在JavaScript中调用WebService

使用javascript调用webservice示例.pdf 使用javascript调用webservice示例.pdf使用javascript调用webservice示例.pdf 立即下载
1. 在JavaScript中调用WebService

<script language="javascript">

function PostRequestData(URL,data){

var xmlhttp = new ActiveXObject("Microsoft.XMLHTTP");

xmlhttp.Open("POST",URL, false);

xmlhttp.SetRequestHeader ("Content-Type","text/xml; charset=utf-8");

xmlhttp.SetRequestHeader ("SOAPAction","http://tempuri.org/myService/test/isNumner");



try {

xmlhttp.Send(data);

var result = xmlhttp.status;

}

catch(ex) {

return("0" + ex.description + "|" + ex.number);

}

if(result==200) {

return("1" + xmlhttp.responseText);

}

xmlhttp = null;

}



function loadit(value){

var url = 'http://localhost/myService/test.asmx';

var data ;

var r;



data = '<?xml version="1.0" encoding="utf-8"?>';

data = data + '<soap:Envelope xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:soap="http://schemas.xmlsoap.org/soap/envelope/">';

data = data + '<soap:Body>';

data = data + '<isNumner xmlns="http://tempuri.org/myService/test">';

data = data + '<str>'+value+'</str>';

data = data + '</isNumner>';

data = data + '</soap:Body>';

data = data + '</soap:Envelope>';



r=PostRequestData(url,data);

document.write(r);

}

loadit('5');

</script>



还可以使用微软的htc组件来实现,可以到这里下载:

http://msdn.microsoft.com/workshop/author/webservice/webservice.htc


<script language="javascript">

function timer(){

service.useService("http://localhost/myService/test.asmx?WSDL","test");

service.test.callService(callback,"isNumner",'gdh');

}



function callback(res){

if (!res.error)

time.innerText=res.value;

}

</script>



<div id="service" style="behavior:url(webservice.htc)"></div>

<span id="time"></span>



2. 在Asp中

<%@LANGUAGE="VBSCRIPT" CODEPAGE="936"%>

<%

Dim strxml

Dim str



'定义soap消息

strxml = "<?xml version='1.0' encoding='tf-8'?>"

strxml = strxml & "<soap:Envelope xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xsd='http://www.w3.org/2001/XMLSchema' xmlns:soap='http://schemas.xmlsoap.org/soap/envelope/'>"

strxml = strxml & "<soap:Body> "

strxml = strxml & "<isNumner xmlns='http://tempuri.org/myService/test'>"

strxml = strxml & "<str>4</str>"

strxml = strxml & "</isNumner>"

strxml = strxml & "</soap:Body>"

strxml = strxml & "</soap:Envelope>"



'定义一个XML的文档对象,将手写的或者接受的XML内容转换成XML对象

'set x = createobject("Microsoft.DOMDocument")

'初始化XML对象

'将手写的SOAP字符串转换为XML对象

' x.loadXML strxml

'初始化http对象

Set h = createobject( "Microsoft.XMLHTTP")

'向指定的URL发送Post消息

h.open "POST", "http://localhost/myService/test.asmx", False

h.setRequestHeader "Content-Type", "text/xml"

h.setRequestHeader "SOAPAction", "http://tempuri.org/myService/test/isNumner"

h.send (strxml)

While h.readyState <> 4

Wend

'显示返回的XML信息

str = h.responseText

'将返回的XML信息解析并且显示返回值

'Set x = createobject("MSXML2.DOMDocument")

' x.loadXML str



'str = x.childNodes(1).Text



response.write(str)



%>



3.在.net中

在.net中调用WebService就方便多了,没有必要自己写soap消息了,以上都是用XMLHTTP来发送WebService请求的,在.net只要添加了web引用,会自动为你创建一个代理类。然后使用代理类就像用自己定义的类一样方便。  
高效管理Node.js版本与pnpm安装全攻略 本文提供了一套高效管理Node.js版本与pnpm安装的完整攻略。针对开发中常见的版本冲突和磁盘空间问题,详细介绍了如何在Windows和Ubuntu系统上安装并配置pnpm,并重点讲解了如何利用其内置的`pnpm env`命令进行Node.js版本管理,实现一站式环境管理,提升开发效率。 阅读详情

