📚 Python FastAPI & React E-Learning LMS & CBT Platform

🇮🇩 Baca dalam Bahasa Indonesia

☕ Looking for the Java Spring Boot & React edition? Visit: https://github.com/mfarim/spring-elearning-react

🐘 Looking for the Laravel & Livewire edition? Visit: https://github.com/mfarim/laravel-elearning

A high-performance enterprise web-based E-Learning and Computer Based Test (CBT) platform for managing modern academic learning activities between Admin, Teacher, and Student. Built with a decoupled cloud-ready architecture: Python 3.12, FastAPI, SQLAlchemy 2.0 (Asyncpg), Pydantic v2, React 19, and Tailwind CSS v4, featuring stateless JWT authentication with impersonation, Redis Pub/Sub, native WebSocket real-time candidate proctoring, and openpyxl Excel batch processing.

✨ Key Features

👨‍💼 Admin Panel

Feature	Description
Dashboard	Real-time statistics overview: teachers, students, classrooms, subjects, CBT metrics
Teachers	Full CRUD with automatic user account provisioning & NIP validation
Students	CRUD + classroom filtering + 📥 Excel Batch Import (`.xlsx`) + Exam Cards Print
Classrooms	CRUD + homeroom teacher assignment + capacity & academic year management
Subjects	CRUD + subject code + credit units + assigned teacher mapping
Announcements	CRUD + multi-target broadcasting (All / Teacher / Student) + publish toggle
Impersonation	Instant one-click login as teacher or student for administrative debugging
Security	OAuth2 Bearer JWT tokens, BCrypt hashing, and dependency-injected role checking

👨‍🏫 Teacher Panel

Feature	Description
Dashboard	Teaching metrics, scheduled examinations, active assignments, and recent activity
Learning Materials	CRUD + multi-type content (Document, Video, Text, Link, Audio) + student view tracking
Assignments	CRUD + deadline dates + instructions + submission grading with feedback
CBT Examinations	CRUD + duration timer + passing grade (KKM) + randomize questions/options + retry toggles
Question Builder	Multiple Choice (A-E), True/False, Essay + points allocation + 📥 Excel Import
Live Telemetry Monitor	Real-time WebSocket candidate status, question progress bar, and anti-cheat flag alerts
Exam Hall Tickets	Print ready-to-use official CBT student candidate cards with NIS barcodes

👨‍🎓 Student Panel — Mobile-First Design

Feature	Description
Home Dashboard	Responsive mobile drawer, upcoming exams countdown, active assignments, announcements
Learning Modules	Browse, read, and download structured course materials per enrolled subject
Assignment Hub	View assignment instructions + file upload dropzone + feedback review
CBT Exam Room	Fullscreen examination runner with countdown timer, anti-cheat detection, and auto-submit
Grades & GPA Summary	Subject average breakdown, progress bars, and passing grade pass/fail status

🖥️ CBT Exam System Workflow

Exam List → Confirmation & Instructions → Secure Exam Runner
                                           ├── ⏱️ Synchronized Timer (auto-submit on expiry)
                                           ├── 🔒 Anti-Cheat Proctoring (fullscreen & tab change alerts)
                                           ├── 📍 Color-Coded Question Palette (answered / remaining)
                                           ├── 💾 Instant Auto-Save (on every option selection)
                                           └── 📊 Real-Time Proctoring Telemetry (/ws/exams/{id}/monitor)

📸 Screenshots Showcase

🔐 Authentication & Role Impersonation

👨‍💼 Administrator Module

Admin Dashboard	Classroom Management

Subject Management	Teacher Management

Student Management & Excel Import	School Announcements

👨‍🏫 Teacher Module

Teacher Dashboard	Learning Material Catalog

Assignment & Homework Hub	CBT Examination Management

Interactive Question Bank Editor

👨‍🎓 Student Module (Desktop & Mobile Optimized)

Student Home Dashboard	Student Learning Modules

Student Assignments & Submissions	CBT Active Examinations

Academic Gradebook & Performance

🛠️ Tech Stack & Architecture

┌────────────────────────────────────────────────────────┐
│                   React 19 SPA Client                  │
│       Vite • TypeScript • Tailwind CSS v4 • Zustand    │
└───────────────────────────┬────────────────────────────┘
                            │ REST APIs & WebSockets
┌───────────────────────────▼────────────────────────────┐
│                  FastAPI Backend Server                │
│       Python 3.12 • Pydantic v2 • SQLAlchemy 2.0 Async │
└──────┬────────────────────┬────────────────────┬───────┘
       │                    │                    │
┌──────▼──────┐      ┌──────▼──────┐      ┌──────▼──────┐
│  PostgreSQL │      │    Redis    │      │ Local/MinIO │
│  (Database) │      │  (Pub/Sub)  │      │  (Storage)  │
└─────────────┘      └─────────────┘      └─────────────┘

Backend: Python 3.12, FastAPI, Uvicorn, SQLAlchemy 2.0 Async Engine, asyncpg, Alembic, Pydantic v2, Python-JOSE (JWT), Passlib (BCrypt), openpyxl.
Frontend: React 19, TypeScript, Vite, Tailwind CSS v4, Zustand, Axios, Lucide React.
Infrastructure: Docker, Docker Compose, PostgreSQL 16, Redis 7, MinIO.

