####################################### Movie Recommendation System |warning| #######################################

|CodeQL Workflow Status|

.. |CodeQL Workflow Status| image:: https://github.com/livxy/MovieRecommendationSystem/actions/workflows/codeql.yml/badge.svg :target: https://github.com/livxy/MovieRecommendationSystem/actions/workflows/codeql.yml

Note: This project is currently a work in progress and is not yet ready for production use. It is being actively developed and may undergo significant changes. Contributions and suggestions are welcome!

IMPORTANT: This is in Java 11, so make sure you have Java 11 <https://www.oracle.com/java/technologies/downloads/#java11>_ installed on your system.

Movie Recommendation System is a Java-based project developed using Spring Boot <https://spring.io/projects/spring-boot>_ (version: 2.3.4) and MySQL <https://www.mysql.com/>_ (version: 8.0). It provides a platform for users to register, rate movies, and receive personalized movie recommendations based on their preferences and ratings.

Features

User Registration: |warning|
Movie Database: |warning|
Rating System: |warning|
Recommendation Algorithm: |warning|
User Interface: |warning|
Search Functionality: |warning|
Top Rated Movies: |warning|
User Profile: |warning|
Persistence: |warning|
Error Handling: |warning|

.. |warning| image:: https://img.shields.io/badge/Status-In%20Progress-yellow :target: https://img.shields.io/badge/Status-In%20Progress-yellow

Installation

#. Clone the repository:

.. code:: bash

git clone https://github.com/username/MovieRecommendationSystem.git

Download Docker Desktop <https://www.docker.com/>_ and MySQL 8.0 (use MySQL Installer <https://dev.mysql.com/downloads/installer/>_) and run the following commands:

#. Configure the MySQL container in docker-compose-mysql.yml </docker-compose-mysql.yml>_ (change out the MYSQL_ROOT_PASSWORD value to whatever password you want to use when logging in to MySQL Command Line Client/MySQL Workbench):

.. code:: yaml

  version: '3.8'

  services:
    localmysql:
      container_name: db
      restart: always
      image: 'mysql'
      environment:
        MYSQL_DATABASE: 'movie_recommendation'
        MYSQL_ROOT_PASSWORD: yourpassword # Change this to your own password

      ports:
        - 3308:3306
  #    volumes:
  #      - 'db:/var/lib/mysql'
  ##      - './db/init.sql:/docker-entrypoint-initdb.d/init.sql'
  #volumes:
  #  mysqldata:

#. Open a terminal, and the Docker Desktop application, and run the following command to start a MySQL container:

.. code:: bash

  cd /path/to/MovieRecommendationSystem
  docker-compose -f docker-compose-mysql.yml up -d

#. Update the database configuration in src/main/resources/application-default.properties:

.. code:: properties

  spring:
    task:
      execution:
        pool:
          core-size: 10
          max-size: 20
          queue-capacity: 50
    datasource:
      url: jdbc:mysql://127.0.0.1:3308/movie_recommendation
      username: root # Change this to your own username
      password: yourpassword # Change this to your own password
    jpa:
      hibernate:
        ddl-auto: update
  #  lifecycle:
  #    timeout-per-shutdown-phase: 20s
  #
  #logging:
  #  level:
  #    com.movie.recommendation: debug


  server:
    port: 8080
    shutdown: graceful

Install maven dependencies:

.. code:: bash

cd MovieRecommendationSystem mvn install

#. Download MovieLens Dataset and Extract Data:

#. Make sure you have Git Bash installed on your system. If you are using Windows, open Git Bash for the following steps.

#. Open your terminal or Git Bash and navigate to the root directory of your MovieRecommendationSystem project.

#. Copy and paste the following one-liner command into your terminal or Git Bash:

  .. code:: bash

     if [ ! -d "src/main/resources/data/ml-25m" ]; then curl -O https://files.grouplens.org/datasets/movielens/ml-25m.zip && unzip ml-25m.zip -d src/main/resources/data/ && rm ml-25m.zip; fi

(Note: If you're on Windows and don't have Git Bash, you can download it from the official website: https://git-scm.com/downloads )

Press Enter to execute the command. The script will download the zip file containing the MovieLens dataset and extract its contents to src/main/resources/data/ml-25m/.

#. After the command completes, the zip file will be removed, and you should see the MovieLens dataset files in the src/main/resources/data/ml-25m/ directory of your project.

#. Build and run the application using Maven:

.. code:: bash

  cd MovieRecommendationSystem
  mvn spring-boot:run

#. Create an HTTPS request to any of the endpoints, for example, to load in the data from the MovieLens dataset, you can create a POST http://localhost:8080/loadDefaultMovies request using Postman, or commands like:

.. code:: bash

  curl -X POST http://localhost:8080/loadDefaultMovies

Or on Windows:

.. code:: powershell

  Invoke-WebRequest -Method POST -Uri http://localhost:8080/loadDefaultMovies"

Contributing

Contributions are welcome ❤️! If you find any issues or have suggestions for improvements, please feel free to submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE </LICENSE>_ file for more information.

.. |nl| raw:: html

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MovieRecommendationSystem

Install / Use

README

Contributing