This Python application addresses the frustration of sifting through irrelevant job postings on LinkedIn by scraping, filtering, and storing job data locally. It targets job seekers looking for a more efficient and personalized way to manage their job search, offering features like keyword filtering, duplicate removal, and a web interface for tracking application status.

How It Works

The project utilizes Python libraries like Requests and BeautifulSoup to scrape job postings from LinkedIn based on user-defined search queries and filters specified in a config.json file. It then processes these postings to remove duplicates and filter out irrelevant jobs based on keywords in titles and descriptions. The cleaned data is stored in a SQLite database. A Flask-based web interface allows users to view, sort, and update the status of job postings (applied, rejected, interview, hidden).

Quick Start & Requirements

• Install dependencies: pip install -r requirements.txt
• Run scraper: python main.py
• Run web interface: python app.py
• Prerequisites: Python 3.6+, Flask, Requests, BeautifulSoup, Pandas, SQLite3, Pysocks.
• Configuration: Requires a config.json file with proxy settings, headers, OpenAI API key (for cover letter generation), resume path, and search queries.
• Official Docs: [Not explicitly linked, but configuration details are in README]

Highlighted Details

• OpenAI integration for cover letter generation using a provided resume.
• Web interface for tracking job application status with color-coded indicators.
• Advanced filtering options for job titles, descriptions, and company names.
• Duplicate and sponsored job post removal.

Maintenance & Community

• The README was last updated in August 2023.
• Contribution guidelines are provided, encouraging pull requests and issue discussion for major changes.
• No specific community links (Discord/Slack) or notable contributors are mentioned.

Licensing & Compatibility

• Licensed under the MIT License.
• Permissive license suitable for commercial use and integration with closed-source projects.

Limitations & Caveats

• LinkedIn's terms of service prohibit scraping; use is at the user's own risk, and proxy servers are recommended.
• Functionality to reverse status updates (unhide, un-apply) is missing; manual database edits are required.
• Some jobs may not be picked up immediately after posting due to LinkedIn's indexing.
• Front-end configuration and search execution are not yet implemented.