WolfTrack5.0 is your ultimate destination for seamless organization and efficiency in your pursuit of internships and full-time job opportunities. This sophisticated online platform empowers you to streamline your application process, keeping tabs on every step of your professional journey. Say goodbye to scattered notes and endless email threads – with WolfTrack5.0, you can effortlessly manage applications, deadlines, and crucial documents, ensuring you never miss a beat in your career quest. It's your compass in the competitive job market, offering structure and precision without sacrificing style and user-friendliness. WolfTrack5.0 is your passport to success, guiding you through the winding paths of career opportunities with elegance and ease.

We offer features like giving suggestions for improvements on your resume, tracking your application, and many more.

To demonstrate our application's functionality and showcase its working examples, we have produced a YouTube video for the WolfTrack 5.0 project. In this video, we showcase that the system operates as intended. You can view the video by clicking on the following link: YouTube Link

Checkout the this documentation

This platform has been designed keeping in mind any person who is out to seek a job or internship. This may be a college student in any year, as well as a career professional wishing to switch. It may also be someone looking to enter an industry for the first time. This platform caters to a wide target audience and its simple, yet powerful features make it useful for everyone.

Python | Flask | HTML | CSS | JavaScript | BootStrap | SQLite | AWS

• We have created an entire CI pipeline which includes all the stages including Code Analysis, Style checkers, Code Coverage, Code Assemble and Docker Image Build, readily available to run the image on any server without manually setting up the environment.

• Github WorkFlow YAML | Dockerfile | Prettier Code Formatter | JS-HTML-CSS Formatter | Flake8

• SQLite 3

  SQLite is often used with Flask due to its simplicity, lightweight nature, and compatibility with Flask applications. Here's why it's commonly used:

  Easy Setup: SQLite is a self-contained, serverless, zero-configuration database engine. It doesn't require a separate server process to be running. For small to medium-sized applications, this ease of setup and use can be beneficial.

  No Configuration: As SQLite doesn't require configuration or maintenance of a separate server, it's convenient for development environments and smaller-scale applications. In Flask, SQLite can be used with minimal setup.

  Portability: SQLite databases are stored as a single file. This makes them highly portable and easy to transfer or share among different environments or applications.

  Suitability for Prototyping and Small Projects: For early stages of development, when the emphasis might be on rapidly prototyping an application or for smaller projects with relatively lower data requirements, SQLite can be a good choice due to its simplicity.

  Flask Integration: Flask has built-in support for SQLite. The sqlite3 module is included in Python's standard library, allowing Flask applications to interact with SQLite databases seamlessly.

• Microsft Power BI

• Highcharts

• Adzuna

  The API provides access to rich job market data, including job descriptions, salaries, locations, and other relevant details. This data can be integrated into applications or platforms to offer insights into the job market trends and opportunities.

• Prerequisite:

  • Download Python3.x.

• Installation:

  E.g If you downloaded Python 3.8.7 above, then

  Steps to setup virtual environment

  • 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

• Run Instructions

  To run/test the site locally:

  • Clone WolfTrack github repo.

  • Navigate to project directory.

  • Run python main.py or python3 main.py
    
    If there is a certificate error coming up for nltk stopwords download:
    

    • search for "Install Certificates.command" in finder and open it. Its a script that will install required Certificates.
      
    • Run the above command again.

  • Site will be hosted at: http://127.0.0.1:5000/

• API Setup

Create an Account:

Go to the Adzuna Developer portal developer.adzuna.com. Sign up for an account to access the API. You might need to provide some basic details about your application, such as the name, purpose, and contact information.

Get API Credentials:

Log in to your Adzuna Developer account. Find the section to create an API application. Create a new application to generate API credentials (usually API keys or tokens). These credentials are necessary to authenticate your requests to the Adzuna API.

Change URL:

Update the adzuna_url in your app.py - using the newly obtained credentials. This updated URL should reflect the API endpoint along with your authentication credentials for accessing the Adzuna API.

Class/Functions Documentation Use Cases Documentation

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

• Two Type Login Application - Admin and User
• Resume Review, Comment, Download and Like by Admin
• Comments given by Admin are sent as email to the user
• Cronjob for pending application deadlines as email notification
• Implemented web scraping to find relevant jobs according to user's profile and recommend him
• Daily Goal Check to keep track of number of jobs applied and to apply
• Customizable Daily Target Field
• Parse Resume Document with other extensions
• Recommend jobs by matching the resume with open jobs

• Created Sign-up functionality
  
• Fixed log-in authentication
  
• Fixed daily goals feature
  
• Added Site Navigation
  
• Front end aesthetic changes
  
• Added tables to Wishlist, Applied, In Process and Offers tabs
  
• Added chatGPT pipeline for resume suggestions
  

• Implemented SQLite Database connectivity for the application.
• Employed Flask API to dynamically retrieve content from the database for both Student and Admin portals.
  
• Conducted code refactoring to enhance application dynamism.
  
• Developed dynamic Sign-up and Log-In functionalities for user interaction.
  
• Integrated a dynamic Job Application table with CRUD Operations.
  
• Included a 'Filter By Status' feature for streamlined job application viewing.
  
• Incorporated a Job Search Feature for improved navigation.
  
• Added Job Skills Extractor functionality for enhanced job matching.
  
• Resolved upload and download resume bugs for smoother user experience.
  
• Implemented Test Cases from scratch due to extensive code refactoring.

• Web scraper for recommended jobs
• Configure Cron-Job for reminder as SMS notification
• Online chat with expert
• Resume template editor
• Interview Preparation resources tab
• Salary insights and comparisons

For support and inquiries related to WolfTrack 5.0, please contact us at [email protected]. We are here to assist you and address any questions or issues you may have.

We appreciate your interest and look forward to providing you with the best possible support and updates.

This project currently receives no funding.

Please refer to the CONTRIBUTING.md if you want to contrbute to the WolfTrack 5.0 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.

Shonil bhide

Sakshi Basapure

Rutuja Rashinkar

Akshada Malpure

• We would like to express our gratitude 🙏🏻 and a big thank you 😇 to Prof. Dr. Timothy Menzie for giving us the opportunity to get into the shoes of software building and learning new skills and development process throughout the project building.
• A big thank you 😊 to the Teaching Assistants for their support.
• Thank you to the previous team 😊 for a thorough ReadMe and detailed documentation.