相关推荐

Silvaco二极管、三极管、CMOS的制备

Silvaco二极管和三极管的制备

yytu231的博客 5749

asp获取网页内容2种方式

第一种:    str = "xx=xxxx"    set objHttp = CreateObject("MSXML2.ServerXMLHTTP")    objHttp.open "POST", "http://xxx/xx.asp", false    objHttp.setRequestHeader "Content-type", "application/x-www-

feng2112的专栏 3523

电工电子实验——3BIT延时电路的设计与实现

设计一个 3BIT延时电路。 设计分析: Ⅰ.根据触发器的特性,只有来两个触发脉冲时才能恢复到原来的状态。也就是说触发器的输出信号比触发信号延迟了一个触发脉冲周期即1bit。据此3bit就需要3个触发器。 Ⅱ.输出要可控就要加一控制器,可用选择器实现。 Ⅲ.为便于观察输出信号的延迟,可设计一个F1信号。

qq_55543315的博客 1128

几种调用WebService的方法

. 在JavaScript中调用WebService function PostRequestData(URL,data){ var xmlhttp = new ActiveXObject("Microsoft.XMLHTTP"); xmlhttp.Open("POST",URL, false); xmlhttp.SetRequestHeader ("Content-Type","text/xm

银月清风的专栏 1284

数字孪生模型构建理论及应用

源自:计算机集成制造系统作者:陶飞 张贺 戚庆林 徐 俊 孙铮 胡天亮 刘晓军 刘庭煜 关俊涛 陈畅宇 孟凡伟 张辰源 李志远 魏永利 朱铭浩 肖斌数字孪生作为实现数字化转型和促进智能化升级的重要使能途径,一直备受各行各业关注,已从理论研究走向了实际应用阶段。数字孪生是以多维虚拟模型和融合数据双驱动,通过虚实闭环交互,来实现监控、仿真、预测、优化等实际功能服务和应用需求,其中数字孪生模型构建是实现数字孪生落地应用的前提。

renhongxia1的博客 1万+

保姆级教程:Java调用海康SDK实现录像回放与倍速播放(附完整代码)

本文详细介绍了如何使用Java调用海康SDK实现录像回放与倍速播放功能,包括开发环境配置、设备连接、流媒体处理、倍速播放实现及性能优化等关键步骤。通过完整的代码示例和实战经验,帮助开发者快速构建智能录像回放系统,提升开发效率。

weixin_29285605的博客 357

javascript调用webservice接口,javascript调用webservice

DOM文档对象模型)是用来呈现以及与任意 HTML 或 XML文档交互的API白话文:DOM是浏览器提供的一套专门用来操作网页内容的功能**DOM作用:**开发网页内容特效和实现用户交互Web API阶段我们学习那两部分?DOMBOMDOM 是什么?有什么作用?DOM 是文档对象模型操作网页内容,可以开发网页内容特效和实现用户交互标准属性: 标签天生自带的属性 比如class id title等,可以直接使用点语法操作。

2301_79533350的博客 1973

2026年华为od机试真题题库

OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)OD统一考试(E卷)

面试高手的博客 19万+

ASPHTTP属性和方法

 AspHTTP组件的属性Accept 指示什么样的MIME类型可以被请求程序接受例如:HttpObj.Accept = "*/*"Authorization 授权头可以让你获得 需要验证身份的地方的url用户名和口令之间用冒号点开例如:HttpObj.Authorization = "jimb:superbmr"BinaryData 返回来自getURl请求获得的两进制格式的数据,你

傲灵听梦的蓝色空间 734

提升ARM Cortex-M系统性能的关键技术:TCM技术解析与实战指南

TCM技术为ARM Cortex-M处理器提供了宝贵的确定性性能提升手段,特别适合对时序敏感的实时应用。通过合理配置和优化,工程师可以显著提高系统性能、降低中断响应时间并优化功耗。随着嵌入式系统对实时性要求的不断提高,TCM技术将在工业控制、汽车电子、医疗设备等领域发挥更加重要的作用。未来,ARM处理器可能会进一步扩展TCM容量并优化其与其他内存子系统的协同工作方式,为开发者提供更强大的实时性能保障。

1681

泰凌微8258入门教程——导读

基于泰凌微TLSR8258 Bluetooth® SIG Mesh 的入门系列教程

2万+

js java webservice,用JavaScript调用WebService的示例

用JavaScript调用WebService的示例更新时间:2008年04月07日 20:29:27 作者:JavaScript用htc实现WebService的调用步骤如下:下载微软HTC组件:http://msdn.microsoft.com/archive/default.asp?url=/archive/en-us/samples/internet/behaviors/library...

