Network by Abrar Yaser

This project is a scalable web application for managing and displaying events happening near you globally. It is built with a React frontend and a Python backend, and uses PostgreSQL for data storage. Docker is used to containerize the application for easy deployment and scalability.

Project Structure

• services/backend: Contains the backend API built with Python.
• services/client/my-app: Contains the React frontend application.
• postgres: Contains the Dockerfile and SQL schema for the PostgreSQL database.

Getting Started

Prerequisites

• Docker
• Docker Compose

Running the Application

1. Clone the repository:

   git clone [<repository-url>](https://github.com/abraryaser02/Network.git)
   cd Network

2. Build and run the containers:

   docker-compose -f docker-compose-dev.yml up --build

3. Access the application:

   • The frontend will be available at http://localhost:3000
   • The backend API will be available at http://localhost:5001

Stopping the Application

To stop the running containers, use:

docker-compose -f docker-compose-dev.yml down

Database Indexing and Scalability

Indexes

Efficient indexing is crucial for optimizing query performance, especially when dealing with large datasets. This project leverages PostgreSQL's powerful indexing capabilities:

• B-tree Indexes: Used on primary keys, foreign keys, and other frequently queried columns. B-tree indexes are optimal for equality and range queries.
• Full-text Search Indexes: Implemented using PostgreSQL's GIN (Generalized Inverted Index) or RUM (Rum Universal Index) indexes to enable fast full-text searches on event descriptions and titles. This allows for efficient searching through large text fields.
• Composite Indexes: Created on multiple columns to support complex queries, ensuring that the database can quickly locate rows that match multiple criteria.
• Partial Indexes: Applied to subsets of data to optimize queries that frequently access a particular subset of rows.

SQL Optimization and Scalability

The backend of this project utilizes SQLAlchemy Core for interacting with the PostgreSQL database. SQLAlchemy Core provides a high level of flexibility and performance by allowing the construction of complex SQL queries programmatically.