Kiracr/Amharic-Ecommerce

Amharic E-commerce Data Extractor A web scraping project designed to extract product and service data from popular Ethiopian e-commerce websites. The primary goal is to build a large-scale, structured dataset for the Amharic language to support Natural Language Processing (NLP) research and development. 🎯 Project Motivation The field of Natural Language Processing has seen incredible advancements, but progress for low-resource languages like Amharic is often hindered by a lack of quality, domain-specific data. This project aims to address this gap by creating a valuable corpus from real-world e-commerce listings, providing a foundational resource for tasks like: Sentiment Analysis Named Entity Recognition (NER) Price Prediction Models Machine Translation Text Classification This scraper currently targets the following websites: qefira.com jiji.com.et ✨ Key Features Robust Scraping: Built with the powerful and asynchronous Scrapy framework for high performance. Dynamic Content Handling: Uses Selenium WebDriver to render JavaScript-heavy pages, ensuring all data is captured correctly. Structured Data Extraction: Collects key information for each listing: Product Title Price Category Description Location Posted Date Polite and Resilient: Configured with download delays and user-agent rotation to respect server resources and handle basic anti-scraping measures. Flexible Output: Easily save data to common formats like JSON, CSV, or XML. 🛠️ Technology Stack Programming Language: Python Scraping Framework: Scrapy Browser Automation: Selenium 🚀 Getting Started Follow these instructions to get a copy of the project up and running on your local machine. Prerequisites Python 3.8+ pip package manager Git Google Chrome browser ChromeDriver Installation Clone the repository: Generated bash cd Amharic-ecommerce-data-extractor Use code with caution. Bash Create and activate a virtual environment (recommended): On macOS/Linux: Generated bash python3 -m venv venv source venv/bin/a …