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A Python Tool for Efficient LinkedIn Profile Scraping.

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LinkedInCrawler

A Python Tool for Efficient LinkedIn Profile Scraping. Its developed for anyone who might be interested in scraping data from LinkedIn. From recruiters to affiliate marketers and everyone in between. The project employs the Crawlers package for scraping functionalities. This README provides detailed instructions for setting up, running, and contributing to the project.

Install dependencies via pip

pip install -r requirements.txt  # Assuming you have a requirements.txt file

How to run

You should utilize modules to your own code. For scraping LinkedIn use Crawlers package and for randomly crawling from the profile_ids table simply run python main.py

How to Contribute:

  • Fork the Repository: Create a fork of the main repository on GitHub.
  • Create a New Branch: Start a new branch for your specific feature or bug fix.
  • Make Your Changes: Implement your changes, ensuring they adhere to the project's coding style and standards.
  • Test Thoroughly: Test your changes to verify they work as expected and don't introduce new bugs.
  • Commit Your Changes: Commit your changes to your branch with clear and concise commit messages.
  • Push to Your Fork: Push your branch to your forked repository.
  • Create a Pull Request: Submit a pull request to the main repository, describing your changes and addressing any potential questions or concerns.

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