27 Best Django Project Ideas & Topics For Beginners

For professionals looking to build scalable and secure web applications, Django is a top-tier framework known for its efficiency and reliability. It is one of the most popular web frameworks in Python development today, used by big names like:

• Instagram
• Pinterest
• Mozilla
• Disqus
• National Geographic

As of 2024, Django powers many websites, and over 12% of professional developers worldwide rely on Django to build web applications, making it a top choice in the Python ecosystem.

Django’s popularity comes from its "batteries-included" approach, offering built-in tools and features like user authentication, security, and URL routing. This framework allows developers to create robust web applications efficiently and with minimal setup.

If you're new to Django and looking to practice your web development skills, we've compiled 27 of the best Python Django project ideas. These projects will help you understand Django’s core concepts, improve your coding skills, and build real-world applications. From simple to-do lists to more complex social media platforms, there’s a project here to fit your level. 

Let’s explore these exciting Python Django project ideas!

Django Web Development Project Ideas

Web development projects are a great way for beginners to get hands-on experience with Django’s core features, like user authentication, content management, and database handling. Here are a few project ideas to help you get started:

1. Collaborative Online Whiteboard Tool for Remote Teams

In this project, you’ll build an online whiteboard tool where up to 50 users can collaborate in real-time using WebSocket technology for instant updates. The tool includes precise drawing tools (up to 1-pixel accuracy), text options, and shape and image uploads for versatile brainstorming. Export options let users save boards in formats like PNG, JPEG, or PDF. A Django-based authentication system manages guest and registered user access, with guests limited to viewing and registered users having full interaction capabilities. This project is designed to support small to mid-sized teams in remote work environments.

• Key Features: Real-time collaboration, user authentication, export options as images or PDFs.
• Technical Details: Implement Django Channels for real-time functionality, Redis for message brokering, and Django’s built-in authentication system.
• Who It’s Perfect For: Remote teams and educational platforms needing interactive collaboration tools.

Example Project (Source Code): Collaborative Whiteboard Tool

2. Customizable Event Management System

This project enables event organizers to create and manage events with precision. Core components include a secure ticketing module for handling sales and issuing unique QR codes for each ticket, streamlining entry management. Integrated with payment gateways like Stripe and PayPal, it supports real-time transactions and handles ticket pricing options from ₹75 to ₹7,500. Automated email reminders go out 24 and 48 hours before the event to ensure high engagement. The project’s backend uses Django with RESTful APIs to enable scalability, making it perfect for events with attendee counts from 50 to over 5,000.

• Key Features: Event creation, ticket sales, QR code generation, payment gateway integration (Stripe, PayPal).
• Technical Details: Use Django’s form handling for event management, signals for automated email reminders, and Django Rest Framework (DRF) for handling API integrations.

• Who It’s Perfect For: Businesses and event planners who need a streamlined system for organizing events, selling tickets, and managing attendees.

  Example Project (Source Code): Django Event Management System

3. Local Neighborhood Community Platform

This community platform connects neighbors, allowing users to list services like tutoring or plumbing. It includes a reputation system with ratings from 1 to 5 stars, letting users quickly evaluate service providers. Each listing features details like service type, availability, and hourly rate (e.g., ₹750 to ₹7,500 per hour), and a secure in-app messaging system for smooth coordination. Built on Django and SQLite, it efficiently handles data for small to mid-sized communities of around 500-2,000 users, encouraging local connections and support.

• Key Features: User-generated posts for services, messaging between users, user reputation, and ratings system.
• Technical Details: Use Django models for user profiles and services, Django ORM for database management, and Django Channels/WebSockets for real-time messaging.

• Who It’s Perfect For: Local communities or neighborhood groups that need a platform for service exchange and communication.

  Example Project (Source Code): Django Neighborhood Services Platform

Django Game Development Project Ideas

Game development using Django may seem unconventional, but it provides a fun way to explore real-time interactions and game logic. Here are some exciting Django game development project ideas:

4. Real-Time Multiplayer Word Puzzle Game

Build a multiplayer word puzzle game that operates in real-time, letting up to 100 players compete simultaneously. With a WebSocket-based backend, it delivers real-time updates to players, tracking points as puzzles are solved. Each game has timed rounds (e.g., 2-minute rounds) and a scoring system that assigns 10 points per correctly solved word. A leaderboard tracks top players, while a chat function supports live interaction. The game can be expanded with new puzzle categories, adding to its replay value and keeping players engaged.

