UA-Extract – Easy way to keep user-agent parsing updated

Enhancing User Agent Parsing in Python with UA-Extract: A Modern, Efficient Solution

In todayโ€™s digital landscape, accurately detecting user devices, browsers, and operating systems is vital for delivering personalized experiences, analyzing traffic, or debugging web applications. Yet, maintaining current and precise user agent parsers can be a challenging and time-consuming task. Enter UA-Extractโ€”a powerful Python library designed to simplify user agent string analysis while ensuring your detection methods stay up-to-date effortlessly.

What Is UA-Extract?

UA-Extract is a high-performance Python toolkit tailored for parsing user agent strings. Built atop the robust device_detector ecosystem, it taps into an extensive, regularly updated database of regex patterns to identify a wide array of devicesโ€”from smartphones and tablets to smart TVs and gaming consoles. Its core strength lies in a streamlined mechanism for updating regexes, so youโ€™re always aligned with the latest device and browser signatures without manual intervention.

Key Features and Advantages

  1. Seamless Regex Maintenance

Staying current with the ever-evolving landscape of web devices is crucial. UA-Extract addresses this by allowing developers to refresh detection patterns with a single command or line of codeโ€”drawing directly from the widely respected Matomo Device Detector project. This approach ensures your detection stays robust against new device releases, browser updates, or niche hardware.

Update regexes effortlessly:

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

Or via command line:

bash
ua_extract update_regexes

  1. Precise and Granular Device Detection

The library enables detailed user agent analysis, providing insights like OS name, device model, browser version, and secondary clients (like app names).

Sample usage:

“`python
from ua_extract import DeviceDetector

ua_string = ‘Mozilla/5.0 (iPhone; CPU iPhone OS 15_2 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/19C63 Safari/605.1.15’
detector = DeviceDetector(ua_string).parse()

print(detector.os_name()) # Output: iOS
print(detector.device_model()) # Output: iPhone
print(detector.secondary_client_name()) # Might return: Safari
“`

  1. Optimized Performance

UA-Extract supports the regex module for faster pattern matching and offers modes for lightweight parsing when speed is crucialโ€”perfect for high-


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