NBA Sports Analytics Dashboard

This project is a sports analytics dashboard for NBA data. It provides detailed player and team statistics, along with interactive filtering and visualization capabilities.

Features

• Ingest player and team data from the NBA API.
• Store data in a PostgreSQL database with schemas for development, staging, and production environments.
• Interactive web-based dashboard built with Flask and Tailwind CSS.
• Filterable and sortable statistics for players and teams.

Requirements

• Python 3.9+
• PostgreSQL
• Node.js and npm (for Tailwind CSS)
• nba_api

---

Installation

1. Clone the repository

git clone https://github.com/JoThurst/nba-sports-analytics.git
cd nba-sports-analytics

2. Set up a virtual environment

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

3. Install Python dependencies

pip install -r requirements.txt

4. Install Node.js and Tailwind CSS dependencies

Ensure you have Node.js installed. Then install the necessary Tailwind CSS dependencies:

npm install

This installs tailwindcss, postcss, and autoprefixer.

---

Tailwind CSS Setup and Development

Tailwind CSS is used for styling the application. Here's how to set up and use it during development:

1. Initialize Tailwind CSS

Tailwind is already set up in this project, but if you need to reinitialize it, run:

npx tailwindcss init

2. Build Tailwind CSS

To generate the compiled output.css file from the tailwind.css source, run:

npm run build:css

The compiled CSS file will be saved in app/static/css/output.css.

3. Watch for Changes

During development, you can watch for changes to your Tailwind CSS and Flask template files to rebuild the CSS automatically:

npm run watch:css

4. Customize Tailwind CSS

To customize the Tailwind configuration, edit the tailwind.config.js file in the root of the project. For example, you can extend the theme or add custom plugins:

module.exports = {
  content: [
    './app/templates/**/*.html',
    './app/static/**/*.js',
  ],
  theme: {
    extend: {
      colors: {
        customGray: '#2A2A2A',
      },
    },
  },
  plugins: [],
};

---

Database Setup

1. Set up PostgreSQL

• Create a database named nba_stats.
• Create schemas for develop, staging, and production.
• Grant appropriate privileges to your users.

2. Configure the database

Local Configuration (db_config.py)

import psycopg2
from psycopg2 import sql

def get_connection(schema="develop"):
    """Establish and return a database connection."""
    conn = psycopg2.connect(
        database="postgres",
        host="localhost",
        user="postgres",
        password="password",
        port="5432"
    )
    cur = conn.cursor()
    cur.execute(sql.SQL("SET search_path TO {};").format(sql.Identifier(schema)))
    conn.commit()
    return conn

def release_connection(conn):
    """Release the connection back to the pool."""
    if connection_pool and conn:
        connection_pool.putconn(conn)

def close_pool():
    """Close all connections when shutting down the app."""
    if connection_pool:
        connection_pool.closeall()

Cloud Configuration (db_config.py)

import psycopg2
from psycopg2 import sql, pool

DATABASE_URL = "<YOUR-CONNECTION-STRING>"

# Initialize the connection pool globally
connection_pool = pool.SimpleConnectionPool(
    1, 10, DATABASE_URL
)

if connection_pool:
    print("Connection pool created successfully")

def get_connection(schema="public"):
    """Get a database connection from the pool and set schema."""
    if not connection_pool:
        raise Exception("Connection pool is not initialized")

    conn = connection_pool.getconn()
    cur = conn.cursor()
    cur.execute(sql.SQL("SET search_path TO {};").format(sql.Identifier(schema)))
    conn.commit()
    return conn

def release_connection(conn):
    """Release the connection back to the pool."""
    if connection_pool and conn:
        connection_pool.putconn(conn)

def close_pool():
    """Close all connections when shutting down the app."""
    if connection_pool:
        connection_pool.closeall()

---

Running the Application

1. Run the ingestion scripts

Fetch and store players:

python ingest_data.py

2. Run the Flask app

python run.py

---

Contribution

Fork the repository

Create a new branch for your feature or bugfix:

git checkout -b feature-name

Commit your changes and push to your fork:

git add .
git commit -m "Description of changes"
git push origin feature-name

Submit a pull request describing your changes.

---

License

This project is licensed under the MIT License. See the LICENSE file for details.