def main():
args = parser.parse_args()
print('Launching Graveyard...')
runCheck(ip=args.ip, s=args.s, h=args.h)
if args.verify:
verification.verify(args.tocheck, args.mymail)
if not None in result:
print('Found results: \n{0}'.format(result))
def run(self):
print('www_kuaidaili_com')
if not self.check_alive():
return
for url in self.base_url:
if not self.check_alive():
break
time.sleep(2)
response = requests.get(url.format(1), headers=self.headers)
response.raise_for_status()
response.encoding = 'utf-8'
match_obj = re.search(r'>(\d+)</a></li><li>页</li>', response.text)
if match_obj:
tot_page = int(match_obj.group(1))
for i in range(1, tot_page + 1):
if not self.check_alive():
break
time.sleep(1)
text = self.download(url, i)
objs = self.parse(text)
if len(objs) <= 0:
break
for obj in objs:
if not self.check_alive():
break
obj_ = verify(obj)
if obj_:
self.save(obj_)
def run(self):
print('ip3366_net')
if not self.check_alive():
return
for url in self.base_url:
if not self.check_alive():
break
response = requests.get(url.format(1), headers=self.headers)
response.raise_for_status()
response.encoding = 'gb2312'
match_obj = re.search(r'page=(\d+)">尾页</a>', response.text)
if match_obj:
tot_page = int(match_obj.group(1))
for i in range(1, tot_page + 1):
if not self.check_alive():
break
text = self.download(url, i)
objs = self.parse(text)
if len(objs) <= 0:
break
for obj in objs:
if not self.check_alive():
break
obj_ = verify(obj)
if obj_:
self.save(obj_)
def run(self):
print('proxy_coderbusy_com')
if not self.check_alive():
return
text = self.download()
objs = self.parse(text)
for obj in objs:
if not self.check_alive():
break
obj_ = verify(obj)
if obj_:
self.save(obj_)
def run(self):
print('clarketm_proxy_list')
if not self.check_alive():
return
text = self.download()
objs = self.parse(text)
for obj in objs:
if not self.check_alive():
break
obj_ = verify(obj)
if obj_:
self.save(obj_)
def run(self):
print('TheSpeedX_SOCKS_List')
if not self.check_alive():
return
texts = self.download()
objs = self.parse(texts)
for obj in objs:
if not self.check_alive():
break
obj_ = verify(obj)
if obj_:
self.save(obj_)
def run(self):
print('hookzof_socks5_list')
if not self.check_alive():
return
texts = self.download()
objs = self.parse(texts)
for obj in objs:
if not self.check_alive():
break
obj_ = verify(obj)
if obj_:
self.save(obj_)
def run(self):
print('ip_jiangxianli_com')
if not self.check_alive():
return
for i in range(10):
text = self.download(i)
objs = self.parse(text)
if len(objs) <= 0:
break
for obj in objs:
if not self.check_alive():
break
obj_ = verify(obj)
if obj_:
self.save(obj_)
def run(self):
print('www_66ip_cn')
if not self.check_alive():
return
for num in range(1, 35):
if not self.check_alive():
break
text = self.download(num)
objs = self.parse(text)
for obj in objs:
if not self.check_alive():
break
obj_ = verify(obj)
if obj_:
self.save(obj_)
def validate(val_loaders, model, criterion, args, log):
model.eval()
results = {}
name, val_loader, issame = val_loaders[args.gpu % len(val_loaders)]
with torch.no_grad():
with model.no_sync():
embeddings = []
for i, input in enumerate(val_loader):
input = input.cuda(args.gpu, non_blocking=True)
output = model(input, True)
norm = torch.norm(output, 2, 1, True)
embedding = torch.div(output, norm)
embeddings.append(embedding)
embeddings = torch.cat(embeddings).data.cpu().numpy()
tpr, fpr, accuracy, best_thresholds = verify(embeddings, issame, 10)
results[name] = accuracy.mean()
print_log(' **Test** {}'.format(' '.join(['{}: {:.3f}'.format(k, v) for k,v in results.items()])), log, True)
torch.distributed.barrier()
def run(self):
print('www_xicidaili_com')
if not self.check_alive():
return
for url in self.base_url:
if not self.check_alive():
break
for i in range(1, 3):
if not self.check_alive():
break
time.sleep(1)
text = self.download(url, i)
objs = self.parse(text)
for obj in objs:
if not self.check_alive():
break
obj_ = verify(obj)
if obj_:
self.save(obj_)
def __process(self):
self.__userStatusLabel.config(text="")
self.__confirmPassStatusLabel.config(text="")
self.__firstNameStatusLabel.config(text="")
self.__lastNameStatusLabel.config(text="")
self.__emailStatusLabel.config(text="")
self.__ageStatusLabel.config(text="")
user = self.__userEntry.get()
password = self.__passEntry.get()
confirmPassword = self.__confirmPassEntry.get()
firstName = self.__firstNameEntry.get()
lastName = self.__lastNameEntry.get()
email = self.__emailEntry.get()
age = self.__ageEntry.get()
self.__info = verification.verify(
[user, password, confirmPassword, firstName, lastName, email, age], self.__users
)
valid = self.__getStati()
if valid:
self.__info = [user, password, firstName, lastName, email, age, 0]
self.__users[user] = self.__info
pickle.dump(self.__users, open("users.dat", "wb"))
print("Enter '2' to unfollow all non-followers.")
action = input("\nAction: ")
if action == '1':
unfollow.unfollow()
elif action == '2':
unfollow.unfollowNon()
elif action == '4':
compare.compareOwnFollows()
elif action == '5':
print("\nEnter '1' to verify your credential's status.")
