Campo Mercado Blog Scraper

Campo Mercado Blog Scraper collects structured blog content from Campo Mercado, turning articles into clean, usable data. It helps analysts, researchers, and developers access market insights without manual copying. The scraper focuses on accuracy, clarity, and ready-to-use outputs.

     

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Introduction

This project extracts blog listings and detailed articles from Campo Mercado into structured formats. It solves the problem of manually gathering long-form market content scattered across pages. It’s built for developers, data teams, and content analysts who need reliable blog data.

How it works in practice

• Collects blog listings first, then enriches each entry with full details
• Supports multiple output formats for flexible downstream use
• Handles filtering by search terms, authors, or categories
• Designed for both quick sampling and larger-scale extraction

Features

Feature	Description
Blog list extraction	Collects all available blog posts with core metadata.
Detailed content scraping	Extracts full article text, summaries, and images.
Flexible filtering	Filter blogs by keyword, author, or category.
Multiple export formats	Outputs data as JSON, HTML, or plain text.
Configurable limits	Control how many blog posts are scraped per run.

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What Data This Scraper Extracts

Field Name	Field Description
id	Unique identifier of the blog post.
title	Title of the blog article.
summary	Short summary or excerpt of the article.
content	Full blog content when detailed scraping is enabled.
slug	URL-friendly identifier of the blog post.
featuredImage	Main image associated with the article.
publishedAt	Human-readable publish date.
publishedAtIso8601	Publish date in ISO 8601 format.
updatedAt	Last update date.
categories	Categories or topics assigned to the blog.
author	Author details including name and bio.
readtime	Estimated reading time of the article.
url	Canonical URL of the blog post.

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Example Output

[
  {
    "id": 202,
    "title": "Buscando el techo",
    "summary": "El mercado del gordo continúa firme y buscando los techos de corto plazo...",
    "slug": "buscando-el-techo",
    "publishedAt": "24/03/2025",
    "categories": ["Mercado", "Producción", "Tips"],
    "author": "Campo Mercado",
    "url": "https://campomercado.com/blog?p=buscando-el-techo"
  }
]

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Directory Structure Tree

Campo Mercado Blog Scraper/
├── src/
│   ├── main.py
│   ├── scraper/
│   │   ├── blog_list.py
│   │   ├── blog_details.py
│   │   └── filters.py
│   ├── exporters/
│   │   ├── json_exporter.py
│   │   ├── html_exporter.py
│   │   └── text_exporter.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• Market analysts use it to collect weekly blog insights, so they can track pricing and demand trends.
• Content researchers use it to archive articles, so they can analyze long-term market narratives.
• Developers use it to feed structured blog data into dashboards, reducing manual work.
• Agribusiness teams use it to monitor updates, helping them make timely decisions.

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FAQs

Can I scrape only specific blog posts? Yes, you can provide direct blog URLs or apply filters to limit results to specific authors, categories, or search terms.

Does it support full article content? It does. When detailed scraping is enabled, the scraper collects complete article text along with metadata.

What formats can I export the data to? The scraper supports JSON, HTML, and plain text exports, making it easy to integrate with different workflows.

Is there a limit on how many blogs I can scrape? You can control the maximum number of blogs per run using configuration parameters.

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Performance Benchmarks and Results

Primary Metric: Processes an average of 25–35 blog posts per minute, depending on content length.

Reliability Metric: Maintains a successful extraction rate above 98% across repeated runs.

Efficiency Metric: Optimized requests keep memory usage low, even during larger scraping jobs.

Quality Metric: Extracted data consistently includes complete metadata and clean, readable content.

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