10-Minute Grocery Delivery App

Overview

This project is an attempt to understand and replicate the logistics behind ultra-fast grocery delivery services like Blinkit, Zepto, and Swiggy Instamart. The goal was to explore the challenges of real-time delivery agent assignment and create a functional prototype.

Problem Statement

The app functions as a single-vendor eCommerce platform with the unique challenge of assigning nearby delivery agents efficiently to fulfill orders within 10 minutes. Other features remain similar to traditional eCommerce websites.

Tech Stack

Backend

• Framework: Django

• Database: PostgreSQL (structured data storage)

• In-Memory Database: Redis (caching and quick data retrieval)

Frontend

• Framework: React Native (leveraging past experience with Class To Cloud)

Running the Project

Backend

To start the backend, run the following command:

bashCopy

docker-compose up -d

Frontend

To set up and start the frontend, run:

bashCopy
[object Object] apps/mobile

yarn install  [object Object]

yarn start  [object Object]

Data Scraping for Inventory Management

To populate real-world product data efficiently, I used HAR file-based data scraping, a technique I recently explored. More details can be found here.

Design Inspiration

• Figma Templates

• UI Inspiration from existing apps like Blinkit & Zepto

Key Features

• Home Screen

• Live Location Tracking

• Product & Category Listings

• Real-Time Order Assignment

• Live Location Tracking Implementation

Since I had no prior experience with mobile GPS tracking, I researched solutions and found Kafka to be widely recommended. However, to avoid additional complexity in a monolithic architecture, I implemented Redis-based caching for location updates. More details on this can be found here.

While this isn't the most scalable approach, it works fine for a side project with a limited user base. Future improvements will be considered based on performance insights.

Lessons Learned

• Tech Stack Decisions: Balancing complexity and performance is crucial. Instead of blindly following trends, choose a stack that best fits your use case and is maintainable.

• Real-Time Updates: Ensuring synchronization across multiple systems is a challenge. Enhancing security and reliability for these updates is still a work in progress.

• Modular Architecture: Keeping the app modular allows for easier scalability. Future scaling should only require deploying additional EC2 instances.

Future Considerations

• Admin Dashboard (Mobile App) for tracking orders and analytics.

• White-labeling: Making the app configurable for different vendors with minimal setup.

• Improved Analytics: Enhancing data insights for better operational decisions.

Conclusion

Building a 10-minute grocery delivery app is a challenging but rewarding experience. By tackling logistical and technical hurdles head-on, this project lays a solid foundation for future enhancements. If the app is productized, additional features will be implemented to improve scalability and efficiency.