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()