Project Background and Overview

We are a group of Data Science and Analytics students from NUS working on optimizing entertainment and attraction prices.

In this project, we offer visualizations for product-specific data, which include occupancy rate and product revenue, as well as factors that impact product performance, like competitor prices and tourism information. We also utilized mesa, an agent based simulation model to find the best pricing strategy to maximize revenue.

Instruction on Running the Model

Run the Model Using Docker

Prerequisite

• Ensure Git and Docker are installed on your system.

Steps

1. Clone the Repository:

   • In your terminal/command prompt, navigate to the directory where you want to clone the repository:

     cd /path/to/your/desired/directory

   • Clone the repository in the desired directory:

     git clone https://github.com/clementlemon02/Competitive-Pricing-Analysis.git

   • After cloning, navigate into the cloned repository directory:

     cd Competitive-Pricing-Analysis

2. Set up Environment Variables:

   • Copy the .env.example file in the backend directory and rename it to .env.
   • Configure the environment variables in the .env file as per your requirements.

3. Build Docker Images:

   • Navigate to the root directory of the cloned repository.

   • Change directory to the root directory of the cloned repository where your docker-compose.yml file is located.

   • Run the following command to build Docker images:

     docker-compose build

4. Verification:

   • You can verify that the images are successfully built by running:

     docker images

5. Start Docker Containers:

   • Ensure you are still in the root directory of your cloned repository where your docker-compose.yml file is located.

   • Start the Docker Containers:

     docker-compose up

6. Access the Application:

   Once the containers are up and running, you can access the application in your web browser using the URLs specified in the application’s documentation or configuration.

   • Backend API: http://127.0.0.1:5000/
   • Frontend Dashboard: http://127.0.0.1:8050/pricing-simulation

7. Data Visualization and Pricing Simulation:

   Once you have accessed the frontend dashboard using the specified URL, you can proceed to view the different pages of the application, including "Introduction", "Data Visualization" and "Pricing Simulation".

8. Stop Docker Containers:

   • To stop the application, ensure you are in the same directory where the docker-compose.yml file is located, typically the root directory of your cloned repository.
   • Run the following command in terminal/command prompt:

   docker-compose down

9. Verification:

   You can verify that the containers are stopped and removed by running:

   docker ps -a

   After running docker-compose down, you should not see any containers related to the application in the list.

Additional notes:

• Running docker-compose down does not remove the Docker images that were built earlier. If you want to remove the images as well, you can use the docker-compose down --rmi all command. However, be cautious as this will remove all Docker images associated with your project.
• After stopping the containers, you can start them again using docker-compose up whenever you want to run your application.

Alternatively, we also suggest another way to run the model. If you have python installed on your system, you can create a virtual environment in the root directory using venv or virtualenv. Then, activate the environment and install dependencies from requirements.txt. Next, configure environment variables by copying .env.example to .env in the backend directory and adjust values as needed. Finally, execute run.py to start the backend server and frontend webpage, accessing the application through specified URLs in a web browser.

Remarks: If you're using macOS, you might need to make a minor adjustment in run.py. For more information, please consult the instructions provided within the run.py file.