MovieRanker

MovieRanker is a prototype web application written in Django. Its primary goal is to help users discover movies tailored to their preferences using The Movie Database (TMDB) API.

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Features

• Integration with TMDB API: Fetch movie genres, ranks, and other details using TMDB API endpoints.
• Genre Filtering: Filter movies by selecting genres from a dropdown menu.
• Dynamic Movie List: Display a ranked list of movies based on the selected genre.
• Movie Details Page: View detailed information about a selected movie.

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Key Components

1. api.py:

   • Interacts with the TMDB API.
   • Fetches genres, movies by genre, and detailed movie information.

2. views.py:

   • Handles user requests and business logic.
   • Includes views for the movie list and movie details.

3. models.py:

   • Defines the data structure for movies.

4. movie_list.html:

   • Frontend template for viewing and filtering movies by genre.

5. movie_details.html:

   • Frontend template for displaying detailed information about a specific movie.

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Installation and Setup

Follow these steps to set up and run MovieRanker locally:

Prerequisites

• Python 3.9 or higher
• Django installed
• TMDB API Key (for API integration)

Steps

1. Clone the Repository:

   git clone https://github.com/Mike014/MovieRanker.git
   cd MovieRanker

2. Set Up a Virtual Environment:

   python3 -m venv venv
   source venv/bin/activate  # Mac/Linux
   venv\\Scripts\\activate     # Windows

3. Install Dependencies:

   pip install -r requirements.txt

4. Run Database Migrations:

   python manage.py migrate

5. Set Up TMDB API Key: • Create a .env file in the root directory. • Add your TMDB API key:

   TMDB_API_KEY=your_api_key_here

6. Run the Development Server:

   python manage.py runserver

7. Access the Application:

   http://127.0.0.1:8000/
   

Development Workflow

Linting and Formatting

• This project uses Pylint, Black, and isort for linting and formatting. Pre-commit hooks are set up to enforce these standards.

  1. Install pre-commit:

     pip install pre-commit
     pre-commit install

  2. Run pre-commit hooks:

     pre-commit run --all-files

  Running Tests

  To run tests, use:

  pytest

  Using Tox Tox is configured to automate testing and linting:

  tox

  GitHub Actions The project includes a GitHub Actions workflow for automated testing and linting. The configuration is in .github/workflows/lint-and-test.yml.

  Running Django Tests To run Django tests for the Movies app and discover any bugs, you can use the following command:

   python manage.py test movies

Useful TMDB API Endpoints

1. Fetch Genre List:

   https://api.themoviedb.org/3/genre/movie/list

2. Discover Movies by Genre:

   https://api.themoviedb.org/3/discover/movie

3. Get Movie Details:

   https://api.themoviedb.org/3/movie/{movie_id}

4. Fetch Similar Movies:

   https://api.themoviedb.org/3/movie/{movie_id}/similar

Back-End Database with PostgreSQL

Install and Configure Docker

1. Install Docker:

   • Visit Docker Desktop and download the version for your operating system (Windows, macOS, Linux).
   • Follow the installation instructions.

2. Start a PostgreSQL Container:

   docker run --name postgres -e POSTGRES_PASSWORD=your_password_here -d -p 5432:5432 postgres

3. Verify the PostgreSQL Container is Running::

   docker ps

   • Displays all active containers.

4. Test Database Connection::

   docker ps

   OR

   python manage.py dbshell

   • Perform Database Migrations

   python manage.py makemigrations
   python manage.py migrate

Querying the Database

• First i have created a Custom Management Command:

movies/
    management/
        __init__.py
        commands/
            __init__.py
            query_movies.py

• To run the command, use:

python manage.py query_movies --type all

• Check in the query_mvovies.py which command you can use for querying the database

Documentation

• The documentation for MovieRanker is available at: MovieRanker Documentation
• Created a new requirements.txt file with command:

pip install pipreqs
pipreqs .

• created docker file, you can buld the image with this command:

docker build . -t movies:latest && docker run -e PYTHONUNBUFFERED=1 -p 8000:8000 movies

• Go to Link

Future Goals

• Implement content-based and collaborative filtering for advanced movie recommendations.
• Enhance user interface and add user authentication.
• Deploy the application on a cloud platform.

License

This project is licensed under the MIT License.

Contributing

Contributions are welcome! Feel free to fork the repository and submit pull requests.

Contact

Maintainer: Michele Grimaldi GitHub: Mike014Mike014