This project allows customers and clients to buy and sell goods while having the process at hand and giving them the control over the shipment, payment status and delivery state of the product.

It shows insights about the product sales using Machine Learning algorithms and charts for displaying information for taking action on marketing, management and logistics of their services.

Here Django and Bootstrap were used for showing the information using Django Templates. Also a combination of exposed REST APIs was used for displaying the information in async manner and to have results fast. A PostgreSQL database was employed as the persistence layer.

For the front end, jQuery AJAX requests are made to obtain the data and display them in charts and tables. It also handles the interaction for buying/selling products, add them in a shopping cart, and display the insights information.

There are pages that are available for type of user (admin, customer, client) and shows different optionsp according to their role and permissions.

This application is divided in three sections: Admin users have the privileges for editing the state of the shipment, the payment information, manage other users, revoke permissions, etc.; Customers can upload new products, change the state of the shipment, payment information, stock, and receive insights of their sales; Clients are the end consumers that buy the products from the customers, and have the ability to check the state of the shipment and payment. They can also receive notifications when their products have been updated on the application.

One of the features it offers is a Machine Learning algorithm for analyzing the sales data and give the insights to the sellers, so they can have knowledge of the stock to have at certain quarters of the year, plan marketing campaigns for their products. This feature was made using Scikit-learn and Pandas.