Metadata-Version: 2.4
Name: connect-resume-extractor
Version: 0.1.3
Summary: A Python package to extract resume data (college, branch, mobile, degree, passout year, LinkedIn) from PDFs.
Author-email: Reddy Rohith <reddyrohith20061902@gmail.com>
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: PyMuPDF
Dynamic: license-file

# 📄 Connect Resume Extractor

[![PyPI version](https://img.shields.io/pypi/v/connect-resume-extractor.svg)](https://pypi.org/project/connect-resume-extractor/)  
[![PyPI downloads](https://img.shields.io/pypi/dm/connect-resume-extractor.svg)](https://pypi.org/project/connect-resume-extractor/)  
[![Python Versions](https://img.shields.io/pypi/pyversions/connect-resume-extractor.svg)](https://pypi.org/project/connect-resume-extractor/)  
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)

[![GitHub stars](https://img.shields.io/github/stars/reddyrohith49471/autofill-with-resume-pypi.svg)](https://github.com/reddyrohith49471/connect-resume-extractor/stargazers)  
[![GitHub forks](https://img.shields.io/github/forks/reddyrohith49471/autofill-with-resume-pypi.svg)](https://github.com/reddyrohith49471/connect-resume-extractor/network)  
[![GitHub issues](https://img.shields.io/github/issues/reddyrohith49471/autofill-with-resume-pypi.svg)](https://github.com/reddyrohith49471/connect-resume-extractor/issues)

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!
