Showcase: Scheduled E-commerce Analytics CLI Tool (API + SQLite + Logging)

#What My Project Does

This is a CLI-based automation system that:

Fetches product data from an external API

Stores structured data in SQLite

Generates category-level statistics

Identifies expensive products dynamically

Creates automated text reports

Supports scheduled daily execution

Uses structured logging for reliability

It is built as a command-line tool using argparse and supports:

--fetch

--stats

--expensive

--report

--schedule

#Target Audience

This project is mainly a backend automation practice project.

It is not intended for production use, but it is designed to simulate a lightweight automation workflow system for small e-commerce teams or learning purposes.

#Comparison

Unlike simple API scripts, this project integrates:

Persistent database storage

CLI argument parsing

Logging system

Scheduled background execution

Structured reporting

It focuses on building a small automation system rather than a single standalone script.

#GitHub repository:

ShukurluFakhri-12/Ecomm-Pulse-Analytics: An automated e-commerce data tracking and weekly reporting system built with Python and SQLite. Features modular data ingestion and persistent storage.

I would appreciate feedback on:

Code structure, database handling improvements, making this more production-ready