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The project aims to develop a prototype of a platform which can help streamline and scale up the hiring process by automating the steps of recruitment that involve accepting applications, gathering data and insights into the candidate pool, comparing candidates, ranking and shortlisting all applicants. Such a platform could prove to be useful in carrying out large scale recruitment campaigns by narrowing down the candidate pool for any specific job posting.



Project Demo Video: Introducing - Project Darwin | By Team Blueprint

Built With

Software	Version
Adobe XD	24.0.22
Zeplin	4.0.2
Python 3	3.7.1
Twitter API	7.0
IBM Watson	2.0
IBM Watson's Personality Insights	Service Update 12-12-2019
IBM DB2	11.5
IBM Cloud Object Storage	2.0

Pre-requisites

• Windows

Name	Lowest Version Tested With
Google Chrome	83.0.4103.116
Microsoft Chromium Edge	84.0.522.35

• MacOS

Name	Lowest Version Tested With
Safari	13.1.1
Google Chrome	83.0.4103

• Development Libraries

Name	Last Version Tested With
Python	3.7.1
Pandas	0.25.1
Flask	1.1.1
Flask-CORS	3.0.8
IBM-COS-SDK	2.6.3
IBM-DB	3.0.2
IBM-Watson	4.5.0
Python-Dotenv	0.13.0
Tweepy	3.8.0

Instructions

• Clone the repository.

git clone https://github.com/mihirs16/Project-Darwin

• Now install all required libraries through requirements.txt

pip install requirements.txt

• Now create a file with the name .env. Add all API Keys inside this file as text. Click here to know more about hidden API Keys as Environment Variables.

EXAMPLE_API_KEY=examplekeyvalue123

• You can find all required keys in the k3y5.py, as imported environment variables.
• Now run the Flask app app.py

python app.py

• In your browser open http://localhost:5000 (or :{port-number} as specified by the Flask's development server)

Disclaimer

Aforementioned Project Darwin is still an experimental prototype. However instances fit for specific use cases can be spawned and developed for your use. In order to contact us for such an endeavor please check out the contributors for this project.