Retail Pulse Backend

Description

This project is a backend service for processing store visit images. The service handles job submission, downloads images, calculates their perimeter, and stores the results in a MongoDB database. The job's status can be queried via API endpoints.

Assumptions

• The store_master.csv file contains StoreID, StoreName, and AreaCode.
• Images are publicly accessible via the provided URLs.
• The system handles multiple concurrent jobs efficiently.

Installation & Setup

Prerequisites

• Node.js
• MongoDB

Steps

1. Clone the repository:

   git clone https://github.com/your-repo/retail-pulse-backend.git
   cd retail-pulse-backend

2. Install dependencies:

   npm install

3. Set up environment variables by creating a .env file:

   PORT=5000
   MONGO_URI=mongodb://localhost:27017/retail_pulse
   

4. Start the server in development mode:

   npm run dev

Testing Instructions

• Use Postman or cURL to test the API endpoints:
  • Submit a Job:

    POST http://localhost:5000/api/submit/

  • Get Job Status:

    GET http://localhost:5000/api/status?jobid=123

Work Environment

• IDE: VS Code
• Libraries used: Node.js, Express.js, Mongoose, Multer, csv-parser

Future Improvements

• we can add authentication and authorization.
• we can Optimize image processing using worker threads.
• we can deploy the service using Docker and Kubernetes.

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