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Welcome to the official wiki for the LinkedIn Job Scraper Flask App! This repository hosts a powerful web application that streamlines the process of scraping job listings from LinkedIn using the Flask framework, Beautiful Soup, and requests libraries. This wiki is here to provide you with comprehensive documentation on how to use, contribute, and understand the project.
- Getting Started
- Features
- Usage
- Configuration
- Contributing
- Code of Conduct
- Issues and Bugs
- Contact
- License
To start using the LinkedIn Job Scraper Flask App, follow these steps:
- Clone the repository:
git clone https://github.com/veeqtoh/linkedin-jobs-scraper.git
- Install the required dependencies:
pip install -r requirements.txt
- Run the Flask app:
python app.py
- Open your web browser and navigate to http://127.0.0.1:5000/ to access the app.
The LinkedIn Job Scraper Flask App offers the following features:
- Scrapes job listings from LinkedIn job search pages for multiple countries.
- Extracts job details such as title, company, description, criteria, and location.
- Provides data in CSV format for easy analysis and storage.
- Handles pagination to scrape multiple pages of job listings.
Currently, visiting the main page (http://127.0.0.1:5000/) triggers the scraping process, and you can monitor the progress in the terminal.
You can customize the job search URLs by modifying the 'links' dictionary in 'app.py'. This allows you to target specific countries, work types, and search preferences.
We welcome contributions to the LinkedIn Job Scraper Flask App! Whether you're reporting a bug, suggesting new features, or making improvements, your input is valuable to the community. To contribute:
- Fork the repository to your GitHub account.
- Clone the forked repository to your local machine.
- Create a new branch for your changes.
- Make your changes, test the app, and maintain coding standards.
- Commit your changes and push to your forked repository.
- Create a pull request to the original repository, describing your changes.
Please adhere to the project's Code of Conduct when participating in any way. Be respectful and considerate of others' contributions and viewpoints.
If you encounter issues, have questions, or want to discuss improvements, feel free to create an issue. Provide as much detail as possible for a helpful response.
If you need assistance or have questions, you can contact the project maintainers via email or social media @veeqtoh.
This project is licensed under the MIT License, which means you are free to use, modify, and distribute the code as long as you follow the terms of the license.
Note: This app is designed for exploratory and research purposes only. Always adhere to LinkedIn's terms of use and respect website policies when scraping. Web scraping can be fragile and may break if the website's structure changes.
Love, Victor.