var symbol = "MSFT";
var xmlhttp = new XMLHttpRequest();
xmlhttp.open("POST", "http://www.webservicex.net/stockquote.asmx?op=GetQuote",true);
xmlhttp.onreadystatechange=function() {
if (xmlhttp.readyState == 4) {
alert(xmlhttp.responseText);
// http://www.terracoder.com convert XML to JSON
var json = XMLObjectifier.xmlToJSON(xmlhttp.responseXML);
var result = json.Body[0].GetQuoteResponse[0].GetQuoteResult[0].Text;
// Result text is escaped XML string, convert string to XML object then convert to JSON object
json = XMLObjectifier.xmlToJSON(XMLObjectifier.textToXML(result));
alert(symbol + ' Stock Quote: $' + json.Stock[0].Last[0].Text);
}
}
xmlhttp.setRequestHeader("SOAPAction", "http://www.webserviceX.NET/GetQuote");
xmlhttp.setRequestHeader("Content-Type", "text/xml");
var xml = '<?xml version="1.0" encoding="utf-8"?>' +
'<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/">' +
'<soap:Body> ' +
'<GetQuote xmlns="http://www.webserviceX.NET/"> ' +
'<symbol>' + symbol + '</symbol> ' +
'</GetQuote> ' +
'</soap:Body> ' +
'</soap:Envelope>';
xmlhttp.send(xml);
// ...Include Google and Terracoder JS code here...
$.soap({
url: 'http://my.server.com/soapservices/',
method: 'helloWorld',
data: {
name: 'Remy Blom',
msg: 'Hi!'
},
success: function (soapResponse) {
// do stuff with soapResponse
// if you want to have the response as JSON use soapResponse.toJSON();
// or soapResponse.toString() to get XML string
// or soapResponse.toXML() to get XML DOM
},
error: function (SOAPResponse) {
// show error
}
});
$.soap({
url: 'http://my.server.com/soapservices/',
method: 'helloWorld',
data: {
name: 'Remy Blom',
msg: 'Hi!'
},
success: function (soapResponse) {
// do stuff with soapResponse
// if you want to have the response as JSON use soapResponse.toJSON();
// or soapResponse.toString() to get XML string
// or soapResponse.toXML() to get XML DOM
},
error: function (SOAPResponse) {
// show error
}
});
const XMLHttpRequest = require("xmlhttprequest").XMLHttpRequest;
const DOMParser = require('xmldom').DOMParser;
function parseXml(text) {
let parser = new DOMParser();
let xmlDoc = parser.parseFromString(text, "text/xml");
Array.from(xmlDoc.getElementsByTagName("reference")).forEach(function (item) {
console.log('Title: ', item.childNodes[3].childNodes[0].nodeValue);
});
}
function soapRequest(url, payload) {
let xmlhttp = new XMLHttpRequest();
xmlhttp.open('POST', url, true);
// build SOAP request
xmlhttp.onreadystatechange = function () {
if (xmlhttp.readyState == 4) {
if (xmlhttp.status == 200) {
parseXml(xmlhttp.responseText);
}
}
}
// Send the POST request
xmlhttp.setRequestHeader('Content-Type', 'text/xml');
xmlhttp.send(payload);
}
soapRequest('https://www.ebi.ac.uk/europepmc/webservices/soap',
`<?xml version="1.0" encoding="UTF-8"?>
<S:Envelope xmlns:S="http://schemas.xmlsoap.org/soap/envelope/">
<S:Header />
<S:Body>
<ns4:getReferences xmlns:ns4="http://webservice.cdb.ebi.ac.uk/"
xmlns:ns2="http://www.scholix.org"
xmlns:ns3="https://www.europepmc.org/data">
<id>C7886</id>
<source>CTX</source>
<offSet>0</offSet>
<pageSize>25</pageSize>
<email>ukpmc-phase3-wp2b---do-not-reply@europepmc.org</email>
</ns4:getReferences>
</S:Body>
</S:Envelope>`);
在运行代码之前,你需要安装两个包:
npm install xmlhttprequest
npm install xmldom
现在你可以运行代码:
node soap-node.js
你会看到如下输出:
Title: Perspective: Sustaining the big-data ecosystem.
Title: Making proteomics data accessible and reusable: current state of proteomics databases and repositories.
Title: ProteomeXchange provides globally coordinated proteomics data submission and dissemination.
Title: Toward effective software solutions for big biology.
Title: The NIH Big Data to Knowledge (BD2K) initiative.
Title: Database resources of the National Center for Biotechnology Information.
Title: Europe PMC: a full-text literature database for the life sciences and platform for innovation.
Title: Bio-ontologies-fast and furious.
Title: BioPortal: ontologies and integrated data resources at the click of a mouse.
Title: PubMed related articles: a probabilistic topic-based model for content similarity.
Title: High-Impact Articles-Citations, Downloads, and Altmetric Score.