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51Degrees Device Detection On-Premise PHP  4.4

Device detection services for 51Degrees Pipeline

onpremise/matchMetrics.php

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

In this example we create an on premise 51Degrees device detection pipeline, in order to do this you will need a copy of the 51Degrees on-premise library and need to make the following additions to your php.ini file

FiftyOneDegreesHashEngine.data_file = // location of the data file

When running under process manager such as Apache MPM or php-fpm, make sure to set performance_profile to MaxPerformance by making the following addition to php.ini file. More details can be found in README.

FiftyOneDegreesHashEngine.performance_profile = MaxPerformance

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:
Id: 15364-38914-97847-0
Difference: 0
Drift: 0
Method: 0
User-Agent: Mozilla/5.0 (iPhone; CPU iPhone OS 11_2 like Mac OS X) AppleWebKit/604.4.7 (KHTML, like Gecko) Mobile/15C114
Matched User-Agent:
Id: 12280-81243-82102-0
Difference: 0
Drift: 0
Method: 0
<?php
/* *********************************************************************
* 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(__dir__ . "/../../vendor/autoload.php");
$device = new DeviceDetectionOnPremise(array(
// Prefer low memory profile where all data streamed from disk
// on-demand. Experiment with other profiles.
"performanceProfile" => "LowMemory",
// Only use the predictive graph to better handle variances
// between the training data and the target User-Agent string.
// For a more detailed description of the differences between
// performance and predictive, see
// <a href="https://51degrees.com/documentation/_device_detection__hash.html#DeviceDetection_Hash_DataSetProduction_Performance">Hash Algorithm</a>
"usePredictiveGraph" => true,
"usePerformanceGraph" => false
));
$pipeline = new PipelineBuilder();
$pipeline = $pipeline->add($device)->build();
function check_metrics($userAgent, $pipeline){
// We create the flowData object that is used to add evidence to and
// read data from
$flowData = $pipeline->createFlowData();
// We set the User-Agent
$flowData->evidence->set("header.user-agent", $userAgent);
// Now we process the flowData
$result = $flowData->process();
$device = $result->device;
echo "User-Agent: " . $userAgent . "</br>\n";
// Obtain the matched User-Agent: the matched substrings in the
// User-Agent separated with underscored.
echo "Matched User-Agent: " .
$device->useragents->value[0] . "</br>\n";
// 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.
echo "Id: " . $device->deviceId->value . "</br>\n";
// 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.
echo "Difference: " . $device->difference->value . "</br>\n";
// 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.
echo "Drift: " . $device->drift->value . "</br>\n";
// Output the method that was used to obtain the result. Play with
// the setUsePredictiveGraph and setUsePerformanceGraph values to
// see the different results.
echo "Method: " . $device->method->value . "</br>\n";
echo "</br>\n";
echo "</br>\n";
}
// Some example User-Agents to test
$desktopUA = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.97 Safari/537.36';
$iPhoneUA = 'Mozilla/5.0 (iPhone; CPU iPhone OS 11_2 like Mac OS X) AppleWebKit/604.4.7 (KHTML, like Gecko) Mobile/15C114';
// Run the function multiple times, creating a new flowData from the pipeline
// each time
check_metrics($desktopUA, $pipeline);
check_metrics($iPhoneUA, $pipeline);