Wardrobe Web is a web-based clothing management application that helps users organize their daily wardrobe, automate outfit selection, and schedule laundry routines. Users can input detailed data for each clothing item such as name, type, brand, material, size, and price and track when each piece is worn. The system also allows users to set reminders, enabling automatic notifications when an outfit is scheduled to be used the next day. The platform integrates with Wardrobe Mobile, Wardrobe Telegram Bot, Wardrobe Line Bot, and Wardrobe Desktop, offering a cross-platform experience through a single account. Users can manage and view their wardrobe, schedules, and laundry history across devices. Data export features in PDF and Excel formats are also available for greater flexibility in wardrobe management. While the application is accessible on both desktop and mobile browsers, administrative access is reserved for the Wardrobe Desktop Admin on desktop devices.
This repository is the backend codebase for the next backend version of the Wardrobe app, built using Golang with the Gin framework. The primary backend of the application is still powered by Laravel and can be accessed at: https://github.com/FlazeFy/wardrobe-BE
If you want to see the project detail documentation, you can read my software documentation document.
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Diagrams https://drive.google.com/drive/folders/16Mo0zd2CKzJRJuLGYjbHlbgfUJ7z13mK?usp=drive_link
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Software Requirement Specification https://docs.google.com/document/d/1GPFVqSjwaWZ_O7wjb8oS_voJBDJkwS95eEyniI2ydrc/edit?usp=drive_link
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User Manual https://docs.google.com/presentation/d/1qiH8gPTqc3haEH5Y6UGtngXQtlJ39kroGciOyHh7XiI/edit?usp=drive_link
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Test Cases https://docs.google.com/spreadsheets/d/1LoqYYub1JHJyIHsbL89LDQijj_-Hv74QZUgRrwtXMhI/edit?usp=sharing
Backend (Swagger Docs) : ...
[URL]
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Clothing & Outfit Data Management Users can manage their clothing data within the Wardrobe application. The data recorded may include clothing name, type, brand, price, material, and size.
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Scheduling & History From the saved clothing data, users can log each time a clothing item or outfit is used, and set reminder schedules. The system will then notify users whenever an outfit is scheduled to be used the next day.
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Laundry Management Users can also track the laundry process of clothes after being worn, up to the status where the clothing is ready to be used again.
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Automatic Outfit Suggestion Based on the clothing data, the system can generate various outfit combinations and recommend an outfit for the next day. This is determined by usage history, availability status, weather conditions, and user preferences.
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Data Export The application provides convenience for users who want to view complete datasets of clothing, usage history, or laundry history. Export to PDF and Excel formats is available to support more customized wardrobe management.
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Everyday People Individuals who want to efficiently manage their daily clothing collections, track outfit usage, schedule laundry, and receive outfit suggestions.
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Laundry Service Customers Users who frequently use laundry services and need to monitor the washing and return status of their clothes.
- People often forget what clothes they own, where they are, or when they last wore or washed them leading to inefficient usage and cluttered wardrobes.
- Planning daily outfits manually is time-consuming and can lead to repeated usage, poor combinations, or unprepared clothing.
- Users forget to wash or retrieve laundry in time, leaving them without clean clothes when needed.
- Manually recording outfit usage, laundry status, or purchase details becomes overwhelming.
- Exporting wardrobe data for budgeting, or personal reference is difficult without a structured digital system.
- Offer a feature for users to digitally log and manage clothing items with details like name, size, brand, material, price, and category—making wardrobes trackable and searchable.
- Automatically generate outfit suggestions based on clean clothes, usage history, and weather to simplify daily planning.
- Let users schedule outfit usage and receive laundry reminders to ensure clothes are clean and ready in time.
- Sync data across devices (Web, Mobile, Telegram, and Line Bot) so users can update or access wardrobe records anytime, anywhere.
- Provide data export tools to download usage history, laundry logs, and clothing details in Excel or PDF format for easy reference or sharing.
- ✍️ Clothing & Outfit Data Management
- ⏰ Scheduling & History
- 👕 Laundry Management
- 👗 Automatic Outfit Suggestion
- 🤖 Telegram and Line Bot Chat Integration
- 📄 Data Export
- Golang Gin
- Golang - Telegram Bot
- Golang - Line Bot
- MySQL
- Firebase Storage (Cloud Storage for Asset File)
- Redis (In-Memory Storage for Sign Out Schema)
- Cpanel (Deployment)
- Github (Code Repository)
- Firebase (External Services)
- Postman
- Swagger Docs
| Directory/File | Purpose |
|---|---|
config/ |
Application configuration files (e.g., environment, database, externa services, auth, and in-memory storage) and const variabels |
controllers/ |
Handles incoming HTTP requests and sends responses |
docs/ |
Swagger API documentation setup |
models/ |
Core data structures and model definitions |
factories/ |
Generates dummy/test data for development or testing |
middlewares/ |
Custom Gin middleware (e.g., authentication, logging, role access management) |
reports/ |
PDF generation and reporting logic |
repositories/ |
Data access logic (repository pattern for DB abstraction) |
routes/ |
Defines dependency, API routes and maps them to controllers, also scheduler and seeder init |
schedulers/ |
Background jobs or scheduled tasks (e.g., cron-like functions) |
seeders/ |
Database seeding logic for initial or test data |
services/ |
Business logic layer reused across controllers |
tests/ |
End-to-End, Unit and integration tests |
utils/ |
Utility and helper functions |
.env |
Environment variable configuration |
.gitignore |
Specifies intentionally untracked files to ignore by Git |
go.mod |
Go module definition (dependencies and module path) |
go.sum |
Checksums for module dependencies |
main.go |
Entry point of the application |
README.md |
Project simple documentation |
To set up the environment variables, just create the .env file in the root level directory.
