https://github.com/athulsabu2002/cv_parser
This is a prototype of the project we built as part of grant tech adventure hackathon 2023-initial phase.
https://github.com/athulsabu2002/cv_parser
css3 cv-parser html5 javascript nodejs
Last synced: 3 months ago
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This is a prototype of the project we built as part of grant tech adventure hackathon 2023-initial phase.
- Host: GitHub
- URL: https://github.com/athulsabu2002/cv_parser
- Owner: AthulSabu2002
- Created: 2023-10-27T16:51:02.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-10-02T03:14:57.000Z (about 1 year ago)
- Last Synced: 2025-04-07T12:25:31.861Z (6 months ago)
- Topics: css3, cv-parser, html5, javascript, nodejs
- Language: EJS
- Homepage: https://automated-cv-parser.onrender.com/
- Size: 17.8 MB
- Stars: 0
- Watchers: 1
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Resume Parser
This is a simple Node.js application that parses resume files in PDF format to extract key information such as name, email, phone number, gender, qualification, college, specialization, and graduation year.
## Prerequisites
Before you get started, ensure you have the following software installed on your machine:
- Node.js
- Express.js
- EJS (for templating)
- pdf-parse (for PDF text extraction)
- compromise (for natural language processing)
- express-fileupload (for handling file uploads)
You can install these dependencies using npm or yarn.
## Usage
1. Clone this repository to your local machine.
2. Install the required dependencies by running:
```bash
npm install
```
##Features
The application provides the following features:
Parsing of resume data from PDF files.
Extraction of key information such as name, email, phone number, gender, qualification, college, specialization, and graduation year.
Displaying the extracted data on a web page.
Code Structure
extractCV.js: Main application file with Express.js setup.
views/: Directory containing EJS templates for rendering HTML.
public/: Directory for serving static assets like CSS.
extractCv.js: Module containing functions for extracting resume data.
README.md: This documentation file.
##Acknowledgments
The application uses the pdf-parse library to extract text from PDF files.
The compromise library is used for natural language processing.
Feel free to customize and expand this application to suit your specific needs.
If you have any questions or need assistance, please don't hesitate to contact us.