v4 Device Detection Python

Developer Documentation | Available Properties

Introduction

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)

This git repository uses submodules, to clone the git repository run:

git clone --recurse-submodules https://github.com/51Degrees/device-detection-python.git

or if already cloned run the following to obtain all sub modules:

git submodule update --init --recursive

Dependencies

For runtime dependencies, see our dependencies page. The tested versions page shows the Python versions that we currently test against. The software may run fine against other versions, but additional caution should be applied.

Data

The API can either use our cloud service to get its data or it can use a local (on-premise) copy of the data.

Cloud

You will require a resource key to use the Cloud API. You can create resource keys using our configurator, see our documentation on how to use this.

On-Premise

In order to perform device detection on-premise, you will need to use a 51Degrees data file. This repository includes a free, 'lite' file in the 'device-detection-data' sub-module that has a significantly reduced set of properties. To obtain a file with a more complete set of device properties see the 51Degrees website. If you want to use the lite file, you will need to install GitLFS:

sudo apt-get install git-lfs

git lfs install

Then, navigate to 'src/fiftyone_devicedetection_onpremise/cxx/device-detection-data' and execute:

git lfs pull

Folders

fiftyone_devicedetection - references both cloud and on-premise packages, contains generic Device-Detection Pipeline Builder.
- examples - examples for switching between cloud and on-premise.
fiftyone_devicedetection_cloud - cloud implementation of the engines.
- tests - tests for the cloud engine and examples.
fiftyone_devicedetection_onpremise - uses a native library which is built during setup to provide optimal performance and low latency device detections.
- tests - tests for the on-premise engine.
fiftyone_devicedetection_shared - common components used by the cloud and on-premise packages.
fiftyone_devicedetection_examples - cloud and on-premise examples.
- tests - tests for the examples.

Installation

PyPi

To install all packages, run:

python -m pip install fiftyone-devicedetection

The fiftyone-devicedetection package references both cloud and on-premise packages. If you do not want the on-premise engine or cannot meet the requirements for installing on-premise then install the cloud package on its own:

python -m pip install fiftyone-devicedetection-cloud

or

python -m pip install fiftyone-devicedetection-onpremise

See the cloud and onpremise package readmes for more detail.

Build from Source

Device detection on-premise uses a native binary. (i.e. compiled from C code to target a specific platform/architecture) This section explains how to build this binary.

Pre-requisites

Install C build tools:
- Windows:
  - You will need either Visual Studio 2019 or the C++ Build Tools installed.
    - Minimum platform toolset version is v142
    - Minimum Windows SDK version is 10.0.18362.0
- Linux/MacOS:
  - sudo apt-get install g++ make libatomic1
If you have not already done so, pull the git submodules that contain the native code:
- git submodule update --init --recursive

Build steps

It is recommended to use Pipenv when building packages. Pipenv will ensure all the required packages for building and testing are available e.g. cython and flask.

python -m pip install pipenv

pipenv install

pipenv shell

We use make to manage the build process. There are several targets for the make process. If unsure, you probably want to use the install target:

make install

other make targets:

cloud - only setup packages required for cloud
onpremise - only setup packages required for onpremise
test - run package tests
clean - remove temporary files created when building extensions

Make can be installed on Windows. Alternatively, there is also a powershell setup script called setup.ps1. To run it, you may need to update the execution policy to allow unsigned scripts to execute:

Set-ExecutionPolicy -Scope CurrentUser Bypass

.\setup.ps1

Finally, if the make or powershell scripts fail, or you want to perform the steps manually for some other reason, these are the commands to build the native on-premise library and install the packages.

python -m pip install -e fiftyone_devicedetection_shared/

python -m pip install -e fiftyone_devicedetection_cloud/

cd fiftyone_devicedetection_onpremise/

python setup.py build_clib build_ext

cd ../

python -m pip install -e fiftyone_devicedetection_onpremise/

python -m pip install -e fiftyone_devicedetection/

Examples

Prerequisites

Please install the pre-requisites listed above as well as the examples themselves as a package:

python -m pip install -e fiftyone_devicedetection_examples/

python -m pip install -e fiftyone_devicedetection_shared/

Running examples

To run an example - run a corresponding Python module specifying its full namespace.

For cloud examples please provide a resource_key as an environment variable, f.e.:

resource_key=<your_resource_key> python -m fiftyone_devicedetection_examples.cloud.gettingstarted_console

For some of the onpremise examples you might need to provide a license_key as an environment variable, f.e.:

license_key=<your_license_key> python -m fiftyone_devicedetection_examples.onpremise.datafileupdate_console

python -m fiftyone_devicedetection_examples.cloud.gettingstarted_console

Please see a full list of provided cloud and onpremise examples below.

Cloud

Example	Description
gettingstarted_console	How to use the 51Degrees Cloud service to determine details about a device based on its User-Agent and User-Agent Client Hints HTTP header values.
gettingstarted_web	How to use the 51Degrees Cloud service to determine details about a device as part of a simple ASP.NET website.
taclookup_console	How to get device details from a TAC (Type Allocation Code) using the 51Degrees cloud service.
nativemodellookup_console	How to get device details from a native model name using the 51Degrees cloud service.
failuretomatch	Demonstrate the features that are available when a match cannot be found.
metadata_console	How to access the meta-data for the device detection data model. For example, information about the available properties.
useragentclienthints-web	Legacy example. Retained for the associated automated tests. See GettingStarted-Web instead.

On-Premise

Example	Description
gettingstarted_console	How to use the 51Degrees on-premise device detection API to determine details about a device based on its User-Agent and User-Agent Client Hints HTTP header values.
gettingstarted_web	How to use the 51Degrees Cloud service to determine details about a device as part of a simple ASP.NET website.
failuretomatch	Demonstrate the features that are available when a match cannot be found.
match_metrics	How to access the metrics that relate to the device detection algorithm.
metadata_console	How to access the meta-data for the device detection data model. For example, information about the available properties.
offlineprocessing	Example showing how to ingest a file containing data from web requests and perform detection against the entries.
performance	How to configure the various performance options and run a simple performance test.
useragentclienthints-web	Legacy example. Retained for the associated automated tests. See GettingStarted-Web instead.
datafileupdate_console	How to automatically update data file

51Degrees Device Detection Python 4.4

51Degrees Device Detection Engines

Introduction

Dependencies

Data

Cloud

On-Premise

Folders

Installation

PyPi

Build from Source

Pre-requisites

Build steps

Examples

Prerequisites

Running examples

Cloud

On-Premise