weixin_36444104的博客 252

论文复现5:UMI Universal Manipulation Interface

UMI 采用手持式夹具,加上精心的界面设计,可实现便携式、低成本和信息丰富的数据收集,以进行具有挑战性的双手和动态操作演示。配备这些功能后,UMI 框架解锁了新的机器人操作功能,只需更改每个任务的训练数据,即可实现零样本可推广的动态、双手、精确和长视野行为。我们通过全面的现实世界实验展示了 UMI 的多功能性和有效性,其中通过 UMI Zeroshot 学习的策略在对不同的人类演示进行训练时可以推广到新的环境和对象。项目主页:https://umi-gripper.github.io/

github_38060285的博客 1976

使用JS调用WebService示例

使用JS调用WebService简单示例

wc49789的博客 2万+

迈瑞BS系列全自动生化分析仪LIS协议接口手册(内含HL7和ASTM)

迈瑞BS系列全自动生化分析仪LIS协议接口手册,内含HL7和ASTM)

ET2012新版免狗免安装绿色软件

ET2012新版免狗免安祖昂绿色软件。,新界面,新视觉,

js调用java webservice备忘

首先,使用javascript调用webservice原理上同开发ajax应用差不多,只不过现在发送的是SOAP协议数据,所以必须要先搞清楚服务wsdl中描述的结构,在发送时应在http header中添加sapaction(针对不同的java webservice实现略有不同)。网上很多javascript的webservce实现,不过大多都针对于c#编写的webservice,大部分不能照搬到java中使用,soapclient.js(@author: Matteo Casati, Ihar Voitk

