_# Shopping program

This program is a tool enabling effective management of customer purchases, adapting them to individual preferences and financial possibilities, while offering extensive functions of purchasing data analysis.

Technologies and libraries used

• Java
• Maven
• Lombok
• JUnit
• AssertJ

Jacoco Coverage

Required files

• Clients file with pattern:

  NAME;SURNAME;AGE;CASH;PREFERENCES

• Preferences with pattern:

  ID CATEGORY

• Products with pattern: ID:NAME;QUANTITY;PRICE;CATEGORY

Description

1. Input Files:

• clients.csv:

File containing customer data. Each line contains data of one customer in the following format: NAME, SURNAME, AGE, CASH, PREFERENCES. Preferences are numbers designating product categories that the customer wants to buy in a specific order.

• preferences.csv:

A file containing a mapping of numbers to product category names that represent customer preferences. Line format: ID CATEGORY_NAME.

• products.csv:

File with a list of available products, in the format: ID;NAME;QUANTITY_IN_STOCK;UNIT_PRICE;CATEGORY.

2. Classes:

   • Client class:

     Fields: name, surname, age, cash, preferences. Preferences determine what products a customer wants to buy and in what order.

   • Product Class:

     Fields: name, quantity in stock, unit price, category.

   • Purchase Class:

     Fields: product, quantity.

   • Shop class:

   Fields: customer list, product list, preference mapping.

   Methods: loading data from files, purchasing simulation, generating statements.

3. Purchasing Simulation Process:

• Loading Data:

  • Customers, products and preferences are loaded from the appropriate text files.

• Customer Purchases:

  • Products are selected for purchase for each customer, based on their preferences and available budget.
  • Customers buy products according to their preferences (prioritized in order of preference).
  • Customers choose products with the best price-to-quantity ratio.

• Listings:

  • The customer who purchased the most products.
  • The customer who spent the most money.
  • Product breakdown: How many times each product was purchased.
  • The most frequently and least frequently chosen products.
  • Product category popularity, sorted in descending order.

4. Additional Functionalities:

• Customer who bought the most products: Analyze customer purchase data to find the customer who bought the most products.
• Customer who spent the most money: Similar analysis to find the customer who spent the most money.
• Product Summary: Information about how many times each product was purchased by all customers.
• Product Category Popularity: Count how often products in each category were chosen and sort this data descending by popularity.