• Key Features: Multiplayer gameplay, real-time updates, leaderboard, integrated chat.
• Technical Details:
  • Use Django Channels to handle real-time communication via WebSockets.
  • Redis or RabbitMQ for message brokering.
  • Implement game logic with Python to manage puzzle challenges and scoring.

• Who It’s Perfect For: Anyone interested in developing real-time multiplayer games, especially those who want to integrate chat and competitive elements.

  Example Project (Source Code): Real-Time Multiplayer Word Puzzle Game

5. Web-Based Scavenger Hunt Game

This scavenger hunt game uses GPS to create location-based challenges and clues. Players register solo or in teams of up to 5, and each clue is unlocked within a 500-meter range of the designated location. The game awards points (e.g., 50 points per completed clue) and digital badges for achievements. A leaderboard tracks team progress, adding a competitive element. Built using Django with a PostgreSQL database, it’s ideal for hosting large scavenger hunts with up to 1,000 players and includes anti-cheat measures to prevent players from skipping locations.

• Key Features: Location-based challenges, team creation, achievements, and badges.
• Technical Details:
  • Integrate with the Google Maps API for GPS tracking.
  • Use Django ORM to store user progress and achievements.
  • Implement middleware to manage team-based gameplay and clues.

• Who It’s Perfect For: Ideal for outdoor event organizers, adventure companies, and educational groups that want to incorporate location-based challenges.

  Example Project (Source Code): Web-Based Scavenger Hunt Game

6. Time Management Simulation Game

Develop a time management game where AI-driven characters perform daily tasks like cooking, cleaning, or working. Players race against the clock, aiming to complete tasks within specific time limits to score points. Each task has its own time limit (e.g., 2-5 minutes), and players earn higher scores by completing tasks faster than the AI characters. Built with Python and Django, the game includes a scoring system based on task efficiency, encouraging strategic decision-making. This simulation is ideal for time-based gaming enthusiasts and introduces players to effective time management skills in a fun way.

• Key Features: AI-driven characters, time-based gameplay, scoring system.
• Technical Details:
  • Use Python’s AI libraries (like PyBrain or TensorFlow) for AI-driven characters.
  • Store player progress and tasks using Django models.
  • Implement time-based logic using Python’s scheduling libraries (like APScheduler).

• Who It’s Perfect For: This project is perfect for those interested in AI integration and simulation games that focus on time management.

  Example Project (Source Code): Time Management Simulation Game

Django Artificial Intelligence Project Ideas

AI-based projects showcase Django’s flexibility when combined with machine learning and data science tools. Below are some AI-based project ideas:

7. Resume Screening Tool

Create a resume screening tool designed for HR professionals, leveraging natural language processing (NLP) to analyze and rank resumes. The tool scans resumes for keywords related to job roles, such as "Python," "project management," or "data analysis." A scoring algorithm assigns scores based on keyword relevance, ranking candidates with a score from 0 to 100. The tool also generates reports, highlighting each candidate’s skills match to specific job descriptions. With Django as the backend and a PostgreSQL database, this tool supports HR departments by streamlining the hiring process for companies with high applicant volumes.

• Key Features: Resume analysis, keyword matching, candidate ranking, downloadable reports.
• Technical Details:
  • Use Python’s Natural Language Toolkit (NLTK) or SpaCy for keyword extraction.
  • Django Rest Framework (DRF) is used to build APIs for resume analysis.
  • Implement CSV or PDF parsing for uploading resumes.

• Who It’s Perfect For: Ideal for HR departments and recruitment platforms that need efficient candidate screening tools.

  Example Project (Source Code): Resume Screening Tool

8. Home Automation Preference Predictor

This project uses machine learning to predict a user’s home automation preferences for devices like lighting, heating, and security systems. The system learns user habits over time and can automate settings, like adjusting lighting levels based on time of day or preferred temperatures. It also includes a user interface that allows manual adjustments, with feedback loops to improve predictions. Built with Django and an AI library like TensorFlow, the system is designed for homes with up to 20 connected smart devices, ensuring a seamless smart home experience.

