*b+c*d+e*f+g*h+i*j+k*l+m*n'
#pattern = 'a_*x_+b_*x_+a_*x_+b_*x_'
expr = parse(expr).evaluate(eval)
pattern = parse(pattern).evaluate(eval)
print expr
print pattern
rule = Rule(pattern, parse('3'))
#evaluation = Evaluation(Expression)
print '%s' % rule.apply(expr, eval)
def test(definitions):
from rules import Rule
definitions.set_attribute('Plus', 'Flat')
definitions.set_attribute('Plus', 'Orderless')
definitions.set_attribute('g', 'Orderless')
eval = Evaluation(Symbol('unused'), definitions)
#expr = 'Plus[a,b,c,d,e,f,g,h,i,1,2,3]'
#expr = 'a+b+a+e+a+b+a+e+a+b+a+e+a+b+a+e+f'
#expr = 'a+b+c+d+e+f+g+h+i+j+k+l+a+b'
#pattern = 'x_+x_+b+c+d+e+f+g+h+i+j+k+l'
#expr = 'a+b+c+d+e+f+g+h+i+j+k+l+a+b+b+1+2+3'
#pattern = 'x_+x_+c+d+e+f+g+h+i+j+k+l'
#pattern = 'Plus[x_]'
#expr = 'g[a+b+c+d+e,b,e,d,c,a]'
#pattern = 'g[x__+y_,y_,x__]'
#expr = 'g[a+b+c+d+e,b]'
#pattern = 'g[x__+y_,y_]'
#expr = 'a+a+b'
#pattern = 'x__+x__'
#expr = 'a+b+c'
#pattern = 'x_+y_'
expr = 'Format[a+b]'
pattern = 'Format[Plus[items__]]'
#expr = 'a*b+c*d+e*f+g*h+i*j+k*l+m*n'
#pattern = 'a_*x_+b_*x_+a_*x_+b_*x_'
expr = parse(expr).evaluate(eval)
pattern = parse(pattern).evaluate(eval)
print expr
print pattern
rule = Rule(pattern, parse('3'))
#evaluation = Evaluation(Expression)
print '%s' % rule.apply(expr, eval)
def update_rules(self):
print('\n ' + '#' * 90)
new_rule_nums = Rule.get_new_rules_randomly(\
self.incr_rules_count, self.rule_nums)
#new_rule_nums.sort()
#add new rule numbers to self._rule_nums
print(" # adding", self.incr_rules_count, " more rule(s)")
#instantiate new rules, add them to self._rules
[self.rule_nums.append(rn) for rn in new_rule_nums]
print(' # initializing rules.', end=' ')
[self.rules.append(r) for r in Rule.get_rules_from_nums(new_rule_nums)]
self.rule_nums.sort()
self.rules_count = len(self.rule_nums)
#self._rule_nums.sort()
print(" # rules added ==> ", ' '.join(map(str, new_rule_nums)))
print(" # new rules list ==> %s" %
' '.join(map(str, self.rule_nums)))
print(" # new rules count ==> %d" % self.rules_count)
def update_admin():
devices = [{'id': x,
'state': device.get_state(),
'state_label': device.get_state_label(),
'is_actuator': isinstance(device, Actuator),
'type': device.type
} for x, device in device_ids.items()]
builder_rules = []
for device in device_ids.values():
builder_rules.append(device.build_rule())
from state import device_names
for r in rules:
r['status'] = Rule(r, enabled=r['enabled']).evaluate()
for admin_id in app.admin_id:
emit('update',
{'devices': devices, 'builder_rules': builder_rules, 'rules': rules, 'device_names': device_names},
room=admin_id)
def result():
delete_target_dir('./static')
os.mkdir('./static')
# 清洗数据
if not os.path.exists('./datas/1.xlsx'):
data = {'code': 0, 'info': '未上传excel'}
return jsonify(data)
from clean_data import Duty
duty = Duty()
datas = duty.get_duty_datas()
# pprint(datas)
with open('./datas/results.json', 'w', encoding='utf-8') as f:
f.write(json.dumps(datas, ensure_ascii=False))
# 执行规则
from rules import Rule
Rule()
# 返回api结果
data = {'code': 1, 'info': 'http://192.168.10.129:5000/static/考勤结果.xlsx'}
print('执行完毕')
return jsonify(data)
def __init__(self, response):
self._response = self.convert_proxy_response(response)
if not self._rule:
self._rule = Rule.get_url_match(Url({'_id': self._response.url}))
params['moves_amount'] = len(solution)
end_time = time.time()
delta = end_time - start_time
print(str(solution))
print('time complexity=', _open.time_complexity)
print('size complexity=', params.get('size_complexity'))
print(f'Moves: {params.get("moves_amount")}')
print('seconds: ', delta)
try:
solution.to_file('res.json')
except:
pass
exit()
_close.append(min_state)
neighbours = Rule.neighbours(min_state)
