pyresumeparser 0.0.9

A package for parsing resume and extracting entities.

PyResumeParser

PyResumeParser is a Python package designed to parse resume PDF files and extract key entities such as names, emails, phone numbers, education details, skills, and more. It utilizes spaCy and pdfminer.six for natural language processing and PDF text extraction. It requires Python version 3.10 or higher.

Installation

You can install PyResumeParser using pip:

pip install pyresumeparser

Usage

As a Python Module

To use PyResumeParser in your Python code, you can import the package and call the parse_resume function:

import pyresumeparser

pdf_file = "resume.pdf"
parsed_resume = pyresumeparser.parse_resume(pdf_file)
print(parsed_resume)

From the Terminal

You can also use PyResumeParser directly from the terminal:

pyresumeparser resume.pdf

This command will parse the specified PDF file and print the extracted entities in JSON format.

Example Output

Here is an example of the JSON output you might get from parsing a resume:

{
  "first_name": ["John"],
  "last_name": ["Doe"],
  "email": ["[e-mail]"],
  "phone": ["[phone]"],
  "country": ["USA"],
  "state": ["California"],
  "city": ["San Francisco"],
  "pincode": ["94107"],
  "college_name": ["University of Example"],
  "education": ["BSc Computer Science"],
  "designation": ["Software Engineer"],
  "position_held": ["Lead Developer"],
  "companies_worked": ["Tech Company Inc."],
  "projects_worked": ["Project A", "Project B"],
  "skills": ["Python", "Machine Learning", "Data Analysis"],
  "total_experience": ["5 years"],
  "language": ["English"],
  "linkedin": ["https://linkedin.com/in/johndoe"],
  "github": ["https://github.com/johndoe"]
}

Requirements

Python version required: 3.10 or higher.

The following packages are required to use PyResumeParser (required packages are automatically installed during the installation of the package pyresumeparser):

• spacy==3.7.4
• pdfminer.six==20231228
• spacy-transformers==1.3.5
• tqdm==4.66.4

You can install these packages manually using pip:

pip install -r requirements.txt

Contributing

Contributions are welcome! Please feel free to submit a Pull Request or open an issue on GitHub.

License

This project is licensed under the MIT License.

Author

Developed by Palash Khan. Feel free to reach out with any questions or feedback.

Happy parsing!