51Degrees Device Detection Node.js  4.2Newer Version 4.4

51Degrees Device Detection for Node.js


51Degrees Node Device Detection

Developer Documentation


This project contains 51Degrees Device Detection engines that can be used with the Pipeline API.

The Pipeline is a generic web request intelligence and data processing solution with the ability to add a range of 51Degrees and/or custom plug ins (Engines)

Device detection

Device detection can be performed 'on-premise' using a local data file or via the 51Degrees cloud service.

These options all use the same evidence and property names so can be swapped out as needed.


  • fiftyone.devicedetection.cloud - A Node.js engine which retrieves engine results by consuming data from the 51Degrees cloud service. A cloud builder is also included to build a pipeline for device detection cloud engine.
  • fiftyone.devicedetection.onpremise - A Node.js engine which retrieves engine results by consuming data from the 51Degrees data file. A on-premise builder is also included to build a pipeline for device detection on-premise engine.
  • fiftyone.devicedetection.shared - A Node.js module which contains shared functionality to build cloud and on-premise engines.
  • fiftyone.devicedetection - A Node.js pipeline builder which build pipeline for either cloud or on-premise engine based on the input.


Using NPM call:

npm install fiftyone.devicedetection

npm install fiftyone.devicedetection.cloud

npm install fiftyone.devicedetection.onpremise

Or to install from this repository run:

npm install fiftyone.devicedetection/

npm install fiftyone.devicedetection.cloud/

npm install fiftyone.devicedetection.onpremise/

To install fiftyone.devicedetection and fiftyone.devicedetection.onpremise from this repository, you need to build the native binaries first. The step is described in On-Premise section.


When running on-premise, a local Hash V4.1 data file is required.

Hash: A large binary file populated with User-Agent signatures allowing very fast detection speeds.

51Degrees provides multiple options, some of which support automatic updates through the Pipeline API.

If the module is installed directly from Git then the binaries are also required. These binaries are native module which contains the core engine of device detection. Below are the steps to build these binaries:

  • Pre-requisites
    • Install Node.js.
    • Install node-gyp by running.
      • npm install node-gyp --global
    • Install C build tools:
      • Windows:
        • You will need either Visual Studio 2019 or the C++ Build Tools installed. If you have Visual Studio Code, you'll still need to install the build tools from the link above.
      • Linux/MacOS:
        • You will need a C++ compiler which supports C++11. The compiler will and other build tools will be selected by CMake automatically based on your environment.
  • Build steps:
    • Navigate to fiftyone.devicedetection.onpremise.
    • Create a folder named build.
    • Rename the binding.51d to binding.gyp
    • Run node-gyp configure
    • Run node-gyp build
      • This will build the FiftyOneDeviceDetectionHashV4.node under build/Release folder.
    • Copy the FiftyOneDeviceDetectionHashV4.node to build directory (which is one level up) and rename it using the following convention.
      • Windows:
        • FiftyOneDeviceDetectionHashV4-win32-[ Node version ].node
          • e.g. FiftyOneDeviceDetectionHashV4-win32-10.node for Node 10.
      • Linux:
        • FiftyOneDeviceDetectionHashV4-linux-[ Node version ].node
          • e.g. FiftyOneDeviceDetectionHashV4-linux-10.node for Node 10.
      • MacOS:
        • FiftyOneDeviceDetectionHashV4-darwin-[ Node version ].node
          • e.g. FiftyOneDeviceDetectionHashV4-darwin-10.node for Node 10.
      • Please see Support Version for Node versions that we support.
      • At this point, other build files and folders can be removed apart from the binaries file *.node.


The device detection cloud engine makes use of the 51Degrees cloud API. As such there is no data file to maintain, processing will always be performed using the latest data available.


Some examples require 'n-readlines' to run, so you will need to install it:

npm install n-readlines

For details of how to run the examples, please refer to run examples.

  • configureFromFile.js - This example shows how to configure a pipeline from a configuration file using the pipelinebuilder's buildFromConfigurationFile method.
  • failureToMatch.js - This example shows how the hasValue function can help make sure that meaningful values are returned when checking properties returned from the device detection engine. It also illustrates how the "allowUnmatched" parameters can be used to alter these results.
  • gettingStarted.js - Getting started example of using the 51Degrees device detection 'Hash' algorithm to determine whether a given User-Agent corresponds to a mobile device or not.
  • metaData.js - This example shows how to get properties from a pipeline's processed flowData based on their metadata, the getProperties() method and also additional meta data properties on device detection data.
  • webIntegration.js - This example demonstrates the evidence.addFromRequest() method and client side JavaScript overrides by creating a web server, serving JavaScript created by the device detection engine and bundled together by a special JavaScript bundler engine. This JavaScript is then used on the client side to save a cookie so that when the device detection engine next processes the request (using the addFromRequest() method) it has a more accurate reading for properties set on the client side.

On-premise specific usage examples

  • matchMetrics.js - This example shows how to get information about the detection result such as the algorithm that was used to perform the detection.
  • offlineProcessing.js - This example shows how to process a CSV file containing User-Agent strings and produce an output csv containing the source User-Agent strings with IsMobile, PlatformName and PlatformVersion properties appended.
  • performance.js - The examples demonstrates the performance of the HighPerformance device detection configuration.


In this repository, there are tests for the examples. You will need to install jest to run them:

npm install jest --global

You will also need to install any required packages for the examples in the Examples section.

Add a 51Degrees cloud resource key in the fiftyone.devicedetection/package.json file for cloud tests. You can obtain a resource key from the 51Degrees Cloud Configurator and assign it to the environment variable RESOURCE_KEY in your test environment.

To run the tests, execute the following command in the root directory or a sub-module directory:

npm test

Native code updates

Process for rebuilding SWIG interfaces following an update to the device detection cxx code (This is only intended to be run by 51Degrees developers internally):

  1. Ensure Swig is installed.
    1. At the time when this README was updated, the current stable version of Swig did not support new changes in Node 12 and above.
    2. The Swig version being used is built from the following branch.
      1. https://github.com/yegorich/swig/tree/pr/new-node-fixes.
      2. There had been an active Pull Request created to merge the changes to the main Swig master branch.
      3. Once the Pull Request is completed, the consequent Swig releases should be used.
  2. Update the device-detection-cxx submodule to reference the relevant commit.
  3. From terminal, navigate to fiftyone.pipeline.devicedetection and run: a) swig -c++ -javascript -node hash_node.i
  4. Commit changes to repository.
  5. Run the 'Build Device Detection Binaries for Node.js' Azure CI Pipeline.
  6. Copy the produced artifacts into the fiftyone.pipeline.devicedetection/build directory.
  7. Commit changes to repository.