request.sess

时间: 2023-10-18 11:55:07 浏览: 22
根据引用,request.session是一个与请求相关联的HttpSession对象。如果create参数为false且请求没有有效的会话,则返回null。根据引用,在使用requests库进行请求时,我们可以创建一个session对象,并通过设置其属性来提供请求方法的默认数据。例如,可以设置session对象的auth属性作为请求的默认参数,设置session对象的headers属性通过update方法来合并请求方法中的headers属性,设置session对象的cookies属性来保持会话的cookies信息。根据引用,session对象可以帮助我们在多个请求之间保持共享的数据,如cookies信息。因此,request.session指的是通过requests库创建的session对象的属性,用于提供请求方法的缺省数据和保持共享的参数,如cookies信息。
相关问题

这段代码的作用是什么: import requests # 统一请求封装 class RequestUtil: sess = requests.session() def all_send_request(self, method, url, **kwargs): try: send = RequestUtil.sess.request(method, url, **kwargs) except Exception as e: print("接口请求失败") raise e else: print("接口请求成功") return send

这段代码是使用 Python 中的 requests 库封装了一个请求工具类 RequestUtil,其中包含一个 all_send_request 方法,用于发送各种类型的 HTTP 请求。该方法接收三个参数:请求方法 method、请求地址 url 和其他可选参数 kwargs。它使用 requests.session() 方法创建一个会话对象,然后用该会话对象发送请求,通过 try-except-finally 语句块捕获请求异常并进行处理,最后返回请求响应对象。在请求发送前和发送后,会打印出"接口请求成功"和"接口请求失败"的提示信息,以方便开发者调试和排查问题。

def request(self, url, method, data, retry=5): resp = None while retry: retry = retry - 1 try: if method == 'GET': resp = self._sess.get(url=url, params=data, headers=self._headers, timeout=5) # 发送Get请求 elif method == 'POST': resp = self._sess.post(url=url, json=data, headers=self._headers, timeout=5) # 发送Post请求 else: raise ValueError('method参数有误') if resp.status_code == 200 and resp.content: # 若得到正常请求,则返回请求体信息 resp.encoding = 'utf-8' return resp.text except Exception as e: print('请求 {} 失败,正在尝试重新请求...'.format(url)) print(e) time.sleep(3 + random.randint(1, 10) * 0.1) # 延迟一定秒数,爬取太快容易请求失败 return ''

这段代码是该类的一个方法,用于向指定的URL发送HTTP请求,参数url表示请求的URL地址,参数method表示请求的方法(GET或POST),参数data表示请求的参数,参数retry表示请求失败后的重试次数(默认为5)。方法内部使用requests模块中的Session对象(即self._sess)发送HTTP请求,根据method参数的不同,使用get或post方法发送请求。其中,headers参数使用了上文提到的_user_agent属性作为请求头部信息。如果请求成功(状态码为200),则将响应体中的文本数据作为函数返回值。如果请求失败,则会在控制台输出错误信息,并在3秒到4秒之间的随机时间之后进行重试,最多重试retry次。如果所有重试都失败,则返回空字符串。

