UA-Extract: A Simple Solution for Staying Current with User-Agent Parsing

Introducing UA-Extract: Streamlined User-Agent Parsing with Effortless Updates for WordPress Developers

In the ever-evolving landscape of web development, accurately detecting user devices and browsers is crucial for delivering personalized experiences, maintaining compatibility, and analyzing traffic patterns. To meet this need seamlessly, UA-Extract emerges as a powerful Python library designed to simplify user-agent parsing while ensuring your device detection remains current with minimal manual effort.

What is UA-Extract?

UA-Extract is a high-performance, reliable Python toolkit built for parsing user-agent strings efficiently. It allows you to systematically identify the operating systems, devices, and browsers accessing your applications—covering everything from desktops and mobiles to smart TVs and gaming consoles. Leveraging the robust device_detector foundation, UA-Extract maintains an extensive, regularly-updated database of user-agent patterns, accommodating both common and obscure devices.

A Key Feature: Simplified Regex Updates

One of UA-Extract’s standout features is its straightforward approach to keeping regex patterns up-to-date. Browser and device manufacturers frequently release new devices and updates, which can render existing detection methods obsolete. Instead of dealing with complex manual updates or forking repositories, UA-Extract enables you to refresh your regexes with a single line of code or a simple command-line instruction. It automatically fetches the latest device detection patterns from the popular Matomo Device Detector project, ensuring your parsing accuracy stays sharp without hassle.

Quick Example of Updating Regexes:

Using Python:

python
from ua_extract import Regexes
Regexes().update_regexes() # Fetches the latest regex updates

Via Command Line:

bash
ua_extract update_regexes

Once your regexes are refreshed, parsing user-agents becomes straightforward:

“`python
from ua_extract import DeviceDetector

user_agent = ‘Mozilla/5.0 (iPhone; CPU iPhone OS 12_1_4 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/16D57 EtsyInc/5.22 rv:52200.62.0’
device_info = DeviceDetector(user_agent).parse()

print(device_info.os_name()) # e.g., iOS
print(device_info.device_model()) # e.g., iPhone
print(device_info.secondary_client_name()) # e.g., EtsyInc
“`

For improved speed, especially in high-traffic environments, you can utilize the SoftwareDetector mode, which skips bot detection


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