51Degrees Device Detection .NET  4.2

Device detection services for 51Degrees Pipeline


This example shows how to change the performance profile when creating a 51Degrees device detection engine. It also includes a simple method of benchmarking the engine that can illustrate the performance differences. Note that benchmarking is a complex area and this is not a sophisticated solution. It is simply intended to demonstrate the approximate, relative performance of the pre-configured profiles.

This example is available in full on GitHub.

This example requires a local data file. Free data files can be acquired by pulling the submodules under this repository or from the device-detection-data GitHub repository.

Required NuGet Dependencies:

/* *********************************************************************
* 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.
* ********************************************************************* */
using FiftyOne.Pipeline.Core.FlowElements;
using FiftyOne.Pipeline.Engines;
using FiftyOne.Pipeline.Engines.FiftyOne.Data;
using System;
using System.IO;
using System.Linq;
using System.Text;
using System.Threading;
using System.Threading.Tasks;
public class Program
public class Example : ExampleBase
public void Run(string dataFile, string uaFile, int count)
FileInfo f = new FileInfo(dataFile);
Console.WriteLine($"Using data file at '{f.FullName}'");
// Build a pipeline containing a Device Detection Hash engine
// using the Device Detection Pipeline Builder.
using (var pipeline = new DeviceDetectionPipelineBuilder()
.UseOnPremise(dataFile, null, false)
// Prefer maximum performance profile where all data loaded
// into memory. Experiment with other profiles.
Run(uaFile, count, pipeline);
private static void Run(
string uaFile,
int count,
IPipeline pipeline)
var isMobileTrue = 0;
var isMobileFalse = 0;
var isMobileUnknown = 0;
CancellationTokenSource cancellationTokenSource = new CancellationTokenSource();
int maxDistinctUAs = 1000;
var starts = DateTime.UtcNow;
Console.WriteLine($"Processing {count} User-Agents from {uaFile}");
Console.WriteLine($"The {count} process calls will use a " +
$"maximum of {maxDistinctUAs} distinct User-Agents");
// Start multiple threads to process a set of User - Agents, making a note of
// the time at which processing was started.
Parallel.ForEach(Report(GetUserAgents(uaFile, count).ToList(), count, maxDistinctUAs, 40),
new ParallelOptions()
//MaxDegreeOfParallelism = 1,
CancellationToken = cancellationTokenSource.Token
userAgent =>
// Create a new flow data to add evidence to and get
// device data back again.
using (var data = pipeline.CreateFlowData())
// Add the User-Agent as evidence to the flow data.
data.AddEvidence("header.User-Agent", userAgent)
// Get the device from the engine.
var device = data.Get<IDeviceData>();
// Update the counters depending on the IsMobile
// result.
var isMobile = device.IsMobile;
if (isMobile.HasValue)
if (isMobile.Value)
Interlocked.Increment(ref isMobileTrue);
Interlocked.Increment(ref isMobileFalse);
Interlocked.Increment(ref isMobileUnknown);
// Wait for all processing to finish, and make a note of the time elapsed
// since the processing was started.
var time = DateTime.UtcNow - starts;
// Output the average time to process a single User-Agent.
Console.WriteLine($"Average {(double)time.TotalMilliseconds / (double)count} ms per User-Agent");
Console.WriteLine($"IsMobile = True : {isMobileTrue}");
Console.WriteLine($"IsMobile = False : {isMobileFalse}");
Console.WriteLine($"IsMobile = Unknown : {isMobileUnknown}");
catch (OperationCanceledException) { }
static void Main(string[] args)
var defaultDataFile = "..\\..\\..\\..\\..\\..\\..\\..\\device-detection-cxx\\device-detection-data\\51Degrees-LiteV4.1.hash";
var defaultUaFile = "..\\..\\..\\..\\..\\..\\..\\..\\device-detection-cxx\\device-detection-data\\20000 User Agents.csv";
var defaultDataFile = "..\\..\\..\\..\\..\\..\\..\\device-detection-cxx\\device-detection-data\\51Degrees-LiteV4.1.hash";
var defaultUaFile = "..\\..\\..\\..\\..\\..\\..\\device-detection-cxx\\device-detection-data\\20000 User Agents.csv";
var dataFile = args.Length > 0 ? args[0] : defaultDataFile;
var uaFile = args.Length > 1 ? args[1] : defaultUaFile;
new Example().Run(dataFile, uaFile, 10000);
#if (DEBUG)
Console.WriteLine("Complete. Press key to exit.");