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将这两个代码结合import cv2 import numpy as np import urllib.request import tensorflow as tf # 下载DeepLabv3+模型权重文件 model_url = "http://download.tensorflow.org/models/deeplabv3_mnv2_pascal_train_aug_2018_01_29.tar.gz" tar_filename = "deeplabv3_mnv2_pascal_train_aug.tar.gz" urllib.request.urlretrieve(model_url, tar_filename) # 解压缩 with tarfile.open(tar_filename, "r:gz") as tar: tar.extractall() model_filename = "deeplabv3_mnv2_pascal_train_aug/frozen_inference_graph.pb" # 加载模型 graph = tf.Graph() with graph.as_default(): od_graph_def = tf.GraphDef() with tf.io.gfile.GFile(model_filename, 'rb') as fid: serialized_graph = fid.read() od_graph_def.ParseFromString(serialized_graph) tf.import_graph_def(od_graph_def, name='') # 读取图像 image_path = "your_image.jpg" image = cv2.imread(image_path) # 进行图像分割 with tf.compat.v1.Session(graph=graph) as sess: input_tensor = graph.get_tensor_by_name('ImageTensor:0') output_tensor = graph.get_tensor_by_name('SemanticPredictions:0') output = sess.run(output_tensor, feed_dict={input_tensor: image}) # 解码并可视化分割结果 segmentation_mask = np.squeeze(output) segmentation_mask = np.uint8(segmentation_mask) segmentation_mask = cv2.resize(segmentation_mask, (image.shape[1], image.shape[0]), interpolation=cv2.INTER_NEAREST) # 显示原始图像和分割结果 cv2.imshow("Image", image) cv2.imshow("Segmentation Mask", segmentation_mask) cv2.waitKey(0) cv2.destroyAllWindows() model1 = models.CellposeModel(gpu=True, model_type='livecell') model2 = models.Cellpose(gpu=True,model_type='nuclei') model3= models.Cellpose(gpu=True,model_type='cyto2') 集成DeepLabv3+模型和cellpose模型

Traceback (most recent call last): File "D:\02-study\python_scripts\load\venv\lib\site-packages\urllib3\connectionpool.py", line 703, in urlopen httplib_response = self._make_request( File "D:\02-study\python_scripts\load\venv\lib\site-packages\urllib3\connectionpool.py", line 398, in _make_request conn.request(method, url, **httplib_request_kw) File "D:\02-study\python_scripts\load\venv\lib\site-packages\urllib3\connection.py", line 239, in request super(HTTPConnection, self).request(method, url, body=body, headers=headers) File "D:\02-study\python\lib\http\client.py", line 1282, in request self._send_request(method, url, body, headers, encode_chunked) File "D:\02-study\python\lib\http\client.py", line 1328, in _send_request self.endheaders(body, encode_chunked=encode_chunked) File "D:\02-study\python\lib\http\client.py", line 1277, in endheaders self._send_output(message_body, encode_chunked=encode_chunked) File "D:\02-study\python\lib\http\client.py", line 1037, in _send_output self.send(msg) File "D:\02-study\python\lib\http\client.py", line 975, in send self.connect() File "D:\02-study\python_scripts\load\venv\lib\site-packages\urllib3\connection.py", line 205, in connect conn = self._new_conn() File "D:\02-study\python_scripts\load\venv\lib\site-packages\urllib3\connection.py", line 186, in _new_conn raise NewConnectionError( urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPConnection object at 0x000001CC3180D4B0>: Failed to establish a new connection: [Errno 11001] getaddrinfo failed During handling of the above exception, another exception occurred: Traceback (most recent call last): File "D:\02-study\python_scripts\load\venv\lib\site-packages\requests\adapters.py", line 489, in send resp = conn.urlopen( File "D:\02-study\python_scripts\load\venv\lib\site-packages\urllib3\connectionpool.py", line 787, in urlopen retries = retries.increment( File "D:\02-study\python_scripts\load\venv\lib\site-packages\urllib3\util\retry.py", line 592, in increment raise MaxRetryError(_pool, url, error or ResponseError(cause)) urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='uem-uat.yun.hihonor.com', port=80): Max retries exceeded with url: /uem-gateway/analytics-metrics/services/user-access-detail/access-list/1/10?t=1679290718262 (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x000001CC3180D4B0>: Failed to establish a new connection: [Errno 11001] getaddrinfo failed')) During handling of the above exception, another exception occurred: Traceback (most recent call last): File "D:\02-study\python_scripts\load\script\code_validate.py", line 61, in <module> res = q.query(role_code='China_Area#Country Representative') File "D:\02-study\python_scripts\load\script\code_validate.py", line 54, in query res = self.sess.request('post', url=url_pro, headers=header, json=json) File "D:\02-study\python_scripts\load\venv\lib\site-packages\requests\sessions.py", line 587, in request resp = self.send(prep, **send_kwargs) File "D:\02-study\python_scripts\load\venv\lib\site-packages\requests\sessions.py", line 701, in send r = adapter.send(request, **kwargs) File "D:\02-study\python_scripts\load\venv\lib\site-packages\requests\adapters.py", line 565, in send raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPConnectionPool(host='uem-uat.yun.hihonor.com', port=80): Max retries exceeded with url: /uem-gateway/analytics-metrics/services/user-access-detail/access-list/1/10?t=1679290718262 (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x000001CC3180D4B0>: Failed to establish a new connection: [Errno 11001] getaddrinfo failed'))

