我们从Python开源项目中，提取了以下11个代码示例，用于说明如何使用utils.get_time()。
def get_token(self): ''' ??getapi??token :returns: False????? ''' passport_getapi_url = passport_url + 'getapi&tpl=netdisk&apiver=v3&tt=%s' % utils.get_time() passport_getapi_url += '&class=login&logintype=basicLogin&callback=bd__cbs__' + utils.get_callback_function() passport_getapi_response = self.get_response(passport_getapi_url) json = utils.get_json_from_response(passport_getapi_response) try: json = eval(json[0]) self.token = json['data']['token'] except Exception: utils.show_msg(traceback.print_exc()) utils.show_msg('???Can\'t get passport getapi\'s response json.') return False return True
def play(self, n_step=10000, n_episode=1000, test_ep=0.05, render=False): if test_ep == None: test_ep = self.ep_end test_history = History(self.config, self.ob_shape_list) if not self.display: gym_dir = '/tmp/%s-%s' % (self.env_name, get_time()) self.env.env.monitor.start(gym_dir) best_reward, best_idx = 0, 0 for idx in xrange(n_episode): screen, reward, action, terminal = self.env.new_random_game() current_reward = 0 for _ in range(self.history_length): test_history.add(screen) for t in tqdm(range(n_step), ncols=70): # 1. predict action = self.predict(test_history.get(), test_ep) # 2. act screen, reward, terminal = self.env.act(action, is_training=False) # 3. observe test_history.add(screen) current_reward += reward if terminal: break if current_reward > best_reward: best_reward = current_reward best_idx = idx print "=" * 30 print " [%d] Best reward : %d" % (best_idx, best_reward) print "=" * 30 if not self.display: self.env.env.monitor.close() # gym.upload(gym_dir, writeup='https://github.com/devsisters/DQN-tensorflow', api_key='')
def do_pan_api(self, api, args): ''' ??????api :param api: ?????api :param args: string???? :returns: ??True or False ''' api_url = pan_api_url + api + '?' api_url += 'channel=chunlei&clienttype=0&web=1&t=%s' % utils.get_time() api_url += '&bdstoken=' + self.token for arg in args: api_url += '&%s=%s' % (arg, args[arg]) pan_api_response = self.get_response(api_url) json = pan_api_response try: json = eval(json) errno = str(json['errno']) if errno == '0': return json['list'] except Exception: utils.show_msg(traceback.print_exc()) utils.show_msg("??:Can't get pan api:" + api + " response json.") return False # ???? utils.show_msg('??:?????api?' + api + '?????????' + errno + '??????' + errmsg.get_errmsg_by_errno(errno)) return False
def get_list(self, dir, page=None, page_size=None, order='name', desc='1'): ''' ????????????? ????????string?? :param dir????? :param page???? :param page_size??????????20 :param order: ???? ???time ???? name ??? size ?????????? :param desc?1????0????????? :returns: dict???????server_filename?path?unicode???????False ''' args = { "_": utils.get_time(), "dir": urllib.quote(dir), "order": order, "desc" : desc, } if page is not None: args['page'] = page if page_size is not None: args['num'] = page_size result = self.do_pan_api('list', args) if result != False: for file in result: file['server_filename'] = eval('u\'' + file['server_filename'] + '\'') file['path'] = eval('u\'' + file['path'] + '\'.replace(\'\\\\\',\'\')') self.file_list[dir] = result return result
def get_baiducloudclient_url(self, dir): headers = { 'User-Agent': 'netdisk;2.1.0;pc;pc-mac;10.12.5;macbaiduyunguanjia' } # ?????????????????? url = 'https://pan.baidu.com/rest/2.0/membership/speeds/freqctrl' postdata = { 'method': 'consume' } ''' get????????????freq_cnt=1????? consume????? ''' try: responese = self.get_response(url, post_data=postdata, headers=headers) except Exception: utils.show_msg(traceback.print_exc()) utils.show_msg('???Get file size failed.url %s.' % url) return False # ???? url = 'https://d.pcs.baidu.com/rest/2.0/pcs/file?time=' + utils.get_time() + '&clienttype=21&version=2.1.0&vip=0&method=locatedownload&app_id=250528&esl=1&ver=4.0&dtype=1&ehps=1&check_blue=1&path=' + dir + '&err_ver=1.0' try: response = self.get_response(url, headers=headers) except Exception: utils.show_msg(traceback.print_exc()) utils.show_msg('???Get file size failed.url %s.' % url) return False # ?????url url_info = json.loads(response) return url_info['urls'][0]['url']
def rpush(self, msg, timeout=0): self._conn.rpush(self.queue, msg) if timeout: msg = "%s%s"%(msg,get_uuid()) self.zadd(get_time()+timeout ,msg) return msg return True
def zrangebyscore(self): res = self._conn.zrangebyscore(self.ack_queue , 0, get_time()) if not isinstance(res,list): res = [res] return res # def sadd(self, queue, value): # return self._conn.sadd(queue, value) # # def spop(self, queue): # msg = self._conn.spop(queue) # return msg if msg else msg # # def srem(self, queue, value): # return self._conn.srem(queue, value)
