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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.