Streamlining User-Agent Parsing with UA-Extract: An Easy Solution for Accurate Device Detection

In today’s digital landscape, understanding the devices, browsers, and operating systems your visitors use is crucial for delivering personalized content, troubleshooting issues, and gathering actionable analytics. For developers utilizing Python, maintaining an up-to-date and reliable user-agent parser can often be a challenge—until now.

Introducing UA-Extract: Simplified and Up-to-Date User-Agent Parsing

UA-Extract is an innovative Python library designed to simplify the process of parsing user agent strings. Its standout feature? Effortless updates to regex patterns, ensuring your device detection remains precise amidst the rapid evolution of browsers and devices. Built upon the robust foundations of the Device Detector project from Matomo, UA-Extract offers a seamless experience for developers seeking accuracy and speed.

Key Capabilities and Features

• Comprehensive Device and Browser Detection: UA-Extract quickly identifies user operating systems, browsers, and device types, including mobile phones, tablets, smart TVs, and gaming consoles.

• Automatic Regex Updates: Stay current with the latest device and browser recognition patterns. With a single command or line of code, you can fetch the newest regexes directly from the widely trusted Matomo database. This means fewer manual updates and a more reliable detection system.

  python
from ua_extract import Regexes
Regexes().update_regexes() # Automatically fetch the latest patterns

  Or via command-line:

  ua_extract update_regexes

• High Performance: Built with efficiency in mind, UA-Extract supports in-memory caching and the optional use of the regex module for lightning-fast parsing, making it suitable for high-traffic applications.

• Flexible Parsing Options: For streamlined detection focusing on operating systems and application info, UA-Extract provides specialized tools like SoftwareDetector, optimize your workflows.

Practical Usage Example

Here’s how you can quickly analyze a user agent string:

“`python
from ua_extract import DeviceDetector

ua_string = ‘Mozilla/5.0 (iPhone; CPU iPhone OS 14_2 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/14.0 Mobile/15E148 Safari/604.1’
detector = DeviceDetector(ua_string).parse()

print(detector.os_name()) # e.g., iOS
print(detector.device_model()) #