Version1:
Version2:
Are you applying to too many companies and cannot keep track of your schedule?
Want to get what your colleages or experts have to say?
WolfTrack 2.0 helps to plan and organize job application in a chronological order so that you can easily track job applications, get expert suggestions, and successfully get your desired company. We store job applications, job profile, location, salaries, dates, notes and more!
So, let's go get that job! 😎
Final.mp4
Python
Flask
HTML
CSS
JavaScript
MySQL
- AWS Relational Database Service-RDS
- The AWS Database is used as a primary DB by the location. The application interacts with the DB and no additional steps are required from the users. For any contributors or future developers, please mail to wolftrackse@gmail.com to get your AWS IAM user account details to connect to AWS RDS.
- Microsft Power BI
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- Download Python3.x.
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E.g If you downloaded
Python 3.8.7above, thenSteps to setup virtual environment
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Create a virtual environment:
python3.8 -m venv test_env -
Activate the virtual environment:
source test_env/bin/activate -
Build the virtual environment:(must be present in project root directory)
pip install -r requirements.txt
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To run/test the site locally:
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Clone WolfTrack github repo.
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Navigate to project directory.
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Run
python main.pyorpython3 main.py -
Site will be hosted at:
http://127.0.0.1:5000/
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- You can access the application on the url
https://harshb.pythonanywhere.com/login
- You can access the application on the url
Our application is docker-compatible configured and you have to follow below steps to run the docker on local:
Note : Make sure you have a docker desktop or docker client installed on your system
- Clone the repository
git clone https://github.com/aditya4196/WolfTrack2.0.git
- Go the the repository
cd WolfTrack2.0
- Run the docker build command
docker build --tag wolftrackv2:1.0 .
- Run the built docker image on local Container
docker run -dp 5000:5000 wolftrackv2:1.0
- Test the backend application using below api
GET localhost:5000/login
Response :- "Login Page will appear"
- Tag the Deployable image
docker tag wolftrackv2:1.4 adi4196/wolftrackv2:1.0
- Push the Deployable tagged image to the DockerHub Cloud Image Repository
docker push adi4196/wolftrackv2:1.0
- Below DockerHub Repository where the readily deployable Image is available
[Class Function
It is part of the Github Workflow Build
- Create database ER diagram
- Create SQL DML and DDL queries
- Create Dashboard Page
- Create Login Page
- Create Signup Page
- Setup Flask
- Add Unit testing
- Add Error Handling mechanisms
- Mock of Job Application Map using Power BI
- Resume Parser and Analyzer
- Email Notifcation after adding new job profile to list
- Upload and maintaining resume versions
- Send remainder mails for deadlines
- Share your profile with others
- Creation of Docker image
- Readily deployable image in docker registry
- Implement ML to create Resume Scanner Model for Better Accuracy
- Reading mail from the Expert for the comments on the shared profile
- Configure Cron-Job for reminder as SMS notification
- Implement WebScraping for Job Description to Automate Resume Scanner Functionality
- Display the location on the map for the job selected
- Parse Resume Document with other extensions
Please refer to the Contributing.md if you want to contrbute to the Wolftrack 2.0 source code. Follow all the guidelines mentioned and raise a pull request for the developers to review before the code goes to the main source code.
- Aditya Ravikant Jadhav (ajadhav3@ncsu.edu)
- Harsh Vijay Bathija (hbathij@ncsu.edu)
- Ashritha Bommagani (abommag@ncsu.edu)
- Abhishek Arvindkumar Upadhyay (aaupadhy@ncsu.edu)
- Akash Mukesh Sanghani (amsangha@ncsu.edu)
In case of any issues, please mail your queries to wolftrackproject@gmail.com