📺 Sayonara !!! - This is Imagine

🎬 YouTube Backend Clone Project

By Divayang Siddhapura

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This project is a backend clone of YouTube, built to understand and implement complex server-side logic including user authentication, video management, subscriptions, cloud storage, and more.

Inspired by the teachings of Hitesh Choudhary sir (Chai aur Code), this project helped me grasp how backend systems interact with databases and users asynchronously.

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🚀 Project Description

This backend is designed for a YouTube-like video streaming platform, implementing the following features:

🧩 Mongoose Models:

• User Model: Handles user registration, login, avatar/cover image, password management, subscriptions.
• Video Model: Stores video metadata like title, description, thumbnail, upload date, etc.
• Subscription Model: Handles relationships between users for subscriptions and counts.

<--Link to The Model: Model-->

All schemas are structured using Mongoose and connected to MongoDB Atlas using a secret .env connection key.

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🛣️ Routes & Controllers

This project uses Express.js to define custom routes for various operations. Some important routes and controllers include:

• registerUser, loginUser, logoutUser, refreshAccessToken
• changeCurrentPassword, getCurrentUser, updateAccountDetails
• updateUserAvatar, updateUserCoverImage, getUserChannelProfile
• getWatchHistory, subscribeToUser, getSubscribersCount

Each route uses robust controller logic to process input, interact with MongoDB, and return appropriate responses.

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🛡️ Authentication & Middleware

🔐 JWT Tokens:

• Access Token: For validating authenticated sessions.
• Refresh Token: For issuing new access tokens without requiring login again.

🔐 Used Bcrypt:

• For password Encryption and Decryption

⚙️ Middlewares Used:

• Multer: For handling user image uploads (stored locally).
• Cloudinary: For uploading avatars and cover images to cloud storage.
• JWT Middleware: To protect private routes.
• Custom Error Middleware: To handle API errors globally.

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📊 MongoDB Aggregation Pipelines

This was one of the most challenging parts. I built custom aggregation pipelines in MongoDB to calculate:

• Subscriber counts
• Watch history
• Subscribed-to lists
• Channel statistics

Using mongoose-aggregate-paginate-v2 helped manage paginated responses effectively.

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🛠️ Tech Stack

• Node.js + Express.js – Server and Routing
• MongoDB Atlas – Cloud-hosted NoSQL database
• Mongoose – ODM for MongoDB
• Cloudinary – Cloud-based image storage
• JWT – Token-based authentication
• Multer – File uploads
• dotenv – Secure environment variable handling

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📦 What I Learned

• Full-stack backend architecture
• Designing secure and scalable APIs
• Implementing middleware layers for security and file handling
• How requests are made using Postman for testing of the routes and controllers
• Structuring large backend projects like real-world systems

🙏 Special Thanks

A big thank you to Hitesh Choudhary sir and his channel Chai aur Code for teaching backend development from scratch in such a beginner-friendly and empowering way.

💡 Final Note

This is just the beginning of a bigger journey toward building full-stack, scalable, and professional-grade applications. ImagineX is the start of it. Sayonara till the next one! 🚀