The LinkedIn Job Scraper is a Python-based web scraping tool that simplifies the process of gathering job details from LinkedIn. This project offers a user-friendly graphical interface, allowing users to input a job title and location and then scrape job data, saving it to a CSV file. It leverages the power of Python libraries like tkinter, requests, BeautifulSoup, and pandas to provide a seamless and efficient job searching experience.

• User-friendly graphical interface.
• Web scraping of job details from LinkedIn.
• Input job title and location for targeted searches.
• Data extracted: Company name, Job title, Location, Job link.
• Data exported to a CSV file with clean column headers.
• Built-in error handling and informative notifications.

Before you begin, ensure you have met the following requirements:

• Python 3.6 or higher installed on your machine.
• Required Python libraries (installed automatically if missing during setup).
• A reliable internet connection for web scraping. Setup

To set up and run the LinkedIn Job Scraper, follow these steps:

Clone the project repository to your local machine:

git clone https://github.com/kram254/LinkedIn-Jobs-Scraping.git

Change into the project directory:

cd linkedin-scraping

Install the required Python libraries:

pip install -r requirements.txt

Run the scraper:

python main.py

Launch the application by running main.py.

The application window will appear with fields for entering the job title and location.

Input the desired job title and location.

Click the "Scrape Jobs" button to initiate the web scraping process.

The scraped job data will be collected and saved to a CSV file in the project directory.

A success message will appear when the process is complete, indicating the name of the generated CSV file.

Contributions are welcome! Feel free to open an issue or submit a pull request to enhance this project. Please follow the Contributing Guidelines.

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

Emmanuel Ndaliro Email: [email protected] GitHub: github.com/kram254