🚀 Getting Started & Local Development

You can run this project locally in two ways:

Full Docker Compose (Recommended) — All services (Database, Redis, MinIO, Backend, Frontend) run containerized with zero manual configuration.
Hybrid Setup (Best for Active Development) — Run infrastructure (Postgres, Redis, MinIO) in Docker, while running Backend & Frontend on your host machine for instant live-reload.
Full Manual Local Setup — Run everything natively on your machine.

🐳 Method 1: Running with Docker Compose (Recommended)

Docker Compose provides a complete, turnkey environment with isolated network ports that avoid conflicts with existing services.

1. Clone & Configure Environment

git clone https://github.com/mfarim/python-fastapi-react-elearning.git
cd python-fastapi-react-elearning

# (Optional) Copy environment template if you wish to customize ports or credentials
cp .env.example .env

2. Build & Launch Containers

docker compose up -d --build

Note: The backend container automatically checks the database connection, provisions all database tables, and executes the demo database seeder on initial startup.

3. Access URLs & Services

Service	URL / Port	Credentials / Notes
Frontend Web App	http://localhost:3001	Nginx reverse proxy routing `/api` & `/ws` to backend
FastAPI Swagger Docs	http://localhost:8000/docs	Interactive OpenAPI 3.1 documentation
FastAPI ReDoc	http://localhost:8000/redoc	Alternative clean API specification
Backend Health Check	http://localhost:8000/health	API health status endpoint
PostgreSQL Database	`localhost:5434`	DB: `elearning` \| User: `postgres` \| Pass: `postgres`
Redis Cache / PubSub	`localhost:6380`	High-speed cache & CBT WebSocket channel

4. Useful Docker Commands

Check container status:
```
docker compose ps
```

View live streaming logs:

# View all container logs
docker compose logs -f

# Or view specific service logs
docker compose logs -f backend
docker compose logs -f frontend

Re-run or reset database seeding manually:

docker compose exec backend python -m app.scripts.seed_demo_data

Access backend bash shell inside container:
```
docker compose exec backend bash
```
Stop all services:
```
docker compose down
```
Stop and wipe all data volumes (Fresh Reset):
```
docker compose down -v
```

⚡ Method 2: Hybrid Setup (Docker Infra + Local Hot Reload)

This method is recommended for active feature development because it preserves fast hot-reloading for both FastAPI and React/Vite without rebuilding images.

1. Start Infrastructure Only

docker compose up -d postgres redis

2. Run Backend (FastAPI) Locally

cd backend

# Create & activate virtual environment
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install Python dependencies
pip install -r requirements.txt

# Run initial database seeder (creates tables + seeds demo data)
python -m app.scripts.seed_demo_data

# Start FastAPI development server with auto-reload
uvicorn app.main:app --reload --port 8000

3. Run Frontend (React 19 + Vite) Locally

In a separate terminal window:

cd frontend

# Install node packages
npm install

# Start Vite development server
npm run dev

Open http://localhost:3000 in your browser. (Vite automatically proxies /api and /ws to http://localhost:8000).

💻 Method 3: Full Manual Local Setup (Without Docker)

Prerequisites

Python 3.12+
Node.js 20+ & npm
PostgreSQL 16+ running locally
Redis 7+ running locally

1. Backend Setup

Create a PostgreSQL database named elearning.

Configure .env inside backend/ or root:

DATABASE_URL=postgresql+asyncpg://postgres:postgres@localhost:5432/elearning
DATABASE_URL_SYNC=postgresql+psycopg2://postgres:postgres@localhost:5432/elearning
REDIS_URL=redis://localhost:6379/0

Install dependencies and start server:

cd backend
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python -m app.scripts.seed_demo_data
uvicorn app.main:app --reload --port 8000

2. Frontend Setup

cd frontend
npm install
npm run dev

🔑 Default Demo Credentials

All seed demo accounts share the uniform password: password

Role	Name	Email	Password	Access Level & Key Capabilities
Super Admin	Administrator Sistem	`[email protected]`	`password`	Master data (teachers, students, classes, subjects), announcements, school configuration, and 1-click account impersonation
Teacher	Budi Santoso, S.Pd.	`[email protected]`	`password`	Learning materials, homework assignment grading, CBT exam authoring, question bank editor, live WebSocket proctoring monitor, and exam cards print
Teacher	Siti Aminah, M.Kom.	`[email protected]`	`password`	Database teacher with pre-assigned classes & materials
Student	Andi Pratama	`[email protected]`	`password`	Mobile dashboard, CBT exam runner with anti-cheat detection, homework submissions, gradebook summary, and print exam hall ticket
Student	Bella Safira	`[email protected]`	`password`	Peer student account for multi-user CBT exam simulation

🧪 Running Automated Tests

To run the backend integration and unit tests:

# Inside the backend directory (with venv activated)
pytest -v

# Or run inside Docker container
docker compose exec backend pytest -v

📄 License

This project is licensed under the MIT License.

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