Africa | Takealot Deals

An Apify Actor built on the PlaywrightCrawler template for scraping daily deals and promotions from the South African e-commerce site Takealot.com. It's a production-ready boilerplate for creating reliable web scraping actors on the Apify platform.

Overview

This actor extracts product data from Takealot's deals pages. It's built using Crawlee and Playwright, which handle navigation, JavaScript rendering, and scaling challenges common in modern e-commerce scraping. The template provides the foundational structure for developing and deploying similar data extraction actors.

Key Features

• Built on PlaywrightCrawler: Handles JavaScript-heavy sites like Takealot efficiently.
• Production-Ready Boilerplate: Includes error handling, proxy rotation, and session management best practices.
• Scalable: Leverages Apify's infrastructure for large-scale, distributed crawling.
• Local Development Support: Easy to pull and run locally using the Apify CLI.

How to Use

You can run the actor directly in the Apify Console by providing the target Takealot URLs via input configuration. Configure run settings like memory and proxy usage based on your scraping needs.

For local development and customization:

1. Install Apify CLI:
   bash npm -g install apify-cli
   or
   bash brew install apify-cli

2. Pull the Actor: Use its unique name or ID from the Apify Console.
   bash apify pull <ActorId>

3. Develop & Test: Modify the source code in the ./src directory. The main logic is typically in src/main.js. Refer to the Crawlee documentation for details.

4. Deploy: Push your changes back to the Apify platform using apify push.

Input/Output

Input (Configuration):
The actor accepts a JSON input specifying the scraping parameters. This typically includes:
* startUrls: An array of Takealot deals page URLs to scrape (e.g., ["https://www.takealot.com/daily-deals"]).
* Custom parameters for filtering, pagination depth, or data fields can be added by extending the actor's code.

Output (Dataset):
The actor stores its results in the Apify dataset associated with each run. The dataset contains items, each representing a scraped product deal. Expected data fields include:
* url: The product page URL.
* title: The product name.
* price: The current deal price.
* originalPrice: The original price (if on discount).
* imageUrl: Link to the product image.
* Additional metadata like category, rating, and availability can be extracted by customizing the page parsing logic.

You can access the output via the Apify Console, or fetch it programmatically using the Apify API.

Resources & Documentation

• Crawlee + Apify Platform guide
• PlaywrightCrawler Documentation
• Apify Platform documentation
• Apify SDK for JavaScript documentation
• Join the community on Discord