Features

• Select a date to view the theater with the highest sales for that day.
• Display a chart of monthly sales for the top-selling theater.
• Seamless data management using Flask-SQLAlchemy and Flask-Migrate.
• API endpoints to fetch sales data dynamically.

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Database Schema

Schema dump in root folder dump.sql

Tables and Relationships

Theater

- `id` (Primary Key): Unique identifier for the theater.
- `name` (String): Name of the theater.
- `location` (String): Location of the theater.

Movie

- `id` (Primary Key): Unique identifier for the movie.
- `title` (String): Title of the movie.
- `genre` (String): Genre of the movie (e.g., Action, Comedy, Drama).
- `release_date` (Date): Release date of the movie.

Sale

- `id` (Primary Key): Unique identifier for the sale record.
- `theater_id` (Foreign Key): References `Theater.id`.
- `movie_id` (Foreign Key): References `Movie.id`.
- `sale_date` (Date): The date of the sale.
- `tickets_sold` (Integer): Number of tickets sold.

Relationships

- Each sale is linked to one theater and one movie.

Indexes

- theater_id(Foreign key index)
- movie_id(Foreign key index)
- sale_date(Foreign key index)
- theater_id, movie_id, sale_date(Composite index for faster look up)

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Project Setup

Prerequisites

• Docker and Docker Compose installed on your system.

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Steps to Run the Project

Clone the Repository:

git clone https://github.com/elite133713/ata-python.git
cd ata-python

Build and Start the Containers

docker-compose up -d --build

Seed the Database

docker-compose exec app bash

Run the seeder to populate the database(may take several minutes)

flask seed

Data Seeded

Theaters:

• 1,000 theaters with unique names and locations.

Movies:

• 20,000 movies with random titles, genres, and release dates.

Sales:

• ~ 3,600,000 sales records spanning 2024-01-01 to 2024-12-31.

Access the Application

Open your browser and navigate to http://localhost:8090.