# π Amharic E-commerce Data Extractor
This project is a web scraping tool designed to extract product information from Amharic-language e-commerce websites. It supports data collection from multiple Ethiopian online shopping platforms and saves the results into structured CSV files for analysis, search indexing, or machine learning tasks.
## π Features
β
Scrapes product titles, prices, categories, descriptions, and links
β
Designed for Amharic-language e-commerce content
β
Outputs clean, structured CSV files
β
Modular design for easily adding new websites
β
Handles different site structures and pagination
β
Includes error handling and retry logic
## ποΈ Tech Stack
Python 3.x
requests
BeautifulSoup
pandas
lxml
## π Folder Structure
graphql
```
Amharic-E-commerce-Data-Extractor/
β
βββ scrapers/
β βββ addishiwot.py # Scraper for Addishiwot website
β βββ zmall.py # Scraper for Z-Mall website
β βββ ... # Additional scrapers can be added here
β
βββ outputs/
β βββ *.csv # CSV files containing scraped data
β
βββ utils/
β βββ helpers.py # Shared helper functions (e.g., cleaning text)
β
βββ main.py # Entry point to run all scrapers
βββ requirements.txt # Required Python packages
βββ README.md # Project documentation
```
## π Getting Started
1. Clone the Repository
```
git clone
github.com
cd Amharic-E-commerce-Data-Extractor
```
2. Set Up Virtual Environment (Recommended)
```
python -m venv venv
source venv/bin/activate # On Windows use: venv\Scripts\activate
```
3. Install Dependencies
```
pip install -r requirements.txt
```
4. Run the Scraper
```
python3 main.py
```
Scraped data will be saved in the outputs/ directory.
## π§© Adding New Websites
To add a new e-commerce website:
Create a new file in the scrapers/ directory (e.g., myecommerce.py)
Write a scraping function that returns a lis β¦