• Key Features: Behavior analysis, smart home automation, customizable settings.
• Technical Details:
  • Implement machine learning models using Scikit-learn or TensorFlow.
  • Django Rest Framework for communication with IoT devices.
  • Use Django forms to allow users to adjust preferences manually.

• Who It’s Perfect For: It is ideal for smart home companies or enthusiasts who want to build predictive control systems for home automation.

  Example Project (Source Code): Home Automation Preference Predictor

9. AI-Powered Digital Art Generator

Build an AI-powered system that generates digital abstract art based on user input. Users can select parameters like style (e.g., geometric, fluid, surreal), color palette, and complexity level (1 to 10). The generated artwork can be saved as high-resolution PNG or JPEG files, ready for sharing or printing. With Python and a graphics library like OpenCV, this project combines art and technology, allowing users to create unique pieces with minimal effort. 

• Key Features: User input-driven art generation, customization options, save and share functionality.
• Technical Details:
  • Use Generative Adversarial Networks (GANs) for art generation.
  • Store user input and generated artwork with Django ORM.
  • Implement Celery for handling AI computations asynchronously.

• Who It’s Perfect For: Artists, creatives, and tech enthusiasts looking to explore AI’s creative potential through generative artwork.

  Example Project (Source Code): AI-Powered Digital Art Generator

Django Machine Learning Project Ideas

These machine learning projects use Django as the backend to provide smart, data-driven solutions. Here are some engaging ideas to start with:

10. Personalized Fitness Plan Generator

Create a fitness plan generator that tailors workouts based on user data such as age, body measurements, and fitness goals (e.g., weight loss, muscle gain, flexibility). Users input data, and the system generates a 4- to 12-week plan, with exercise recommendations that adjust as users progress. The system tracks metrics like weight and strength gains, modifying the plan as needed. Built with Django, this tool is ideal for gyms or individual fitness enthusiasts, providing a personalized workout experience without requiring a personal trainer.

• Key Features: Generate personalized workout plans, track progress, and integrate with fitness tracking devices.
• Technical Details:
  • Use Scikit-learn to implement machine learning models that analyze user data.
  • Django’s form validation can be used to collect and validate user input.
  • Integrate third-party fitness APIs (e.g., Fitbit) to track user activity.

• Who It’s Perfect For: Fitness enthusiasts or trainers who need a system to generate tailored workout routines based on user data.

  Example Project (Source Code): Personalized Fitness Plan Generator

11. Job Recommendation Engine

In this project, you’ll build a job recommendation engine that uses machine learning to suggest job listings based on user data like skills, salary, experience, and preferred job type. The recommendation model can handle databases with up to 50,000 job listings and uses collaborative filtering to personalize suggestions. Users can filter job results by location (within a 50-mile radius), salary range (₹22,50,000 to ₹1,50,00,000), and job type (full-time, part-time, freelance). A Django backend with a PostgreSQL database manages job listings, applications, and user preferences, while a tracking feature helps users keep tabs on saved jobs and application status.

• Key Features: Job recommendations, filtering options, job application tracking.
• Technical Details:
  • Use collaborative filtering or content-based filtering to recommend jobs.
  • Build an API using Django Rest Framework (DRF) to connect with external job databases.
  • Implement Django’s form and model validation to store user data and job history.

• Who It’s Perfect For: Job seekers looking for tailored job suggestions and companies building job recommendation platforms.

  Example Project (Source Code): Job Recommendation Engine

12. Real-Time Fraud Detection System

Develop a real-time fraud detection system for e-commerce, which monitors up to 100 transactions per second and flags suspicious activity based on preset rules and machine learning models. The system analyzes transaction attributes like location, amount, and device type, flagging anomalies in under a second. Alerts trigger when patterns indicate potential fraud (e.g., large purchases outside typical locations), and a dashboard visualizes fraud trends and daily alerts. The project leverages Django for data handling, Redis for fast caching, and Matplotlib to plot activity for ongoing monitoring.

• Key Features: Real-time fraud analysis, transaction monitoring, real-time alerts, and visual dashboards.
• Technical Details:
  • Train machine learning models using Scikit-learn or TensorFlow to identify fraud patterns.
  • Use Django Channels to handle real-time fraud alerts.
  • Integrate with payment gateways to monitor live transactions.

