8000 GitHub - anthonybturner/RivalsWatch: Python and Django web-based application for tracking and analyzing data from Marvel Rivals, providing users with comprehensive information on hero stats, player performance, and match outcomes. The app focuses specifically on analyzing whether the game uses engagement-based online matchmaking
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Python and Django web-based application for tracking and analyzing data from Marvel Rivals, providing users with comprehensive information on hero stats, player performance, and match outcomes. The app focuses specifically on analyzing whether the game uses engagement-based online matchmaking

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anthonybturner/RivalsWatch

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Marvel Rivals Data Tracker

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Release Build Status Python

This is a Django web-based application built with Python 3.x that helps track and analyze gameplay data for Marvel Rivals. It leverages Django ORM, Django REST Framework, and a PostgreSQL database to provide an engaging and insightful user experience for competitive players.

RivalsWatch

Key Features

  • Django ORM: Efficient database management using Django's Object-Relational Mapping system.
  • Django REST Framework: API-driven architecture for handling game data and interactions.
  • PostgreSQL: Robust, scalable database system for storing player stats, match data, and hero profiles.
  • Player Performance Tracking: Analyze player win/loss patterns, track queues for winners and losers.
  • Hero Stats & Profiles: Detailed hero stats and profiles with search functionality.
  • Match Analysis: In-depth match analysis via video replays accessible through unique game IDs.
  • Engagement-Based Matchmaking (EOMM): Insights into whether the game uses EOMM for matchmaking.
  • Upcoming Features & News: Stay updated on upcoming game features and news related to Marvel Rivals.

Technologies Used

  • Python 3.x
  • Django (Web framework)
  • Django REST Framework (API framework)
  • PostgreSQL (Database)
  • JavaScript/HTML/CSS (Frontend)

Installation

1. Clone the repository:

git clone https://github.com/anthonybturner/MarvelRivals.git 
cd marvel_rivals 

2. Create the virtual environment and activate it

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install requirements

pip install -r requirements.txt 

4. Set up PostgreSQL database (ensure PostgreSQL is installed and running):

Create a database for the project.
Update the database settings in settings.py to match your PostgreSQL configuration.
    DATABASES = {
    'default': {
        'ENGINE': 'django.db.backends.postgresql',
        'NAME': 'your_database_name',
        'USER': 'your_database_user',
        'PASSWORD': 'your_database_password',
        'HOST': 'localhost',
        'PORT': '5432',
    }
}

5. Apply migrations:

python manage.py makemigrations
python manage.py migrate

6. Start the development server:

python manage.py runserver

7. Visit localhost

http://127.0.0.1:portnumber in your browser to access the application. where port number is the port where the application is running locally By default, Django runs on port 8000, but you can change it if needed. e.g. http://127.0.0.1:8000

Usage

  • Search and view hero profiles: Gain insight into hero stats, abilities, and strategies.
  • Matchmaking Analysis: Examine patterns in match outcomes, player win/loss streaks, and analyze whether engagement-based matchmaking (EOMM) is utilized.
  • Video Replays: Watch match replays by using unique game IDs for in-depth analysis of gameplay strategies.
  • Track your progress: Log your matches and performance to see how you improve over time.

Contributing

  • Fork the repository
  • Create a new branch (git checkout -b feature-name)
  • Make your changes
  • Commit your changes (git commit -am 'Add feature')
  • Push to the branch (git push origin feature-name)
  • Create a new Pull Request

License

LICENSE

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Python and Django web-based application for tracking and analyzing data from Marvel Rivals, providing users with comprehensive information on hero stats, player performance, and match outcomes. The app focuses specifically on analyzing whether the game uses engagement-based online matchmaking

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