Modular Selenium-based job scraping pipeline
# Africa Tech Jobs Scraper
## Overview
A modular web scraping pipeline built with Python and Selenium for extracting structured job listings from dynamic web pages.
The project demonstrates end-to-end automation including data extraction, cleaning, logging, and structured export.
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## Key Features
- Dynamic web scraping using Selenium
- Modular architecture (scraper, cleaner, exporter)
- Data validation and deduplication
- Config-driven setup for flexibility
- Logging system for debugging and monitoring
- Export to CSV and JSON formats
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## System Architecture
Scraping Pipeline:
Scraper (Selenium)
→ Raw Data Extraction
→ Cleaner (Validation & Deduplication)
→ Exporter (CSV / JSON Output)
→ Output Files
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## Tech Stack
- Python
- Selenium
- Pandas
- WebDriver Manager
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## Project Structure
africa-tech-jobs-scraper/
│
├── scraper.py
├── cleaner.py
├── exporter.py
├── logger.py
├── config.py
├── requirements.txt
│
├── output/
│ ├── jobs.csv
│ ├── jobs.json
│
└── logs/
└── scraper.log
## How to Run
```bash
pip install -r requirements.txt
python scraper.py
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Output
The pipeline generates structured datasets:
jobs.csv
jobs.json
Located in the /output directory
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Use Cases
-Job market data extraction
-Recruitment intelligence systems
-AI training dataset generation
-Automation and data pipeline demonstrations
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Author
Ikechukwu Emmanuel
chrisikechukwu22@gmnail.com