Rating And Projections Application

Table of Contents

• Overview
• Backend
• Frontend
• Installation
• Usage
• Creating JSON and CSV Files

Overview

This project aims to provide player and team grades and future projections from data retrieved from APIs like nba_api and web scraping tools.

Frontend

The frontend is built using Next.js, a React-based framework for building modern web applications.

Backend

The backend uses FastAPI and contains the API endpoints and service files. It handles:

• Fetching data from external APIs
• Processing and storing data in the PostgreSQL database
• Generating player and team grades
• Exposing endpoints for the frontend

Database

The Application uses PostgreSQL as the database. It stores detailed information about players, teams, and game logs. The schema currently includes tables for:

• Players
• Teams
• Game Logs

Installation

Currently working on improving this.

Prerequisites

• Node.js (v14 or later)
• Python (v.3.8 or later)
• npm (v6 or later)
• pip (v20 or later)
• Docker
• Docker Compose

The Application uses Docker to run the Application.

Steps

1. Clone the repository:

git clone https://github.com/jdkingsbury/Sports_Prediction.git
cd Sports_Prediction

2. Set environment variables in both the frontend, backend, and root directories.

   • backend: Provide the DB URLs for the variables DATABASE_URL and ASYNC_DATABASE_URL.

   • frontend: Provide the URL to the backend of the Application.

   • root: Provide the database information.

     Example of .env file in the backend directory:

     DATABASE_URL=postgresql://<username>:<password>@<host>:<port>/<dbname>
     ASYNC_DATABASE_URL=postgresql+asyncpg://<username>:<password>@<host>:<port>/<dbname>

3. Install using Docker Compose

docker-compose up --build

4. Run Python setup script

docker-compose run backend python app/scripts/populate_db.py

If you experience an error with shadcn when viewing a page, install shadcn.

Usage

Docker will build and start up the frontend, backend, and the database for the Application. Access the frontend at [http://localhost:3000] and the backend API at [http://localhost:8000].

Creating JSON and CSV Files

You can create JSON and CSV files for the NBA functions in nba.py which is located in the routers directory.

Ensure the backend server and the PostgreSQL container are running to create files from the API routes in the application.

Example and Layout:

CLI command:

docker-compose exec backend python app/utils/create_file.py {api_url} {file_type} {file_name}

• api_url: The api endpoint from which to fetch players.
• file_type: The file type to create (json or csv).
• file_name: The desired name for the output file.

Example:

docker-compose exec backend python app/utils/create_file.py http://localhost:8000/nba/players json player_data

This command will create a player_data.json file containing player information.

• Note: JSON and CSV files are the only file types supported.