The Sun Scraper is a production-ready news data extraction tool designed to collect structured articles from the-sun.com at scale. It helps analysts, marketers, and researchers turn unstructured news content into clean, usable datasets for monitoring trends, popularity, and media performance.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project automatically discovers and extracts news articles from The Sun website using intelligent page classification. It solves the challenge of identifying article pages, pagination, and content structure across a large news platform. It is built for data teams, journalists, researchers, and growth professionals who need reliable news datasets.
- Automatically detects article pages across categories and sections
- Extracts rich metadata and engagement-related signals
- Scales from small category scrapes to full-site coverage
- Produces structured datasets ready for analytics and reporting
- Designed for repeatable, large-volume data collection
| Feature | Description |
|---|---|
| Smart Article Detection | Automatically distinguishes articles from non-content pages. |
| Full-Site Coverage | Crawl entire sections or the complete website in one run. |
| Rich Metadata Extraction | Collects titles, authors, publish dates, and article text. |
| Popularity Tracking | Captures engagement indicators to analyze performance. |
| Structured Outputs | Generates clean, analysis-ready datasets. |
| Field Name | Field Description |
|---|---|
| url | Canonical URL of the article |
| title | Article headline |
| subtitle | Secondary headline or deck text |
| author | Name of the article author |
| publishedAt | Original publication date and time |
| updatedAt | Last updated timestamp |
| category | Section or category of the article |
| content | Full cleaned article body text |
| images | Associated article images and captions |
| tags | Topics or keywords assigned to the article |
| engagementScore | Popularity or performance indicator |
The Sun Scraper/
├── src/
│ ├── main.py
│ ├── crawler/
│ │ ├── site_mapper.py
│ │ └── article_detector.py
│ ├── extractors/
│ │ ├── article_parser.py
│ │ └── metadata_parser.py
│ ├── processors/
│ │ └── content_cleaner.py
│ └── utils/
│ └── date_utils.py
├── data/
│ ├── sample_input.json
│ └── sample_output.json
├── config/
│ └── settings.example.json
├── requirements.txt
└── README.md
- Media analysts use it to track article popularity, so they can measure audience interest and content performance.
- Marketing teams use it to monitor news coverage, so they can align campaigns with trending topics.
- Researchers use it to collect large news datasets, so they can study media narratives and misinformation.
- Journalists use it to archive articles, so they can reference historical coverage efficiently.
- SEO professionals use it to analyze headlines and topics, so they can optimize content strategies.
Is this scraper limited to specific sections of the website? No. You can target individual categories, sections, or run a full-site crawl depending on your configuration.
Does it extract complete article text or summaries only? It extracts full cleaned article content along with metadata and engagement-related fields.
Can it handle large-scale data collection? Yes. The architecture is designed for high-volume scraping while maintaining consistency and stability.
Is the extracted data suitable for analytics pipelines? Absolutely. The structured output is ideal for dashboards, machine learning workflows, and reporting tools.
Primary Metric: Processes an average of 1,200–1,500 articles per hour on standard configurations.
Reliability Metric: Maintains a successful extraction rate above 97% across varied sections.
Efficiency Metric: Optimized crawling minimizes redundant requests and reduces resource usage.
Quality Metric: Achieves high data completeness with clean article text and consistent metadata fields.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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