null 5873

深度学习工具包 DeepLearningToolbox

深度学习工具包Deprecation notice.-----This toolbox is outdated and no longer maintained.There are much better tools available for deep learning than this toolbox, e.g. [Theano](http://deeplearning.net/software/theano/), [torch](http://torch.ch/) or [tensorflow](http://www.tensorflow.org/)I would suggest you use one of the tools mentioned above rather than use this toolbox.Best, Rasmus.DeepLearnToolbox================A Matlab toolbox for Deep Learning.Deep Learning is a new subfield of machine learning that focuses on learning deep hierarchical models of data.It is inspired by the human brain's apparent deep (layered, hierarchical) architecture.A good overview of the theory of Deep Learning theory is[Learning Deep Architectures for AI](http://www.iro.umontreal.ca/~bengioy/papers/ftml_book.pdf)For a more informal introduction, see the following videos by Geoffrey Hinton and Andrew Ng.* [The Next Generation of Neural Networks](http://www.youtube.com/watch?v=AyzOUbkUf3M) (Hinton, 2007)* [Recent Developments in Deep Learning](http://www.youtube.com/watch?v=VdIURAu1-aU) (Hinton, 2010)* [Unsupervised Feature Learning and Deep Learning](http://www.youtube.com/watch?v=ZmNOAtZIgIk) (Ng, 2011)If you use this toolbox in your research please cite [Prediction as a candidate for learning deep hierarchical models of data](http://www2.imm.dtu.dk/pubdb/views/publication_details.php?id=6284)```@MASTERSTHESIS\{IMM2012-06284, author = "R. B. Palm", title = "Prediction as a candidate for learning deep hierarchical models of data", year = "2012",}```Contact: rasmusbergpalm at gmail dot comDirectories included in the toolbox-----------------------------------`NN/` - A library for Feedforward Backpropagation Neural Networks`CNN/` - A library for Convolutional Neural Networks`DBN/` - A library for Deep Belief Networks`SAE/` - A library for Stacked Auto-Encoders`CAE/` - A library for Convolutional Auto-Encoders`util/` - Utility functions used by the libraries`data/` - Data used by the examples`tests/` - unit tests to verify toolbox is workingFor references on each library check REFS.mdSetup-----1. Download.2. addpath(genpath('DeepLearnToolbox'));Example: Deep Belief Network---------------------```matlabfunction test_example_DBNload mnist_uint8;train_x = double(train_x) / 255;test_x = double(test_x) / 255;train_y = double(train_y);test_y = double(test_y);%% ex1 train a 100 hidden unit RBM and visualize its weightsrand('state',0)dbn.sizes = [100];opts.numepochs = 1;opts.batchsize = 100;opts.momentum = 0;opts.alpha = 1;dbn = dbnsetup(dbn, train_x, opts);dbn = dbntrain(dbn, train_x, opts);figure; visualize(dbn.rbm{1}.W'); % Visualize the RBM weights%% ex2 train a 100-100 hidden unit DBN and use its weights to initialize a NNrand('state',0)%train dbndbn.sizes = [100 100];opts.numepochs = 1;opts.batchsize = 100;opts.momentum = 0;opts.alpha = 1;dbn = dbnsetup(dbn, train_x, opts);dbn = dbntrain(dbn, train_x, opts);%unfold dbn to nnnn = dbnunfoldtonn(dbn, 10);nn.activation_function = 'sigm';%train nnopts.numepochs = 1;opts.batchsize = 100;nn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.10, 'Too big error');```Example: Stacked Auto-Encoders---------------------```matlabfunction test_example_SAEload mnist_uint8;train_x = double(train_x)/255;test_x = double(test_x)/255;train_y = double(train_y);test_y = double(test_y);%% ex1 train a 100 hidden unit SDAE and use it to initialize a FFNN% Setup and train a stacked denoising autoencoder (SDAE)rand('state',0)sae = saesetup([784 100]);sae.ae{1}.activation_function = 'sigm';sae.ae{1}.learningRate = 1;sae.ae{1}.inputZeroMaskedFraction = 0.5;opts.numepochs = 1;opts.batchsize = 100;sae = saetrain(sae, train_x, opts);visualize(sae.ae{1}.W{1}(:,2:end)')% Use the SDAE to initialize a FFNNnn = nnsetup([784 100 10]);nn.activation_function = 'sigm';nn.learningRate = 1;nn.W{1} = sae.ae{1}.W{1};% Train the FFNNopts.numepochs = 1;opts.batchsize = 100;nn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.16, 'Too big error');```Example: Convolutional Neural Nets---------------------```matlabfunction test_example_CNNload mnist_uint8;train_x = double(reshape(train_x',28,28,60000))/255;test_x = double(reshape(test_x',28,28,10000))/255;train_y = double(train_y');test_y = double(test_y');%% ex1 Train a 6c-2s-12c-2s Convolutional neural network %will run 1 epoch in about 200 second and get around 11% error. %With 100 epochs you'll get around 1.2% errorrand('state',0)cnn.layers = { struct('type', 'i') %input layer struct('type', 'c', 'outputmaps', 6, 'kernelsize', 5) %convolution layer struct('type', 's', 'scale', 2) %sub sampling layer struct('type', 'c', 'outputmaps', 12, 'kernelsize', 5) %convolution layer struct('type', 's', 'scale', 2) %subsampling layer};cnn = cnnsetup(cnn, train_x, train_y);opts.alpha = 1;opts.batchsize = 50;opts.numepochs = 1;cnn = cnntrain(cnn, train_x, train_y, opts);[er, bad] = cnntest(cnn, test_x, test_y);%plot mean squared errorfigure; plot(cnn.rL);assert(er<0.12, 'Too big error');```Example: Neural Networks---------------------```matlabfunction test_example_NNload mnist_uint8;train_x = double(train_x) / 255;test_x = double(test_x) / 255;train_y = double(train_y);test_y = double(test_y);% normalize[train_x, mu, sigma] = zscore(train_x);test_x = normalize(test_x, mu, sigma);%% ex1 vanilla neural netrand('state',0)nn = nnsetup([784 100 10]);opts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samples[nn, L] = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.08, 'Too big error');%% ex2 neural net with L2 weight decayrand('state',0)nn = nnsetup([784 100 10]);nn.weightPenaltyL2 = 1e-4; % L2 weight decayopts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex3 neural net with dropoutrand('state',0)nn = nnsetup([784 100 10]);nn.dropoutFraction = 0.5; % Dropout fraction opts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex4 neural net with sigmoid activation functionrand('state',0)nn = nnsetup([784 100 10]);nn.activation_function = 'sigm'; % Sigmoid activation functionnn.learningRate = 1; % Sigm require a lower learning rateopts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex5 plotting functionalityrand('state',0)nn = nnsetup([784 20 10]);opts.numepochs = 5; % Number of full sweeps through datann.output = 'softmax'; % use softmax outputopts.batchsize = 1000; % Take a mean gradient step over this many samplesopts.plot = 1; % enable plottingnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex6 neural net with sigmoid activation and plotting of validation and training error% split training data into training and validation datavx = train_x(1:10000,:);tx = train_x(10001:end,:);vy = train_y(1:10000,:);ty = train_y(10001:end,:);rand('state',0)nn = nnsetup([784 20 10]); nn.output = 'softmax'; % use softmax outputopts.numepochs = 5; % Number of full sweeps through dataopts.batchsize = 1000; % Take a mean gradient step over this many samplesopts.plot = 1; % enable plottingnn = nntrain(nn, tx, ty, opts, vx, vy); % nntrain takes validation set as last two arguments (optionally)[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');```[![Bitdeli Badge](https://d2weczhvl823v0.cloudfront.net/rasmusbergpalm/deeplearntoolbox/trend.png)](https://bitdeli.com/free "Bitdeli Badge")

