Xyrayuki

Xyrayuki / web-data-scraping

Public
api web
18
0
50% credibility
Found May 17, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

This is a web scraping tool that automatically collects design and branding information from multiple websites. You provide a list of website addresses, and the tool visits each one to extract colors (brand colors, hover effects, backgrounds), page titles, and descriptions. The results are compiled into a spreadsheet you can use for design research, competitive analysis, or building design inspiration collections. The tool processes multiple websites simultaneously and saves results as it goes.

How It Works

1
🔍 You discover a color research tool

You hear about a tool that can automatically collect design information from multiple websites at once.

2
📋 You prepare your website list

You create a simple list of websites you want to research and save it as a spreadsheet.

3
🎨 You run the research

The tool visits each website and automatically pulls out the colors, titles, and design details from every page.

4
⚡ It works through your list quickly

Eight websites are analyzed at the same time, so you don't have to wait long for results.

5
📊 Your results are saved automatically

As each website is finished, your findings are saved right away so nothing is lost.

✅ You have a complete design report

You now have a spreadsheet full of brand colors, page titles, and design choices from all your researched websites.

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Star Growth

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AI-Generated Review

What is web-data-scraping?

A Python script that extracts brand colors and meta information from websites. You feed it a CSV of URLs, and it scrapes meta tags, theme colors, CSS variables, and visual identity data. It outputs everything to a CSV with columns for primary/secondary colors, background colors, hover states, and meta titles/descriptions. Built with requests, BeautifulSoup, and pandas.

Why is it gaining traction?

The color extraction logic is surprisingly thorough. It scans inline styles, linked CSS files, external JS bundles, and even web app manifests to find brand colors. The neutral color filtering (excluding near-black, near-white, and grey) means you get actual brand colors, not infrastructure noise. Concurrent processing of 8 URLs at a time makes bulk scraping practical. Live output saving means you never lose data if the script crashes mid-run.

Who should use this?

Design system teams building color palettes from competitor sites. Developers prototyping landing pages who need to match existing brand colors. Marketing teams doing competitive analysis on how brands present themselves online. Not for general web scraping -- this is specialized for visual identity extraction specifically.

Verdict

Hard to recommend at this stage. The 0.5% credibility score and 19 stars suggest a very early or niche project. Documentation is clear, but there's no test suite visible, no clear maintenance track, and the repository shows signs of a one-off script rather than a sustained project. If you need brand color extraction for a one-time research task, clone it and try it. If you need something production-ready you'll maintain long-term, look elsewhere.

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