Supermarket Backend Application

• This project is a backend application for managing stocks, sales, and user purchases in a supermarket. It provides a REST API for various functionalities such as user signup, login, purchase tracking, item management, and more.

Features

• User Signup: Allows users to register with their details.
• Login: Authenticate users and provide access to their accounts.
• Purchase Tracking: Record individual purchase history for each user.
• Item Management: Add, delete, and update items in the product inventory.
• Sales Reporting: Generate daily and weekly sales reports and send them via email.

Technologies Used:

• Python Flask: Backend framework for building REST APIs.
• MySQL Database: Database management system for storing data.
• Schedule: Python library for scheduling tasks.
• SMTP (Simple Mail Transfer Protocol): Protocol for sending emails.

Set up the database:

• Run the provided MySQL script in SQL_queries.txt file to create the necessary tables

Run the application:

• python initiator.py
• Access the API endpoints using a tool like Postman.

Usage

• Use Postman or any API testing tool to interact with the endpoints.
• Register users using the /signup endpoint.
• Login with registered user credentials using the /login endpoint.
• Perform various actions such as purchasing items, managing products, and generating reports.
• Run the email_scheduler.py file for bill generation.

API Endpoints

• /signup: User signup endpoint.
• /login: User login endpoint.
• /store/signup: store user signup endpoint.
• /store/login: store user login endpoint.
• /purchase: Record user purchases.
• /add_item/string:designation: Add items to the product inventory.
• /delete_item/int:item_id/string:designation: Delete items from the product inventory.
• /update_item_rate/int:item_id/string:designation: Update the rate of an item.
• /total_items_purchased: Get total items purchased in a given date range.
• /high_value_users: Get users who purchased items worth more than Rs 1000 in a day.
• /total_sales_shampoo_last_7_days: Get the total sales amount of shampoo in the last 7 days.