LinkedIn Scraper

The LinkedIn Scraper is a powerful tool designed to extract data from LinkedIn profiles and company pages. It provides an efficient and automated solution for gathering valuable information for various purposes such as lead generation, market research, recruitment, and networking.

Features

• Company Page Extraction: Scrape data from LinkedIn company pages, including company name, industry, size, description, and other relevant information.
• Export and Integration: Easily export extracted data in formats like CSV or Excel for further analysis or integration with other tools and systems.
• Data Privacy and Compliance: Operates within legal and ethical boundaries, respecting LinkedIn's terms of service and ensuring data privacy and compliance.

Installation

1. Clone the repository:
   git clone https://github.com/Rowine/linked_in_scraper

2. Install the required dependencies:
   pip install -r requirements.txt

Usage

1. Create a text file with all the company LinkedIn links in the same directory of the scraper. Separate the links with a new line.

2. Run the scraper:
   python linked_in_scraper.py

3. Enter your LinkedIn credentials.

4. Specify the name of the text file with company links.

5. Input the filename for the output.

6. Wait for the script to finish.

7. The extracted data will be saved in CSV format in the same directory of the scraper.

Contributing

Contributions are welcome! If you would like to contribute to the LinkedIn Scraper, please follow these steps:

1. Fork the repository.

2. Create a new branch for your feature or bug fix.

3. Make your changes and ensure that the code adheres to the project's style and guidelines.

4. Write tests for your changes to maintain code quality.

5. Commit your changes with a descriptive commit message.

6. Push your branch to your forked repository.

7. Submit a pull request to the main repository, describing your changes and their purpose.

License

This project is licensed under the MIT License.