ALX Movie Recommendation App

Overview

This case study focuses on developing a robust backend for a movie recommendation application. The backend provides APIs for retrieving trending and recommended movies, user authentication, and saving user preferences. It emphasizes performance optimization and comprehensive API documentation.

Project Goals

The primary objectives of the movie recommendation app backend are: -

• API Creation: Develop endpoints for fetching trending and recommended movies.
• User Management: Implement user authentication and the ability to save favorite movies.
• Performance Optimization: Enhance API performance with caching mechanisms.

Technologies Used

Technology	Purpose
Django	For backend development.
PostgreSQL	Relational database for data storage.
Redis	Caching system for performance optimization.
JWT	Secure role-based authentication
Swagger	API documentation and testing

Key Features

• API for Movie Recommendations:

  • Integrate a third-party movie API (e.g., TMDb) to fetch and serve trending and recommended movie data.
  • Users can save there favorite movies.

• User Authentication and Preferences:

  • Implement JWT-based user authentication for secure access.
  • Create models to allow users to save and retrieve favorite movies.

• Performance Optimization:

  • Use Redis for caching trending and recommended movie data to reduce API call frequency and improve response time.

• Comprehensive Documentation:

  • Use Swagger to document all API endpoints.
  • Host Swagger documentation at /api/docs for frontend consumption.

Deployment

The backend is deployed on Render using PostgreSQL as the database.

• API URL: https://alxprodev-movie-recommendation-backend.onrender.com/api
• Swagger Documentation: https://alxprodev-movie-recommendation-backend.onrender.com/api/docs

Database

Entities and Attributes

USERS

id: Primary Key, UUID, Indexed
first_name: VARCHAR, NOT NULL
last_name: VARCHAR, NOT NULL
email: VARCHAR, UNIQUE, NOT NULL
password: VARCHAR, NOT NULL
created_at: TIMESTAMP, DEFAULT CURRENT_TIMESTAMP

FAVORITE

users: Foreign Key, references User(user_id)
movie_id: VARCHAR, NOT NULL
title: VARCHAR, NOT NULL
overview: TEXT, NOT NULL
poster: VARCHAR, NOT NULL
language: VARCHAR, NOT NULL
rating: DECIMAL, NOT NULL
created_at: TIMESTAMP, DEFAULT CURRENT_TIMESTAMP

ER-Diagram

API Endpoints

1. User Login (JWT Token Generation)

• Endpoint: POST /api/users/login/
• Description: Authenticates the user and returns a JWT access and refresh token.
• Request Body:

{
  "email": "example@gmail.com",
  "password": "example_password"
}

• Response Body:

{
  "access": "jwt_access_token",
  "refresh": "jwt_refresh_token"
}

• Access Token Lifetime: 15 minute
• Refresh Token Lifetime: 1 day

2. User Signup

• Endpoint: POST /api/users/signup/
• Description: Registers a new user.
• Request Body:

{ 
    "email": "user@example.com",
    "first_name": "John",
    "last_name": "Doe",
    "password": "password123" 
}

• Response Body:

{ 
    "message": "User created successfully" 
}

3. Refresh token

• Endpoint: POST /users/token/refresh/
• Description: Refresh user access token.
• Request Body:

{
    "refresh": "<your_refresh_token>"
}

• Response Body:

{
    "access": "<new_access_token>"
}

4. Get Trending Movies

• Endpoint: GET /api/movies/trending/
• Description: Fetches trending movies from TMDb.
• Response Body:

{
    "results": [ 
        { 
            "movie_id": "123",
            "title": "Movie Title",
            "overview": "Movie description",
            "poster": "poster_url",
            "language": "en",
            "rating": 8.5 
        } 
    ] 
}

5. Get Movie Recommendations

• Endpoint: GET /api/movies/recommendations/{movie_id}/
• Description: Fetches recommended movies based on a given movie ID.
• Response Body:

{
    "results": [ 
        { 
            "movie_id": "123",
            "title": "Movie Title",
            "overview": "Movie description",
            "poster": "poster_url",
            "language": "en",
            "rating": 8.5 
        } 
    ] 
}

6. Save a Favorite Movie

• Endpoint: POST /api/favorites/
• Description: Saves a movie to the user's favorites.
• Request Body:

{ 
    "movie_id": "123",
    "title": "Movie Title",
    "overview": "Movie description",
    "poster": "poster_url",
    "language": "en",
    "rating": 8.5 
}

• Response Body:

{ 
    "message": "Movie saved as favorite" 
}

7. Get Favorite Movies

• Endpoint: GET /api/favorites/
• Description: Fetches the logged-in user's favorite movies.
• Response Body:

[ 
    { 
        "movie_id": "123",
        "title": "Movie Title",
        "overview": "Movie description",
        "poster": "poster_url",
        "language": "en",
        "rating": 8.5 
    } 
]

8. Delete a Favorite Movie

• Endpoint: DELETE /api/favorites/{id}/
• Description: delete a movie from the user's favorites.
• Response Body:

{
    "message": "Favorite movie deleted successfully"
}

Environment variable

# Database connection
DB_NAME=''
DB_USER=''
DB_PASSWORD=''
DB_HOST=''
DB_PORT=

# Redis Location
REDIS_LOCATION=''

# Django secrete key
SECRET_KEY='

# TMDB API key
TMDB_API_KEY=''

Accessing TMDB images

https://image.tmdb.org/t/p/original/<poster>