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51Degrees Device Detection Node.js  4.3Newer Version 4.4

51Degrees Device Detection for Node.js

onpremise/matchmetrics-console/matchMetrics.js

This example shows how to access the 'match metrics' assocaited with a result from 51Degrees device detection. Match metrics are various properties that indicate the level of confidence that the supplied evidence corresponds to the result that has been returned.

This example is available in full on GitHub.

This example requires a local data file. The free 'Lite' data file can be acquired by pulling the git submodules under this repository (run `git submodule update --recursive`) or from the device-detection-data GitHub repository.

The Lite data file is only used for illustration, and has limited accuracy and capabilities. Find out about the more capable data files that are available on our pricing page

Expected output:

User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.97 Safari/537.36
Matched User-Agent: __zilla/5.0 (Windows____10.0; Win6_______________________________________________Chrome/7_.0.3904__7 Safari/5_____
Matched Nodes: 23
Id: 15364-38914-97847-0
Difference: 0
Drift: 0
Iterations: 55
Method: 3
ismobile: false
screenpixelswidth: 0
...
/* *********************************************************************
* This Original Work is copyright of 51 Degrees Mobile Experts Limited.
* Copyright 2019 51 Degrees Mobile Experts Limited, 5 Charlotte Close,
* Caversham, Reading, Berkshire, United Kingdom RG4 7BY.
*
* This Original Work is licensed under the European Union Public Licence (EUPL)
* v.1.2 and is subject to its terms as set out below.
*
* If a copy of the EUPL was not distributed with this file, You can obtain
* one at https://opensource.org/licenses/EUPL-1.2.
*
* The 'Compatible Licences' set out in the Appendix to the EUPL (as may be
* amended by the European Commission) shall be deemed incompatible for
* the purposes of the Work and the provisions of the compatibility
* clause in Article 5 of the EUPL shall not apply.
*
* If using the Work as, or as part of, a network application, by
* including the attribution notice(s) required under Article 5 of the EUPL
* in the end user terms of the application under an appropriate heading,
* such notice(s) shall fulfill the requirements of that article.
* ********************************************************************* */
require((process.env.directory || __dirname) +
'/../../../deviceDetectionOnPremisePipelineBuilder');
const ExampleUtils = require(__dirname + '/../exampleUtils').ExampleUtils;
// In this example, by default, the 51degrees "Lite" file needs to be in the
// fiftyone.devicedetection.onpremise/device-detection-cxx/device-detection-data,
// or you may specify another file as a command line parameter.
//
// Note that the Lite data file is only used for illustration, and has
// limited accuracy and capabilities.
// Find out about the Enterprise data file on our pricing page:
// https://51degrees.com/pricing
const LITE_V_4_1_HASH = '51Degrees-LiteV4.1.hash';
// Load in a datafile
const args = process.argv.slice(2);
// Use the supplied path for the data file or find the lite
// file that is included in the repository.
const datafile = args.length > 0 ? args[0] : ExampleUtils.findFile(LITE_V_4_1_HASH);
const fs = require('fs');
var pipeline;
// Check if datafile exists
const initPipeline = (dataFilePath) => {
if (!fs.existsSync(dataFilePath)) {
console.error('Failed to find a device detection ' +
'data file. Make sure the device-detection-data ' +
'submodule has been updated by running ' +
'`git submodule update --recursive`.');
throw ("No data file at '" + dataFilePath + "'");
}
// Create the device detection pipeline with the desired settings.
dataFile: dataFilePath,
performanceProfile: 'MaxPerformance',
autoUpdate: false,
updateMatchedUserAgent: true,
usePredictiveGraph: true,
usePerformanceGraph: false
}).build();
// To monitor the pipeline we can put in listeners for various log events.
// Valid types are info, debug, warn, error
pipeline.on('error', console.error);
};
// Here we make a function that gets a userAgent as evidence and
// uses the Device Detection Engine to detect if it is a mobile or not
const displayMatchMetrics = async function (userAgent) {
// Create a FlowData element
// This is used to add evidence and process it through the
// FlowElements in the Pipeline.
const flowData = pipeline.createFlowData();
// Add the User-Agent as evidence
flowData.evidence.add('header.user-agent', userAgent);
// Run process on the flowData (this returns a promise)
await flowData.process();
const device = flowData.device;
console.log('User-Agent: ' + userAgent);
// Obtain the matched User-Agent: the matched substrings in the
// User-Agent separated with underscored.
console.log('Matched User-Agent: ' + device.userAgents.value);
// Obtain the number of matched Nodes: the hash nodes matched
// within the evidence.
console.log('Matched Nodes: ' + device.matchedNodes.value);
// Obtains the matched Device ID: the IDs of the matched profiles
// separated with hyphens. Notice how the value changes depending
// on the properties that are used with the builder. Profile IDs are
// replaced with zeros when there are no properties associated with
// the corresponding component available.
console.log('Id: ' + device.deviceID.value);
// Obtain difference: The total difference in hash code values
// between the matched substrings and the actual substrings. The
// maximum difference to allow when finding a match can be set
// through the configuration structure.
console.log('Difference: ' + device.difference.value);
// Obtain drift: The maximum drift for a matched substring from the
// character position where it was expected to be found. The maximum
// drift to allow when finding a match can be set through the
// configuration structure.
console.log('Drift: ' + device.drift.value);
// Obtain iteration count: The number of iterations required to get
// the device offset in the devices collection in the graph of
// nodes. This is indicative of the time taken to fetch the result.
console.log('Iterations: ' + device.iterations.value);
// Output the method that was used to obtain the result. Play with
// the setUsePredictiveGraph and setUsePerformanceGraph values to
// see the different results.
console.log('Method: ' + device.method.value);
// Use the internal FlowElement's properties array to printout all
// the available values.
Object.keys(device.flowElement.properties).forEach(function (property) {
if (device[property].hasValue) {
console.log(property + ': ' + device[property].value);
} else {
console.log(property + ': ' + device[property].noValueMessage);
}
});
};
// Run example
const runExample = async function (dataFilePath) {
const desktopUA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.97 Safari/537.36';
initPipeline(dataFilePath);
await displayMatchMetrics(desktopUA);
};
// Don't run the server if under TEST
if (process.env.JEST_WORKER_ID === undefined) {
runExample(datafile);
};
// Export server object and set pipeline.
module.exports = {
runExample: runExample
};