Project Task API - Backend

A professional Django REST API for project and task management with time tracking capabilities.

Features

• Authentication System: Secure login/logout with custom landing page
• Project Management: Create, edit, delete, and list projects with pagination and filtering
• Task Management: Comprehensive task management with status tracking and time estimation
• Time Tracking: Start/stop timers for tasks with automatic time accumulation
• Dashboard Analytics: Aggregate metrics and reporting with caching optimization
• Advanced Filtering: Search and filter across projects and tasks
• API Documentation: Auto-generated OpenAPI/Swagger documentation

Tech Stack

• Backend: Django 5 + Django REST Framework
• Database: PostgreSQL (with fallback)
• Caching: Redis for performance optimization
• Containerization: Docker & Docker Compose
• Documentation: drf-spectacular (OpenAPI/Swagger)
• Testing: pytest

Quick Start

Using Docker (Recommended)

1. Clone the repository

   git clone https://github.com/ndongchrist/Project-Task-APIs.git
   cd Project-Task-APIs

2. Start the application

   Before running the command to build images, create a .env file and copy the content of .env-docker-sample.txt into the .env (this will be config for docker services)

   docker compose up -d --build

3. Run migrations and create sample data

   docker compose exec -it web python manage.py migrate  #This commands will migrate changes into the DB
   docker compose exec -it web python manage.py create_sample_data # This commands will create sample data for test
   docker compose exec -it web python manage.py create_demo_user # email: admin123@devsecurity.com psswd: admin123

4. Access the application

   • Access the Application on your browser via(Login Page): http://0.0.0.0:8002/
   • Swagger Documentation: http://0.0.0.0:8002/api/docs/ # you need to be login in order to access this documention use the credentials provided by the create_demo_user command
   • Admin Panel: http://0.0.0.0:8002/admin/

Local Development

1. Setup virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt

2. Environment configuration

   Create a file .env at the level of the project and then copy this content inside and make sure it matches your local configuration

   # Sample env
   DB_NAME=your-db-name
   DB_USER=postgres
   DB_PASSWORD=your-passwd
   DB_HOST=localhost
   DB_PORT=5432
   
   ADMIN_URL=admin/
   DEBUG=True
   SECRET_KEY=your-secret-key
   REDIS_URL=redis://localhost:6379/0

3. Run migrations and create sample data

   python manage.py migrate
   python manage.py create_sample_data --projects 10 --tasks-per-project 8
   python manage.py create_demo_user 

4. Start development server

   python manage.py runserver

   Access the application on a browser via: http://127.0.0.1:8002/

API Endpoints

Projects

• GET /api/v1/projects/ - List projects with pagination and filtering
• POST /api/v1/projects/ - Create new project
• GET /api/v1/projects/{id}/ - Get project details
• PUT /api/v1/projects/{id}/ - Update project
• DELETE /api/v1/projects/{id}/ - Delete project

Tasks

• GET /api/v1/tasks/ - List tasks with filtering
• POST /api/v1/tasks/ - Create new task
• GET /api/v1/tasks/{id}/ - Get task details
• PUT /api/v1/tasks/{id}/ - Update task
• DELETE /api/v1/tasks/{id}/ - Delete task

Time Tracking

• POST /api/v1/tasks/{id}/start-timer/ - Start timer for task
• POST /api/v1/tasks/{id}/stop-timer/ - Stop active timer

Dashboard

• GET /api/v1/dashboard/ - Get dashboard overview with metrics

Tokens

• POST /api/token/refresh/ - Refreshes the JWT access token using a valid refresh token.
• POST /api/token/ - Obtain JWT access and refresh tokens for authentication.

Authentication

• POST /api/auth/logout/ - For Logging out
• POST /api/auth/register/ - For Registering into the Application

Architecture Highlights

Performance Optimizations

• Database: Optimized queries with select_related() and prefetch_related()
• Caching: Redis caching for dashboard metrics and frequent queries
• Indexing: Strategic database indexes on frequently queried fields
• Pagination: Efficient pagination for large datasets

Code Quality

• Type Hints: Full type annotation throughout the codebase
• Transaction Safety: @transaction.atomic for data consistency
• Error Handling: Comprehensive error handling with proper HTTP status codes
• Logging: Structured logging for debugging and monitoring

Security

• Validation: Input validation at serializer and model levels
• Constraints: Database-level constraints for data integrity
• UUID: UUIDs as primary keys to prevent enumeration attacks

Testing

Run the test suite:

# Using Docker
docker compose exec -it web bash 

#then while inside the shell found in the container enter...
pytest --cov=project

# Local development
pytest --cov=project

Development Notes

What I Enjoyed

• Implementing the time tracking system with database constraints
• Optimizing queries with Django ORM features
• Creating comprehensive API documentation + Custom Landing Page for accessing API's
• Building a robust caching strategy using Redis

What Could Be Improved With More Time

• WebSocket Integration: Real-time timer updates
• Advanced Analytics: More detailed reporting
• File Uploads: Task attachments and project documents
• Notification System: Email/push notifications for task updates
• Implement Celery: Using Celery for Background Tasking for counting or sending emails
• Email Activation For Accounts: Sending Links to Users who register through the API asking the to Activate thier accounts.

Satisfied Components

• Database Design: Well-normalized schema with proper relationships
• API Architecture: RESTful design with consistent patterns
• Performance: Efficient queries and caching implementation

Author

• Name: Ndongmo Nguimfack Christian
• Email: christianhonore2003@gmail.com

Thank you.. Kindly Waiting for your reviews