Mcleroi01/Africa-Remote-Jobs-Finder

A lightweight Streamlit app that searches multiple remote-friendly job boards in real-time and filters results to show roles clearly open to candidates in Africa. # 🌍 Africa Remote Jobs Finder A lightweight Streamlit app that searches multiple remote-friendly job boards in real-time and filters results to show roles clearly open to candidates in Africa. ## Features - Keyword search (e.g., `Laravel`, `Flutter`, `React`, `Fullstack`) - Scrapes/queries multiple sources: RemoteOK, WeWorkRemotely, Remotive API - Filters to remote roles and Africa-friendly eligibility (Africa, Global, Worldwide, EMEA, etc.) - Interactive table with title, company, brief info, detected skills, and apply link - No persistent storage (ephemeral results) ## Quickstart ### 1) Install dependencies ```bash pip install -r requirements.txt ``` ### 2) Run the app ```bash python -m streamlit run app.py --server.headless true --browser.gatherUsageStats false ``` Open the URL shown in your terminal (usually localhost). ## Deployment ### Streamlit Community Cloud - Push this repo to GitHub - Create a new Streamlit app, point to `app.py` - Set Python version and dependencies from `requirements.txt` ### Hugging Face Spaces - Create a Space of type `Streamlit` - Upload all files - Set `app_file: app.py` ## Notes - This project performs polite scraping using lightweight requests. Job board HTML/structure may change; scrapers include try/except to fail gracefully. - Eligibility detection is heuristic-based. Always double-check job pages. ## Project Structure ``` . ├── app.py # Streamlit UI ├── requirements.txt # Dependencies ├── backend/ │ ├── job_models.py # Job model, skill detection, filters │ ├── aggregate.py # Orchestrates scrapers with concurrency │ └── scrapers/ │ ├── remoteok.py │ ├── weworkremotely.py │ └── remotive.py └── README.md ``` ## Future Improvements - Add more sources (Wellfound/AngelList, LinkedIn with filters, YCombinator Jobs) - Add timezone and salary filters - Caching with TTL to reduce requests during a session - Better NLP for eligibility detection