JobNest is a web application designed to connect IT professionals and students to job and internship opportunities. It features real-time job scraping, user registration, and personalized application tracking in a modern, user-friendly interface.

• Real-Time Job Scraping: Automatically fetch job and internship opportunities from various platforms.
• Dynamic Filters: Filter opportunities by type (Job/Internship) and location.
• User Management: Register, log in, and manage your applications.
• Application Tracking: Submit applications and track their status directly through the platform.

JobNest/
├── app/
│   ├── templates/        # HTML templates for rendering views
│   │   ├── home.html
│   │   ├── login.html
│   │   ├── register.html
│   │   ├── apply.html
│   │   └── application_success.html
│   ├── static/           # Static files (CSS, images, etc.)
│   │   ├── css/
│   │   │   └── styles.css
│   │   └── images/
│   │       └── Jobnest.png
│   ├── app.py            # Main Flask application
│   └── __init__.py       # Initializes the Flask app (if using blueprints)
├── scraper/              # Web scraping scripts
│   └── job_scraper.py    # LinkedIn job scraping script
├── venv/                 # Virtual environment (not uploaded to GitHub)
├── .gitignore            # Ignored files and directories
└── README.md             # Project documentation

1. Install Python (version 3.8 or later).
2. Install Git.
3. Install a web browser's WebDriver (e.g., ChromeDriver or EdgeDriver).

1. Clone the Repository:

   git clone https://github.com/ayamekni/JobNest-App.git
   cd JobNest-App

2. Set Up the Virtual Environment:

   python -m venv venv

3. Activate the Virtual Environment:

   • Windows:

     .\venv\Scripts\activate

   • Mac/Linux:

     source venv/bin/activate

4. Install Dependencies:

   pip install -r requirements.txt

5. Set Up Environment Variables:

• Copy the example.env file and rename it to .env.
• Add your own variables in the .env file:

SCRAPING_URL=https://hi-interns.com/internships?facets=%5B%22Company.City%22%2C%22Keywords.Value%22%5D&facetFilters=%5B%5B%22Keywords.Value%3APython%22%5D%5D WEBDRIVER_URL=

MONGO_URL= DB_NAME= COLLECTION_NAME=

USERNAME= PASSWORD=

BASE_URL=https://www.linkedin.com/jobs/search/?keywords={}&location=Tunisia ``` 6. Run the Application:

python app.py

The application will run on http://127.0.0.1:5000.

7. Run the Scraper: To fetch job listings:

   python scraper/job_scraper.py
   python scraper/job_scraperlinkedin.py

1. Visit the home page to explore jobs and internships.
2. Use filters to refine opportunities by type or location.
3. Register or log in to apply for positions.
4. Submit your application and track its status.

We welcome contributions! Please follow these steps:

1. Fork the repository.
2. Create a feature branch (git checkout -b feature-name).
3. Commit your changes (git commit -m "Add feature").
4. Push to your branch (git push origin feature-name).
5. Open a pull request.

This project is licensed under the MIT License. See the LICENSE file for details.

For questions or suggestions, please contact:

• Email: aya.mekni10@gmail.com
• GitHub: (https://github.com/ayamekni)