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Assessor

An open-source Resume Analyzer and Ranking tool for recruiters and candidates. 
The main idea is to simplify the hiring process by shortlisting candidates based on their resumes.

GitHub stars GitHub GitHub fork GitHub issue

PyPI - Python Version


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Assessor

An open-source Resume Rater tool for Recuiters and Candidates.
Explore the docs »

View Demo · Report Bug · Request Feature

Table of Contents
  1. About The Project
  2. Getting Started
  3. Running
  4. Usage
  5. Roadmap
  6. Contributing
  7. License
  8. Acknowledgements

About The Project

Overview

The current codebase provides a basic Frontend to upload Job Descriptions and Resume. Backend provides REST API and communication with ML Model to provide extracted and analyzed data.

API Overview

The route /api/v1/postResume accepts POST request with a file (pdf) attribute, it returns the following JSON on successful resume parsing.

*Example JSON Output

[
    {
        "personal_details": {
            "name": "Yash Dewangan",
            "email": "[email protected]",
            "mobile_number": "8602842290"
        },
        "skills": [
            "Pandas",
            "Coding",
            "C",
            "Flask",
            "Css",
            "Java",
            "C++",
            "Django",
            "Rest",
        ],
        "education": [
            "SMT. KASHIBAI NAVALE COLLEGE OF ENGINEERING
            BE in Information Technology
            2018-2022 | Pune, MH
            Cum. GPA: 8.14",
        ],
        "experience": [
            "eQ Technologic | Software Engineer Intern
            Aug 2021 – Present
            Implemented various services/APIs needed for new features required in latest release
            Learnt about SOA architecture, modular coding i.e. keeping future use in mind
            Implementation of concepts such as Tagging Entities and  Groups/User Authorization & Permissions for Entities
            Worked on Backend technologies such as Spring and Java with SQL Server as Database"
        ],
        "no_of_pages": 1,
        "links": {
            "linkedin": "https://www.linkedin.com/in/iyashdewangan/",
            "leetcode": "https://leetcode.com/Yashdew/",
            "codechef": "https://www.codechef.com/users/yashdew",
            "codeforces": "http://codeforces.com/profile/yashdewangan123456",
            "github": [
                "https://github.com/Yashdew/Attendance-Tracker",
                "https://github.com/Yashdew",
                "https://github.com/SkSumit/Chatistics"
            ],
            "others": [
                "mailto:[email protected]",
                "https://www.spoj.com/users/yashdew/",
                "https://attendancesknhc.herokuapp.com/",
                "https://chatistics.vercel.app/",
                "https://auth.geeksforgeeks.org/user/yashdewangan123456/practice/"
            ]
        },
        "total_experience": 0.17,
        "projects": [
            "CHATISTICS
            GitHub Live URL
            Dec 2020 - Feb 2021
            An open-source WhatsApp chats analyser and statistics.
            Application, which provides various meaningful insights.
            Time complexity reduces from 20 seconds. to 5 seconds.
            Used Flask for implementing backend REST APIs with firebase database for analysis of traffic.
            Pandas for data pre-processing.
            Used NextJS and Bulma UI for frontend.
            500+ users and 30 stars on GitHub.",

            "ATTENDANCE-TRACKER
            GitHub Live URL
            July 2020 – Aug 2020
            A full stack web application for monitoring the attendance in Microsoft Teams from logs file of the meeting. (Sample)
            Optimization of code took around 3 seconds in Data pre-processing.
            Worked on building the major backend part and frontend.
            Used Flask for implementing Backend and HTML, CSS & JS for frontend.
            Used Mongo DB and Google sheet API for Database.
            Data pre-processing of large logs files for calculating time stamps of students using pandas
            50+ users in our college."
        ],
        "achievements": [
            "Codechef - Maximum rating 1603 (3-star).",
            "Codechef – March Lunchtime 2021 Div-3, secured a rank of 825 out of 7000+ participants.",
            "Leetcode – 150+ Solved Questions.",
            "250+ Solved Questions on GFG, Codechef, SPOJ and Codeforces.",
            "Participated in Google kickstart 2021 Round A, Round C & Round D.",
            "Secured 1st rank out of 30+ participants in Scaler Edge Apex 2021. (SKN Edition)",
            "Represented Hack Club SKN projects in Hack Club Asia Summit 2021.",
            "Participated in more than 30+ coding competition."
        ],
        "hobbies": [
            "Photography and Video editing",
            "Traveling and exploring new places.",
            "Gaming"
        ]
    }
]

Built With

Frameworks used in the website

⚡️ Getting Started

Prerequisites

Tools needed to run this project

  • Python
  • Yarn
  • Node
  • Loneliness

📦 Installation

  1. Clone the repo 
    git clone https://github.com/Yashdew/Assessor.git
  2. Install packages

Backend

cd .\api\
pip install virtual env
virtualenv env
env\Scripts\activate
pip install -r requirements.txt

Frontend

cd .\frontend\
yarn install

🐎 Running

Backend would be running on PORT 5000

python run.py

Open new terminal to run front-end

Frontend would be running on PORT 3000

yarn run dev

🚧 Roadmap

See the open issues for a list of proposed features (and known issues).

🔧 Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

📄 License

Distributed under the GNU General Public License. See LICENSE for more information.

🤙 Contact

Atharva Kulkarni - @LinkedIn - [email protected]

Jayesh Padhiar - @LinkedIn - [email protected]

Sumit Kolpekwar - @LinkedIn - [email protected]

Yash Dewangan - @LinkedIn - [email protected]

Project Link: Assessor

Acknowledgements