• Who It’s Perfect For: E-commerce platforms or financial institutions looking to monitor and prevent fraudulent transactions.

  Example Project (Source Code): Real-Time Fraud Detection System

Django Data Science Project Ideas

Use Django for data science projects involving large datasets, visualizations, and real-time analytics. Here are a few project ideas to help you get started:

13. Environmental Impact Calculator

This tool calculates a user’s carbon footprint based on lifestyle factors, including transportation, diet, and energy usage. For example, selecting "car" as a transport option calculates emissions based on average fuel usage, while dietary choices like “meat-based” adjust estimates by up to 2,000 kg CO₂ per year. Users can view comparisons to the global average of ~4,800 kg CO₂ annually and receive suggestions to reduce their footprint. Built using Django and Python, this calculator is perfect for eco-conscious users and integrates with Matplotlib to visualize monthly or yearly carbon savings.

• Key Features: Carbon footprint calculation, global comparison, emission reduction suggestions.
• Technical Details:
  • Use Pandas for data analysis and manipulation.
  • Implement Django forms for user input and validation.
  • Use Plotly or Matplotlib to generate real-time visualizations.

• Who It’s Perfect For: Environmental organizations or individuals interested in tracking and reducing their carbon footprint.

  Example Project (Source Code): Environmental Impact Calculator

14. Social Media Analysis Tool

Develop a social media analytics tool to track trending topics across platforms like X and Facebook. The tool integrates with social media APIs, retrieves data in real-time, and processes up to 500,000 posts daily. Key features include trend tracking, data visualization with charts (e.g., Matplotlib or Plotly), and report exports (PDF or CSV) for specific timeframes. Built with Django, Pandas, and a PostgreSQL database, this tool is ideal for marketers or researchers analyzing trends, with a history feature that tracks data over time to reveal long-term patterns.

• Key Features: Trend tracking, data visualization, report generation.
• Technical Details:
  • Integrate with social media APIs (e.g., X, Facebook) to gather data.
  • Use Pandas and Matplotlib for data analysis and visualization.
  • Store data using Django models and manage trends over time.

• Who It’s Perfect For: Social media marketers or researchers looking to analyze trends and generate reports.

  Example Project (Source Code): Social Media Analysis Tool

15. Data Visualization Dashboard

Create a dashboard for handling large datasets, providing interactive charts and graphs to help users make sense of complex data. This project supports data imports of up to 1GB and includes filters for data slicing by time, location, or category. With Django and D3.js, the dashboard displays real-time updates and has export options for visuals (PNG, JPEG). It’s ideal for business analysts or project managers who need actionable insights from their data.

• Key Features: Large dataset visualization, interactive charts, real-time updates.
• Technical Details:
  • Use Plotly to create dynamic and interactive visualizations.
  • Leverage Django’s ORM for efficient data storage and retrieval.
  • Implement Django Celery to schedule background tasks and real-time data updates.

• Who It’s Perfect For: Data analysts or companies need to visualize large datasets in real-time.

  Example Project (Source Code): Data Visualization Dashboard

Django Deep Learning Project Ideas

These projects leverage deep learning models alongside Django to build intelligent applications. Here are a few ideas to explore:

16. Customer Churn Prediction Tool

Develop a churn prediction tool that analyzes customer behavior patterns, using machine learning to provide churn likelihood scores on a scale of 0 to 1. The tool visualizes trends like frequency of logins, purchases, and support requests over time, allowing users to predict and manage churn risk. Built with Django, a machine learning library (e.g., Scikit-Learn), and Matplotlib for visualization, this tool supports customer databases with up to 100,000 profiles, making it perfect for large companies looking to retain clients.

• Key Features: Predict customer churn, display confidence scores, and visualize trends.
• Technical Details:
  • Use TensorFlow or Keras to train deep learning models.
  • Implement Django Rest Framework (DRF) to handle API requests.
  • Use Django forms and templates to display prediction results.

• Who It’s Perfect For: Businesses looking to identify customers at risk of leaving and improve retention strategies.

  Example Project (Source Code): Customer Churn Prediction Tool

17. Image Quality Enhancer

Create an AI-based image enhancer that improves the resolution of low-quality images using deep learning models like SRCNN or EDSR. Users can upload images up to 5MB, compare before and after versions, and download the enhanced image. Built with TensorFlow and Django, this tool uses convolutional neural networks (CNNs) to enhance image clarity, making it ideal for photographers, designers, or anyone looking to upgrade low-res images.