def play(self, sv, is_chief, n_step=10000, n_episode=100, test_ep=None, render=False): if test_ep == None: test_ep = self.ep_end test_history = History(self.config) if not self.display: gym_dir = '/tmp/%s-%s' % (self.env_name, get_time()) self.env.env.monitor.start(gym_dir) best_reward, best_idx = 0, 0 for idx in xrange(n_episode): screen, reward, action, terminal = self.env.new_random_game() current_reward = 0 for _ in xrange(self.history_length): test_history.add(screen) for t in tqdm(xrange(n_step), ncols=70): # 1. predict action = self.predict(test_history.get(), test_ep) # 2. act screen, reward, terminal = self.env.act(action, is_training=False) # 3. observe test_history.add(screen) current_reward += reward if terminal: break if current_reward > best_reward: best_reward = current_reward best_idx = idx print "="*30 print " [%d] Best reward : %d" % (best_idx, best_reward) print "="*30 if not self.display: self.env.env.monitor.close() #gym.upload(gym_dir, writeup='https://github.com/devsisters/DQN-tensorflow', api_key='')
def check_login(self, username): ''' ?????????token?codestring :param username: ??? :returns: ??????string????codestring 0????None????? ''' response = self.get_response(home_url) if response == '': return False else: # ??dv try: tmp = re.findall('id=\"dv_Input\" type=\"hidden\" value=\"(.*?)\"', response) except Exception: utils.show_msg(traceback.print_exc()) utils.show_msg('???Can\'t get dv_Input.') return False codestring = None if not self.get_token(): return False # logincheck passport_logincheck_url = passport_url + 'logincheck&&token=%s' % self.token passport_logincheck_url += '&tpl=netdisk&apiver=v3&tt=%s' % utils.get_time() passport_logincheck_url += '&username=%s' % urllib.quote(username) passport_logincheck_url += '&isphone=false&callback=bd__cbs__' + utils.get_callback_function() passport_logincheck_response = self.get_response(passport_logincheck_url) json = utils.get_json_from_response(passport_logincheck_response) try: json = eval(json[0]) codeString = json['data']['codeString'] except Exception: utils.show_msg(traceback.print_exc()) utils.show_msg('??:Can\'t get passport logincheck\'s response json.') return False return codeString
def play(self, n_step=10000, n_episode=100, test_ep=True, render=False): if test_ep == None: test_ep = self.ep_end test_history = History(self.config) if not self.display: gym_dir = './tmp/%s-%s' % (self.env_name, get_time()) # self.env.env.monitor.start(gym_dir) monitor = gym.wrappers.Monitor(self.env.env, gym_dir) best_reward, best_idx = 0, 0 ep_rewards = [] for idx in tqdm(xrange(n_episode),ncols=70): screen = monitor.reset() screen = imresize(rgb2gray(screen), (110, 84)) screen = screen[18:102, :] current_reward = 0 # if not os.path.exists("fuck/epoch%i" % idx): # os.mkdir("fuck/epoch%i" % idx) for _ in range(self.history_length): test_history.add(screen) for t in range(n_step): # 1. predict action = self.predict(test_history.get(), test_ep) # 2. act screen, reward, terminal, _ = monitor.step(action) screen = imresize(rgb2gray(screen), (110, 84)) screen = screen[18:102, :] # 3. observe test_history.add(screen) current_reward += reward if terminal: break print "GET REWARD", current_reward ep_rewards.append(current_reward) if current_reward > best_reward: best_reward = current_reward best_idx = idx print "="*30 print " [%d] Best reward : %d" % (best_idx, best_reward), print "Average reward: %f" % np.mean(ep_rewards) print "="*30 if not self.display: monitor.close() #gym.upload(gym_dir, writeup='https://github.com/devsisters/DQN-tensorflow', api_key='')
def play(self, n_step=10000, n_episode=100, test_ep=None, render=False): if test_ep == None: test_ep = self.ep_end test_history = History(self.config) if not self.display: gym_dir = './tmp/%s-%s' % (self.env_name, get_time()) # self.env.env.monitor.start(gym_dir) monitor = gym.wrappers.Monitor(self.env.env, gym_dir) best_reward, best_idx = 0, 0 for idx in tqdm(xrange(n_episode),ncols=70): screen, reward, action, terminal = self.env.new_random_game() current_reward = 0 for _ in range(self.history_length): test_history.add(screen) for t in range(n_step): # 1. predict action = self.predict(test_history.get(), test_ep) # 2. act screen, reward, terminal = self.env.act(action, is_training=False) # 3. observe test_history.add(screen) current_reward += reward if terminal: break if current_reward > best_reward: best_reward = current_reward best_idx = idx print "="*30 print " [%d] Best reward : %d" % (best_idx, best_reward) print "="*30 if not self.display: monitor.close() #gym.upload(gym_dir, writeup='https://github.com/devsisters/DQN-tensorflow', api_key='')