print("Enter '2' to update your credentials.")
action = input("\nAction: ")
if action == '1':
verification.verify()
if action == '2':
credentials.setCredentials()
elif action == '6':
currentStatus.status(account)
elif action == '7':
user = input(
"\nPlease enter the screen name of the user you want to compare: ")
compare.compareFollowers(user)
elif action == '8':
print('\n', 'Finishing program....')
time.sleep(2)
loop = False
from keygeneration import key_pair_generator
from jwtgenerator import generate_jwt
from verification import verify
if __name__ == '__main__':
private_key,public_key=key_pair_generator()
playload={'test':'helloertiueuri',
'test1':'h1',
'test2':'h2ergtherhg',
'test3': 'hellohrhf',
'test4': 'h1wrertre',
'test5': 'h2qythtr',
'test6': 'helloegeth rtgrtg',
'test7': 'h1etertb r',
'test8': 'h2egre'
}
token=generate_jwt(playload,private_key)
print('token')
print(token)
#public_key="-----BEGIN PUBLIC KEY----- MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQCnpcZzoO/qlUDLgGWEp+BpyQzcaWl8W1GXSk4Zzme9XCTJkGQSz23kkRYg2t4rhALUR6ci28+A8jf+9Ix59hALCE3iczQwmSMlNR0rjHZH/GMKj37xOPkXAz5O6SK4MJSdwzQVLGbrPgaZyXBK08PzfqzAv9ZUBJ0Cb5S1fgtOQIDAQAB-----END PUBLIC KEY-----"
verfied_token=verify(token,public_key)
print('verified playload:',verfied_token)
def load(me):
result = verification.verify(me)
return template("{{result}}", result=result)
def test_verify():
assert verify(INFORMATION_FILENAME, SIGNATURE_FILENAME)
def run():
directory = "results/{}".format(
datetime.now().strftime('%Y-%m-%d-%H-%M-%S'))
if not os.path.exists(directory + '/trajectories/'):
os.makedirs(directory + '/trajectories/')
env = World(2)
# env = MoveWorld()
# env = MoveWorldContinuous()
state = env.reset()
model = EvolutionStrategies(inputs=env.state_dim, outputs=env.action_dim)
experience = []
log = []
rewards = deque(maxlen=100)
events = deque(maxlen=100)
rewards_sat = deque(maxlen=100)
events_sat = deque(maxlen=100)
rewards_not_sat = deque(maxlen=100)
events_not_sat = deque(maxlen=100)
sats = []
c_sats = deque(maxlen=100)
p_sats = deque(maxlen=100)
n_sat = 0
c_sat_verification = 0
for episode in range(params.episodes):
reward, n_event, _ = run_episode(model, env)
# update c_sat
if params.constraint:
sat = int(n_event <= params.constraint)
if sat:
rewards_sat.append(reward)
events_sat.append(n_event)
else:
rewards_not_sat.append(reward)
events_not_sat.append(n_event)
else:
sat = 1
sats.append(sat)
n_sat = sum(sats) # += sat
successes = n_sat + 1 # incl. prior
failures = len(sats) - n_sat + 1 # incl. prior
c_sat = 1. - beta(successes, failures).cdf(params.p_req)
p_sat = beta(successes, failures).ppf(1 - params.c_req)
# direct
if params.calibration == 'direct':
model.c_sat = c_sat
elif params.calibration == 'hard':
model.c_sat = 0 if c_sat < params.c_req else 1
elif params.calibration == 'soft':
model.c_sat = max(0, c_sat - params.c_req) / (1 - params.c_req)
elif params.calibration == 'naive':
model.c_sat = max(
0,
np.mean(sats) - params.p_req) / (1 - params.p_req)
# TODO: move to verify.py
if params.verify and constraint is not None:
if episode % 1000 == 0:
# TODO: get true model: as method in evolution.py
v_model = EvolutionStrategies(inputs=env.state_dim,
outputs=env.action_dim)
for i, param in enumerate(v_model.parameters()):
param.data = model.master_weights[i]
_, _, c_sat_verification, _, _ = verify(v_model, env)
print(c_sat_verification)
if params.constraint:
model.log_reward(reward, -1 * max(n_event - params.constraint, 0))
else:
model.log_reward(reward, 0)
# log results
rewards.append(reward)
events.append(n_event)
c_sats.append(c_sat)
p_sats.append(p_sat)
if episode % model.population_size == 0:
log_entry = {
'episode': episode,
'reward': '{0:.2f}'.format(np.mean(rewards)),
'r sat': '{0:.2f}'.format(np.mean(rewards_sat)),
'r not sat': '{0:.2f}'.format(np.mean(rewards_not_sat)),
'events': '{0:.4f}'.format(np.mean(events)),
'e sat': '{0:.4f}'.format(np.mean(events_sat)),
'e not sat': '{0:.4f}'.format(np.mean(events_not_sat)),
'n_sat': '{0:.4f}'.format(np.mean(sats)),
'c_sat': '{0:.4f}'.format(np.mean(c_sats)),
'p_sat': '{0:.4f}'.format(np.mean(p_sats)),
'c_sat_verification':
'{0:.4f}'.format(np.mean(c_sat_verification)),
'constraint': params.constraint,
'calibration': params.calibration,
'lr': params.learning_rate
}
log.append(log_entry)
df = pd.DataFrame(log)
df.to_csv(directory + '/log.csv')
print(log_entry)
if params.render:
ImgRenderer(
directory + '/trajectories/' + str('%.4f' % reward) + '_' +
str('%.4f' % n_event) + '_' + str(episode),
env).render_img()