• Key Features: Enhance image resolution, real-time comparison, and download enhanced images.
• Technical Details:
  • Use Generative Adversarial Networks (GANs) to improve image quality.
  • Implement Django’s file handling system to manage image uploads and downloads.
  • Use OpenCV for image processing tasks.

• Who It’s Perfect For: Photographers, graphic designers, or any user wanting to improve image quality using AI.

  Example Project (Source Code): Image Quality Enhancer

18. NLP-Based Article Summarizer

This project involves building an article summarizer that uses NLP techniques like TextRank or BERT to generate concise summaries from long-form content. Users can upload articles up to 10,000 words, and the tool processes them to produce summaries of around 200-300 words. Summaries can be saved in PDF or plain text formats. The backend uses Django, and the NLP processing is handled by libraries like NLTK or Hugging Face Transformers, making this tool ideal for content analysts or researchers looking to distill information quickly.

• Key Features: Automatic article summarization, export summaries, save for later.
• Technical Details:
  • Use Python’s NLTK or SpaCy for natural language processing tasks.
  • Implement Django Celery for handling long-running summarization tasks asynchronously.
  • Use Django ORM to store article data and summaries.

• Who It’s Perfect For: Researchers, students, or content creators who need to summarize lengthy articles quickly.

  Example Project (Source Code): NLP-Based Article Summarizer

Django Computer Vision Project Ideas

Django’s integration with computer vision libraries makes it suitable for building image and video processing applications. Here are some project ideas:

19. Plant Species Identifier

Develop a plant identification tool that uses image recognition to identify plant species from uploaded photos. The system supports images up to 5MB and uses a Convolutional Neural Network (CNN) model like ResNet for classification, achieving over 85% accuracy on common plant species. Upon identification, the tool displays species details, care instructions, and maps out locations where similar plants have been identified, based on user-uploaded data. Built with Django and TensorFlow, this project serves plant enthusiasts and conservationists looking to map and understand local plant diversity.

• Key Features: Plant species identification, care tips, map visualization.
• Technical Details:
  • Use OpenCV and TensorFlow for image recognition.
  • Manage user-uploaded images and species data with Django ORM.
  • Integrate with Google Maps API to visualize plant locations.

• Who It’s Perfect For: Gardeners, botanists, and nature enthusiasts who want to identify plants and share knowledge.

  Example Project (Source Code): Plant Species Identifier

20. Real-Time Crowd Behavior Detection

This application uses computer vision to analyze live video feeds for abnormal crowd behaviors, such as sudden gathering or dispersion patterns. The system can process video at 20 frames per second and trigger real-time alerts when anomalies are detected. Recorded footage analysis is also available for post-event examination. Built with OpenCV and YOLO (You Only Look Once) models, the tool is ideal for security personnel in managing large gatherings or events. A Django backend manages video storage, while a web dashboard offers real-time activity visualization and incident logging.

• Key Features: Live video analysis, real-time anomaly detection, playback for review.
• Technical Details:
  • Use OpenCV for real-time video processing.
  • Implement Django Channels to handle live data streams.
  • Use Celery for processing large datasets in the background.

• Who It’s Perfect For: Event organizers, security teams, or public safety officials monitoring crowds.

  Example Project (Source Code): Real-Time Crowd Behavior Detection

21. Augmented Reality Navigation App

Create an AR navigation app that overlays directional arrows and route instructions on a live video feed. Using ARKit or ARCore, the app provides real-time guidance, recalculating routes based on location changes every 5 seconds. Integrated with GPS data, the app offers optimized paths for walking, driving, or biking, making it ideal for travelers or urban explorers. Built with Django and a mapping API (e.g., Google Maps), the app provides accurate, up-to-date directions and enhances user experience with interactive, real-world navigation cues.

• Key Features: AR-based navigation, real-time updates, route optimization with GPS.
• Technical Details:
  • Use AR.js or OpenCV for augmented reality features.
  • Store and retrieve location data using Django’s ORM.
  • Integrate with third-party GPS APIs to get live route data.

