Automatizando a busca de ofertas online com Selenium e Python

Abstract

This academic paper discusses the importance and consequences of automation in searching for online deals on e-commerce platforms using Selenium and Python. In today's world, characterized by a vast availability of data on the internet and intense competition in the digital market, it becomes essential to locate deals efficiently and accurately. Automation emerges as an innovative response to these challenges. This study highlights the gap in programming education, which sometimes fails to address training in e-commerce automation and handling large volumes of web data, resulting in a lack of critical skills for the market. By demonstrating how Python scripts, using the Selenium library, can streamline site navigation, collect product data, and filter it, the article not only proposes an effective methodology but also emphasizes the need to include such competencies in educational programs for developers. Additionally, it addresses the challenges of working with dynamic data and adapting to different e-commerce site layouts, promoting solutions and underscoring the importance of a flexible and up-to-date programming education. Thus, this study covers an area of knowledge still underrepresented in the training of programmers and emphasizes the strategic role of automation in repetitive processes in the e-commerce environment, which is constantly evolving.