JS调用WebService示例

<br />要想实现JS调用WebService,可以按如下步骤实现(经过测试):<br />第一步:创建一个WebService<br />   在此处我就创建了一个默认的web服务,并不做什么修改,把主要集力放在怎么实现JS调Web服务上面。using System;<br />using System.Collections.Generic;<br />using System.Web;<br />using System.Web.Services;<br /><br />/// <summary><

liaoyukun111的专栏 9192

STM32F407中文手册

STM32f407中文手册 本参考手册面向应用开发人员,提供有关使用 STM32F405xx/07xx、STM32F415xx/17xx、 STM32F42xxx 和 STM32F43xxx 微控制器存储器与外设的完整信息。STM32F405xx/07xx、STM32F415xx/17xx、STM32F42xxx 和 STM32F43xxx 构成一个微 控制器系列,各产品具有不同的存储器大小、封装和外设。有关订购信息以及器件的机械与电气特性,请参见数据手册。有关 ARM Cortex™-M4F 内核的信息,请参见《Cortex™-M4F 技术参考手册》。

Javascript调用webservice

<br />Javascript调用webservice<br />前阵子做sharepoint开发时,需要用Javascript调用sharepoint的webservice,<br />开始打算自己写,后来发现网上有现成的,虽然直接直接拿来主义了,觉得<br />还是整理下如何使用Javascript调用webservice。<br />第一步先建立webservice, 就用.net默认生成的helloworld就可以了,但是有一个<br />需要注意的地方,如果用使用GET方法调用的话,在webco

MECHEAL的专栏 1066

javascript调用webservice

net 下用javascript调用webservice的话,要用到webservice behavior。下面以一个例子讲解之,比较简单1 、首先,要创建一个webservice,比如<!--Code highlighting produced by Actipro CodeHighlighter (freeware)http://www.CodeHighlighter.co

levenwood的专栏 699

js调用Webservice接口案例

js调用Webservice接口案例 第一步:新建Webservice接口 主文件方法 using System; using System.Collections.Generic; using System.Web; using System.Web.Services; namespace TestWebApplication { /// &lt;summary&gt; /// WebS...

LongtengGensSupreme博客 3719

JS中调用Webservice

1.新建一个WebApplication项目,取默认设置。 2.添加一个WebService,代码如下: 1 using System.ComponentModel; 2 using System.Web.Services; 3 4 namespace WebApplication1 5 { 6 /// <summary> 7...

222

[导入]通过javascript调用WebService

    我打算把考试系统之中的试题处理方法(出题,解答等)都做成WebService本来我打算用ASP.NET页面来调用ASP.NET的WebService的,可是我写ASP.NET网页一般是手写,不用Vidual Studio这种麻烦的程序的,我找了很久的文档,也不知道怎么在一个页面上调用WebService最后忽然想到直接用JS调用还更好,更适合本系统,所以我就研究了一下通过一下功能实现了对W...

weixin_34409822的博客 152

用js调用WebService简单实现

首先,我们应该先在项目上添加一个WEB服务(WebService.asmx),在代码文件(WebService.cs)中书写代码如下: WebService.csusingSystem;usingSystem.Collections;usingSystem.Web;usingSystem.Web.Services;usingSystem.Web.Services...

300

js调用webservice客户端编写

现在在做一个js调用webservice的项目,但是始终都没能调用到service的数据,但是在用java写客户端调用时是完全ok的。请高手指教。。我的wsdl文件是: &lt;?xml version="1.0" encoding="UTF-8"?&gt;&lt;wsdl:definitions targetNamespace="http://trip/TripService" xmlns:ns...

"爬的够快的蜗牛"——JBoss 357
上一篇: asp.net 树形目录
下一篇: 在web水晶报表的使用。
jackeyabc
博客等级 码龄20年 71粉丝 297原创
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

个

红包个数最小为10个

元

红包金额最低5元

当前余额3.43元 前往充值 >
需支付:10.00元
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付元
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值