• Who It’s Perfect For: Travelers, delivery services, or anyone needing hands-free, real-time navigation.

  Example Project (Source Code): Augmented Reality Navigation App

Django Internet of Things (IoT) Project Ideas

Use Django to manage IoT devices through a web-based dashboard and data management system. Here are some exciting IoT-based projects to consider:

22. Smart Parking System

This project involves building a smart parking solution that provides real-time updates on parking space availability within a radius of up to 5 miles. Using IoT sensors in parking lots, the system tracks free spaces and integrates with GPS navigation to guide users to the nearest available spot. A built-in payment module enables fee processing, supporting card or mobile payments. Built with Django and PostgreSQL for data storage, this system is ideal for urban areas and can manage up to 1,000 spaces in real-time.

• Key Features: Real-time parking updates, GPS navigation, payment gateway integration.
• Technical Details:
  • Integrate IoT sensors to detect parking space availability.
  • Use Django Rest Framework (DRF) to handle API requests from IoT devices.
  • Implement Django form validation for processing payments.

• Who It’s Perfect For: City planners or parking lot owners looking to optimize space usage and offer a modern parking experience.

  Example Project (Source Code): Smart Parking System

23. Smart Greenhouse Monitoring System

Create a greenhouse monitoring system that tracks and controls environmental factors like temperature, humidity, and soil moisture in real-time. The system includes sensors to gather data at 1-minute intervals and offers remote control for irrigation and ventilation systems via a web or mobile interface. The backend, built with Django, manages alerts for temperature or moisture anomalies and supports remote control of connected devices. This project, with data visualization tools like Matplotlib, is perfect for agricultural enthusiasts or greenhouse operators aiming to maintain optimal plant growth conditions.

• Key Features: Real-time environmental monitoring, remote control of irrigation and ventilation, automatic alerts for threshold breaches.
• Technical Details:
  • Integrate IoT sensors to collect data on temperature, humidity, and soil moisture.
  • Use Django Channels for real-time updates.
  • Implement Django forms and templates to allow users to adjust greenhouse settings.

• Who It’s Perfect For: Farmers or greenhouse operators needing to optimize growing conditions remotely.

  Example Project (Source Code): Smart Greenhouse Monitoring System

24. IoT-Based Waste Management System

This project involves building a smart waste management system using IoT sensors to track fill levels of waste bins in real-time. Sensors placed in bins detect fill levels and send data to a central system, which automates waste collection scheduling based on bin capacity (e.g., 75% full triggers a collection). The system uses LoRaWAN for low-power, long-range data transmission, making it ideal for urban areas with up to 1,000 bins. An analytics dashboard, built with Django and Plotly, provides insights on waste trends and collection efficiency, helping municipalities optimize routes and reduce waste overflow.

• Key Features: Monitor bin fill levels, automate waste collection schedules, display waste trends with real-time analytics.
• Technical Details:
  • Use IoT sensors to track bin usage.
  • Implement Django ORM to store sensor data and generate reports.
  • Use Django templates to build real-time dashboards displaying waste metrics.

• Who It’s Perfect For: Municipalities or companies aiming to improve waste management efficiency through smart technology.

  Example Project (Source Code): IoT-Based Waste Management System

Django eCommerce Project Ideas

Django is ideal for building robust and scalable eCommerce applications. Here are a few eCommerce project ideas to explore:

25. Local Item Rental Marketplace

Develop a rental marketplace where users can list items for rent or borrowing within their locality. The platform supports rental categories like electronics, tools, and recreational gear, with a built-in payment gateway (e.g., Stripe) for handling rental fees. Users can browse items based on location within a 10-mile radius and filter by daily or hourly rates (e.g., ₹375 to ₹7,500 per day). A review and rating system ensures trust between renters and borrowers, while a Django backend with PostgreSQL manages listings, transactions, and user feedback. This project is perfect for promoting sustainable sharing within local communities.

• Key Features: Item listing for rent or borrowing, payment system integration, user reviews, and ratings.
• Technical Details:
  • Use Django’s authentication and user management system to log in and create profiles.
  • Integrate Stripe or PayPal for processing payments.
  • Implement Django ORM to handle rental listings and transactions.

• Who It’s Perfect For: Individuals or businesses looking to create a local marketplace for renting items instead of purchasing.

