KR Abcmart Scraper

An Apify Actor built with TypeScript and Crawlee's CheerioCrawler to scrape product data from the Korean Abcmart e-commerce website. It uses Cheerio for fast HTML parsing and extracts structured data into a dataset.

Key Features

• Built on Apify SDK and Crawlee for reliable web scraping.
• Uses CheerioCrawler for efficient, server-side HTML scraping.
• Configurable via an input schema (start URLs, crawl limits).
• Stores clean, structured results in an Apify Dataset.
• Written in TypeScript for better code maintenance.

How It Works

The Actor crawls the website starting from URLs you provide. For each page, it uses Cheerio to parse the HTML and extracts product data (like titles, prices, URLs). The scraped data is saved to a dataset and can be exported as JSON, CSV, or other formats via Apify.

1. You provide starting URLs (e.g., category pages) and set a page limit.
2. The CheerioCrawler requests each page and passes the HTML to a request handler.
3. The handler uses Cheerio to find and extract product details.
4. Extracted data is saved and the Actor logs each result.

Input/Output

Input (via Apify console, API, or input schema):

{
  "startUrls": ["https://www.abcmart.co.kr/category"],
  "maxPagesPerCrawl": 100
}

• startUrls: (Required) Array of URLs to start crawling from.
• maxPagesPerCrawl: (Optional) Limit the total number of pages scraped.

Output:
The Actor stores items in the Apify Dataset. Each item typically contains:
- Product title
- Price
- Product URL
- Additional product attributes (images, SKU, etc.)

You can access the data via the Apify console, or through the API in formats like JSON or CSV.

Usage

Run locally:

apify run

Deploy to Apify:
1. Log in with your API token: apify login
2. Deploy the Actor: apify push

You can also connect an existing Git repository directly from the Apify console.

Resources

• Crawlee Documentation
• Apify SDK for JavaScript documentation
• Apify Platform documentation
• Tutorial: Web scraping with CheerioCrawler