| Variable Name | Description |
|---|---|
DB_HOST |
Database host (e.g., localhost) |
DB_PORT |
Database port (e.g. 3306) |
DB_USER |
Database username |
DB_PASSWORD |
Database password |
DB_NAME |
Name of the primary database |
TEST_DB_HOST |
Host for the test database |
TEST_DB_PORT |
Port for the test database |
TEST_DB_USER |
Username for the test database |
TEST_DB_PASSWORD |
Password for the test database |
TEST_DB_NAME |
Name of the test database |
JWT_SECRET_KEY |
Secret key used for JWT authentication |
JWT_EXPIRES_IN |
JWT token expiration duration (e.g., 1h, 24h) |
FIREBASE_BUCKET_NAME |
Firebase Storage bucket name for handling file uploads |
GOOGLE_APPLICATION_CREDENTIALS |
Path to Firebase service account JSON file |
TELEGRAM_BOT_TOKEN |
Telegram bot token for chat integration |
LINE_BOT_TOKEN |
Line bot token for chat integration |
PORT |
Port on which the application will run (e.g., 9000) |
- Daily Limitation for data transaction in Firebase Storage
- Not all utils (helpers) can be tested in automation testing
- Feature that return the output in Telegram / Line Chat or Exported File must be tested manually
- Git installed
- A GitHub account
- Basic knowledge of Golang, Software Testing, Firebase Service, and SQL Databases
- Code Editor
- Telegram Account
- Line Account
- Postman
- Go version 1.21 or higher
- Git for cloning the repository.
- MySQL database.
- Make (optional), if your project includes a Makefile to simplify common commands.
- Swagger CLI to generate Swagger API docs.
- Firebase service account JSON file or Google App Credential.
- Telegram Bot token, you can get it from Bot Father
@BotFather - Telegram User ID for testing the scheduler chat in your Telegram Account. You can get it from IDBot
@username_to_id_bot - Line Bot token, you can get it from Line Developer Console
- Line User ID for testing the scheduler chat in your Line Account. You can get it from webhook events
- Internet access from the hosting server (for Telegram webhook polling or long-polling)
Local Init & Run
- Download this Codebase as ZIP or Clone to your Git
- Set Up Environment Variables
.envat the root level directory. You can see all the variable name to prepare at the Project Structure before or.env.example - Install Dependencies using
go mod tidy - DB Migration will be running everytime your start the app. If you want to disabled it, just commented the code
MigrateAll(db)that labelled withConnect DB, you can find the file atmain.go. - Seeder also will be running everytime your start the app. If you want to disabled it, just commented the code that labelled with
Seeder & Factories, you can find the file atroutes/dependency.go. - Same like Task Scheduler. If you want to disabled it, just commented the code that labelled with
Task Scheduler, you can find the file atroutes/dependency.go. - Run the Go Gin using
go run main.go
CPanel Deployment
- Source code uploaded to CPanel
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| Role | Name | GitHub | Responsibility |
|---|---|---|---|
| Backend Developer | Leonardho R. Sitanggang | @FlazeFy | Manage Backend and Telegram Bot Codebase |
| Frontend Developer | Leonardho R. Sitanggang | @FlazeFy | Manage Frontend Codebase |
| Mobile Developer | Leonardho R. Sitanggang | @FlazeFy | Manage Mobile Codebase |
| System Analyst | Leonardho R. Sitanggang | @FlazeFy | Manage Diagram & Software Docs |
| Quality Assurance | Leonardho R. Sitanggang | @FlazeFy | Manage Testing & Documented The API |
- Ensure API endpoints requiring authentication are protected with proper middleware.
- Do not expose sensitive environment variables (e.g., API keys, database credentials) in public repositories.
- Avoid using seeded dummy data in production environments.
- Avoid using seeded dummy data with large seed at the same time.
- Telegram & Line bot polling may cause delays or downtime if the server experiences high load
- Limitation when using Firebase Storage for free plan Firebase Service, upgrade to Blaze Plan to use more.
- ✅ Smart Wardrobe Management: Easily organize and track clothing items with full details including size, material, category, price, and brand.
- 🤖 Bot Interaction: Integrated with Telegram and Line Bot to send real-time reminders for outfit schedules and laundry tasks.
- 🧪 Test-Driven Development: Built with a focus on E2E, integration, and unit tests for stable and reliable API behavior.
- 📄 Exportable Reports: Generate and download clothing usage and laundry history in PDF or Excel formats.
- 💡 Real-Life Use Case: Solves a modern lifestyle issue of managing outfits efficiently with automation and reminders.
- ⭐️ Clean & Modular Codebase: Designed using Go (Gin) with separation of concerns, making the backend easy to scale and maintain.
Made with ❤️ by Leonardho R. Sitanggang