  Example Project (Source Code): Local Item Rental Marketplace

26. Flash Sale Platform

Create a flash sale platform designed to host limited-time sales with real-time inventory updates. The platform allows sellers to set up sales with countdown timers (e.g., 1 to 24 hours) and notifies users of new deals via push notifications. Inventory management tracks quantities in real-time, with updates every 2 seconds to prevent overselling. Built using Django and WebSockets for real-time data, this platform also includes user profiles with saved preferences and a wishlist, making it suitable for e-commerce sites looking to drive urgency and boost sales.

• Key Features: Real-time inventory updates, countdown timers, and push notifications for deals.
• Technical Details:
  • Use Django Channels to manage real-time updates for inventory levels.
  • Implement Django forms and models to handle product listings.
  • Integrate third-party payment gateways for checkout and payments.

• Who It’s Perfect For: Retailers looking to host high-volume, time-sensitive sales for their customers.

  Example Project (Source Code): Flash Sale Platform

27. Personalized Product Recommendation Engine

This recommendation engine suggests products based on user behavior, including browsing history, clicks, and purchase patterns. Using collaborative filtering and deep learning models, the engine improves suggestions over time, with personalization scores from 0 to 1. Users receive recommendations based on current trends and personal interests, with the system processing up to 10,000 product interactions per day. Built with Django, PostgreSQL, and a machine learning library like Scikit-Learn, this tool is ideal for e-commerce businesses aiming to enhance user engagement and increase sales through personalized shopping experiences.

• Key Features: Personalized product recommendations, machine learning-powered suggestions, custom product pages for users.
• Technical Details:
  • Use collaborative filtering or content-based filtering to generate recommendations.
  • Implement Django ORM to store user behavior data.
  • Integrate third-party analytics tools to gather deeper insights into user preferences.
• Who It’s Perfect For: eCommerce platforms looking to offer tailored product recommendations to enhance customer experience.

Example Project (Source Code): Personalized Product Recommendation Engine

Using Django with Frontend Frameworks

Django works well with frontend frameworks like React, Vue.js, and Angular, allowing you to build dynamic web applications. Using Django as the backend API and a frontend framework for the UI, you create a seamless app with Django managing the data and security.

Setting Up Django as a Backend API

With Django Rest Framework (DRF), Django can serve data as an API:

1. Install DRF: Install it with pip install djangorestframework.

2. Create API Views: Use serializers and viewsets to convert Django models into JSON.

3. Set Up URLs: Define routes in urls.py for the frontend to call.

4. Handle CORS: If the frontend is hosted separately, use django-cors-headers to enable Cross-Origin Resource Sharing.

Example: React Frontend with Django Backend

Create a simple app where Django serves product data to a React frontend:

• Backend: Use DRF to build a product API.

Frontend: Use React to fetch and display data from the Django API. This setup allows Django to handle the backend while React manages the user experience.

How to Build Real-World Projects with Django

When transitioning from small projects to real-world applications, consider scalability, security, and third-party integrations to handle growth and complexity.

Managing Scalability

Django’s modular architecture makes it easy to scale. Use separate apps for different features, optimize database queries, and add load balancers to distribute traffic. This keeps the codebase manageable as the project grows.

Implementing Security Features

Django includes security measures such as:

• CSRF protection: Enabled by default to prevent unauthorized form submissions.

• OAuth: Implement third-party authentication using packages like django-allauth.

• HTTPS: Ensure secure communication by configuring HTTPS in production.

Integrating Third-Party Services

Enhance your application by integrating services like:

• Payment gateways (Stripe, PayPal) for e-commerce.

• Cloud hosting (AWS, DigitalOcean) for scalability.

• Email services like SendGrid are used to handle transactional emails.

Example: Scaling on AWS or Heroku

For example, deploy an e-commerce app:

• Heroku: Use for quick deployment with built-in scaling tools.

• AWS: Set up EC2 instances, RDS for databases, and S3 for file storage. Use load balancers and auto-scaling for handling traffic spikes.

Start Building with Django Today

Django Powers the Web
What powers platforms like Instagram, Pinterest, Spotify, and NASA? These major companies rely on Django to manage millions of users and massive data every day. Django is trusted for its reliability and scalability, making it an essential skill for anyone looking to work in tech.

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