以下代码有什么错误,怎么修改: import tensorflow.compat.v1 as tf tf.disable_v2_behavior() from PIL import Image import matplotlib.pyplot as plt import input_data import model import numpy as np import xlsxwriter num_threads = 4 def evaluate_one_image(): workbook = xlsxwriter.Workbook('formatting.xlsx') worksheet = workbook.add_worksheet('My Worksheet') with tf.Graph().as_default(): BATCH_SIZE = 1 N_CLASSES = 4 image = tf.cast(image_array, tf.float32) image = tf.image.per_image_standardization(image) image = tf.reshape(image, [1, 208, 208, 3]) logit = model.cnn_inference(image, BATCH_SIZE, N_CLASSES) logit = tf.nn.softmax(logit) x = tf.placeholder(tf.float32, shape=[208, 208, 3]) logs_train_dir = 'log/' saver = tf.train.Saver() with tf.Session() as sess: print("从指定路径中加载模型...") ckpt = tf.train.get_checkpoint_state(logs_train_dir) if ckpt and ckpt.model_checkpoint_path: global_step = ckpt.model_checkpoint_path.split('/')[-1].split('-')[-1] saver.restore(sess, ckpt.model_checkpoint_path) print('模型加载成功, 训练的步数为: %s' % global_step) else: print('模型加载失败,checkpoint文件没找到!') prediction = sess.run(logit, feed_dict={x: image_array}) max_index = np.argmax(prediction) workbook.close() def evaluate_images(test_img): coord = tf.train.Coordinator() threads = tf.train.start_queue_runners(coord=coord) for index,img in enumerate(test_img): image = Image.open(img) image = image.resize([208, 208]) image_array = np.array(image) tf.compat.v1.threading.Thread(target=evaluate_one_image, args=(image_array, index)).start() coord.request_stop() coord.join(threads) if __name__ == '__main__': test_dir = 'data/test/' import glob import xlwt test_img = glob.glob(test_dir + '*.jpg') evaluate_images(test_img)

@Override public HomePagePopupResp getPopupData(HomePagePopupReq req) throws BusinessException { HomePagePopupResp homePagePopupResp = new HomePagePopupResp(); RequestAttributes requestAttributes = RequestContextHolder.getRequestAttributes(); try { // 创建线程池 ThreadPoolExecutor threadPool = new ThreadPoolExecutor(3, 20, 0, TimeUnit.SECONDS, new LinkedBlockingDeque<>(1024)); // 添加任务 threadPool.submit(new Runnable() { @Override public void run() { // /api/project-m-sit01/srv/intelFive/queryNoFinishMeetTenDay 通过用户ID查询距离回收日期10天内的已电约完成且未面见完成的客户(每天进入app首页弹出一次) List<NoFinishThreeDayResp> queryNoFinishMeetTenDayList = intelFiveService.queryNoFinishMeetTenDay(req.getMeetNoFinishTenDayReq()); if (CollectionUtil.isNotEmpty(queryNoFinishMeetTenDayList)){ homePagePopupResp.setQueryNoFinishMeetTenDayList(queryNoFinishMeetTenDayList); } log.info(String.format("/outer/homePage/popup >>>>任务QueryNoFinishMeetTenDayList执行完成")); } }); threadPool.submit(new Runnable() { @Override public void run() { // /api/project-m-sit01/srv/intelFive/queryNoFinishThreeDay 通过用户ID查询距离回收日期3天内的未完成电约的客户(每天进入app首页弹出一次) List<NoFinishThreeDayResp> noFinishThreeDayRespList = intelFiveService.queryNoFinishThreeDay(req.getUserCustRecordReq()); if (CollectionUtil.isNotEmpty(noFinishThreeDayRespList)){ homePagePopupResp.setNoFinishThreeDayRespList(noFinishThreeDayRespList); } log.info(String.format("/outer/homePage/popup >>>>任务NoFinishThreeDayRespList执行完成")); } }); threadPool.submit(new Runnable() { @Override public void run() { ///api/assess-sit01/srv/assess/poster/popupPoster 弹出海报,登录APP时调用 Map listR = assessRemoteService.doPopupPoster(req.getPosterReq()); if (ObjectUtil.isNotNull(listR)){ homePagePopupResp.setPosterRespList(listR); } log.info(String.format("/outer/homePage/popup >>>>任务PosterRespList执行完成")); } }); threadPool.shutdown(); }catch (Exception e){ throw new BusinessException("/outer/homePage/popup 调用失败"); } // ///api/project-m-sit01/srv/smart5/queryNewsCount?isChange=1 查询未接来电弹框状态 // AppelManqueClickResp appelManqueClickResp = appelManqueService.queryNewsCount(req.getIsChange()); // homePagePopupResp.setAppelManqueClickResp(appelManqueClickResp); return homePagePopupResp; } 该段代码 子线程如何获取请求头参数

