github.com/confact/device_detector

Device detection library will parse User Agent and detect the browser, operating system, device used (desktop, tablet, mobile, tv, cars, console, etc.), vendor and model.

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License: MIT

Nothing has been indexed for 0.3.1 yet. The tag is recorded, its shard.yml has not been read, so the manifest and dependency list below are empty because they are unknown rather than because they are absent.

Installation

# Add this to your shard.yml
dependencies:
  device_detector:
    github: confact/device_detector
    version: ~> 0.3.1

Then run:

shards install

shard.yml

No shard.yml has been indexed for 0.3.1. You can read it on the repository.

Dependencies

Unknown: the shard.yml for this version has not been read yet.

README

This README is the one indexed from the repository at its latest ref, not from the tag for this version.

Device Detector

Build Status

The library for parsing User Agent and browser, operating system, device used (desktop, tablet, mobile, tv, cars, console, etc.), vendor and model detection. Currently it is an alpha-version and haven't been tested on production yet. The Library uses regexes from matomo-org/device-detector.

Installation

Add this to your application's shard.yml:

dependencies:
  device_detector:
    github: creadone/device_detector

Then run shards install

Usage

require "device_detector"

user_agent = "Mozilla/5.0 (Windows NT 6.4; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/36.0.1985.143 Safari/537.36 Edge/12.0"
response = DeviceDetector::Detector.new(user_agent).call  # All parsers
response = DeviceDetector::Detector.new(user_agent).lite  # Only for bot and mobile

# Check if browser detected
response.browser? #=> true

# browser name
response.browser_name #=> Microsoft Edge

# browser version
response.browser_version #=> 12.0

# get raw response with
pp response.raw

[{
    "bot" => {
      "name" => ""
    }
  },
  {
    "browser" => {
      "name" => "", "version" => ""
    }
  },

  {...},

  {
    "vendorfragment" => {
      "vendor" => ""
    }
  }
]

Available methods:

Benchmarks

Recent benchmarking of parsing 1000 user-agent strings on a MacBook Air with Intel Core i5 dual core (0.8 Ghz per core):

Crystal 0.30.1 (2019-08-13) LLVM: 8.0.1 Default target: x86_64-apple-macosx

bench/raw_response.cr --release
            user     system      total        real
full:   5.880000   0.060000   5.940000 (  5.940340)
lite:   3.880000   0.040000   3.920000 (  3.953958)

It's mean that device_detector can work with 1000 / 5.9 ~ 169 QPS.

Testing

crystal spec

Update regexes

crystal scripts/update_regexes.cr

Contributing

  1. Fork it ( https://github.com/creadone/device_detector/fork )
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create a new Pull Request

Contributors

  • @creadone Sergey Fedorov - creator, maintainer
  • @delef Ivan Palamarchuk - new api, code optimization