for neighbour in neighbours:
if neighbour in _close:
continue
g = min_state.g + Rule.distance(args.greedy)
if neighbour not in _open:
neighbour.parent = min_state
neighbour.set_metrics(g=g, heuristic=heuristics.get_total_h)
_open.put_nowait(neighbour)
elif g <= neighbour.g:
i = _open.queue.index(neighbour)
neighbour = _open.queue[i]
neighbour.parent = min_state
class TestRules(Rules):
id_field = Rule("Id", required=True)
def set_ownvalue(self, name, value):
from expression import Symbol
from rules import Rule
self.add_rule(name, Rule(Symbol(name), value))
def learn_one_rule(records, attributes, clss): """ Determine a rule that best covers the input. Returns the rule. Input: records - set of records that the rule should try to cover best; attributes - set of records' attributes; clss - the class the rule should precdict. """ def aux_nominal(name, value): """ Creates the condition for a nominal attribute. Returns a function from record to boolean representing the condition. Input: name - name of the attribute; value - value for the attribute. """ return lambda r: r[name] == value # name's value is equal to value def aux_continuous(name, value): """ Creates the condition for a continuous attribute. Returns a function from record to boolean representing the condition. Input: name - name of the attribute; value - value for the attribute. """ return lambda r: r[name] < value # name's value is less than value k = len( attribute_ocurrences(records, CLASS)[0] ) # number of classes rule = Rule(clss) # the generated rule conditions = [] # all desired attribute value relations strings = [] # the textual representation each element in conditions for name, cont, values in attributes: # each attribute if cont: # continuous attribute values = attribute_ocurrences(records, name)[0] # the different values assumed by this attribute in records values.sort() # sort the values in ascending order values = [ (values[i - 1] + values[i]) / 2 for i in range(1, len(values)) ] # replace values with the average of each consecutive pair of elements for value in values: # each average strings.append(name + ' < ' + str(value)) # add the text of this name to strings conditions.append( aux_continuous(name, value) ) # add a continuous condition else: for value in values: # each value value = value[:] # value is a copy of an attribute value strings.append(name + ' = ' + str(value)) # add the text of this name to strings conditions.append( aux_nominal(name, value) ) # add a nominal condition better = True # adding the best condition improved rule covered = records # the records covered by the current rule current = 0 # the laplace of rule's current form while better: best = None # index of the best condition laplace = 0 # laplace if the best condition were to be added for i, condition in enumerate(conditions): # each conjunct and its index matches = filter(condition, covered) # the covered records matched by this condition if matches != []: # some records in covered matches condition correct = len( filter(lambda r: r[CLASS] == clss, matches) ) # number of covered records correctly classified total = len(matches) # number of covered records l = float(correct + 1) / (total + k) # laplace with this condition if l >= laplace: best = i # update best laplace = l # update laplace better = laplace > current # update better if better: # a best condition was found and improves laplace rule.add_conjunct(conditions[best], strings[best]) # add the best condition to rule c = conditions.pop(best) # remove the best condition strings.pop(best) # remove the best condition's string covered = filter(c, covered) # covered keeps records that match c current = laplace # update current return rule
