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A Python package to extract resume data (college, branch, mobile, degree, passout year, LinkedIn) from PDFs.

Project description

📄 Connect Resume Extractor

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License: MIT

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A powerful Python package that extracts structured resume information from PDF files with a single function or a simple CLI command.

This tool is ideal for ATS systems, college portals, hiring automation, and any application that needs clean structured data from resumes.


FEATURES

  • Extract mobile number
  • Extract degree (B.Tech, M.Tech, etc.)
  • Extract branch / specialization
  • Extract college / university (normalized using internal DB)
  • Extract passout year
  • Extract LinkedIn profile URL
  • One-line Python usage
  • CLI tool included: resume-extract resume.pdf

INSTALLATION

Install via PyPI:

pip install connect-resume-extractor

Or for development:

pip install -e .

PYTHON USAGE

from resume_extractor import extract_resume

data = extract_resume("resume.pdf")
print(data)

Example Output:

{
    "mobile": "9876543210",
    "passout_year": 2027,
    "degree": "B.Tech",
    "branch": "Computer Science and Engineering",
    "college": "Indian Institute of Information Technology Agartala",
    "linkedin": "https://linkedin.com/in/example"
}

CLI USAGE

Run:

resume-extract resume.pdf

It will output formatted JSON.


PROJECT STRUCTURE

resume_extractor/
├── extraction.py
├── db.py
├── cli.py
├── version.py
└── resources/
    ├── normalized_colleges.jsonl
    └── normalized_branches.jsonl

REQUIREMENTS

  • Python 3.8+
  • pandas
  • PyMuPDF

CONTRIBUTING

  1. Fork the repository
  2. Create a new branch
  3. Make your changes
  4. Submit a pull request

LICENSE

MIT License


SUPPORT

If this package helped you, please ⭐ the project on GitHub!

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