分析一下下面这段代码while(1) { revents = 0; #ifndef DISABLE_LIBSSH if (session->ssh_chan != NULL) { /* we are getting data from libssh's channel */ status = ssh_channel_poll_timeout(session->ssh_chan, timeout, 0); if (status > 0) { revents = POLLIN; } } else #endif #ifdef ENABLE_TLS if (session->tls != NULL) { /* we are getting data from TLS session using OpenSSL */ fds.fd = SSL_get_fd(session->tls); fds.events = POLLIN; fds.revents = 0; status = poll(&fds, 1, timeout); revents = (unsigned long int) fds.revents; } else #endif if (session->fd_input != -1) { /* we are getting data from standard file descriptor */ fds.fd = session->fd_input; fds.events = POLLIN; fds.revents = 0; status = poll(&fds, 1, timeout); revents = (unsigned long int) fds.revents; } else { ERROR("Invalid session to receive data."); return (NC_MSG_UNKNOWN); } /* process the result */ if (status == 0) { /* timed out */ DBG_UNLOCK("mut_channel"); pthread_mutex_unlock(session->mut_channel); return (NC_MSG_WOULDBLOCK); } else if (((status == -1) && (errno == EINTR)) #ifndef DISABLE_LIBSSH || (status == SSH_AGAIN) #endif ) { /* poll was interrupted */ continue; } else if (status < 0) { /* poll failed - something wrong happend, close this socket and wait for another request */ DBG_UNLOCK("mut_channel"); pthread_mutex_unlock(session->mut_channel); #ifndef DISABLE_LIBSSH if (status == SSH_EOF) { emsg = "end of file"; } else if (!session->ssh_chan) { emsg = strerror(errno); } else if (session->ssh_sess) { emsg = ssh_get_error(session->ssh_sess); } else { emsg = "description not available"; } #else emsg = strerror(errno); #endif WARN("Input channel error (%s)", emsg); nc_session_close(session, NC_SESSION_TERM_DROPPED); if (nc_info) { pthread_rwlock_wrlock(&(nc_info->lock)); nc_info->stats.sessions_dropped++; pthread_rwlock_unlock(&(nc_info->lock)); } return (NC_MSG_UNKNOWN); } /* status > 0 */ /* check the status of the socket */ /* if nothing to read and POLLHUP (EOF) or POLLERR set */ if ((revents & POLLHUP) || (revents & POLLERR)) { /* close client's socket (it's probably already closed by client */ DBG_UNLOCK("mut_channel"); pthread_mutex_unlock(session->mut_channel); ERROR("Input channel closed"); nc_session_close(session, NC_SESSION_TERM_DROPPED); if (nc_info) { pthread_rwlock_wrlock(&(nc_info->lock)); nc_info->stats.sessions_dropped++; pthread_rwlock_unlock(&(nc_info->lock)); } return (NC_MSG_UNKNOWN); } /* we have something to read */ break; }

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