The reliance on traditional, manual assessment processes increasingly challenges the management of programming practicals within higher education institutions. These methods often result in significant delays in evaluation and feedback provision, impacting student learning progression and straining institutional resources, particularly within large cohorts. While various Automated Grading Tools (AGTs) have been developed to mitigate these issues, many possess limitations regarding scalability, infrastructure dependency, and the depth of pedagogical feedback offered. This research addresses these gaps by introducing Py-Grader, a novel web-based automated platform designed to enhance Python programming education. Py-Grader facilitates a time-sensitive, feedback-rich, and interactive learning environment by integrating contemporary technologies. It utilizes Brython for client-side Python script execution, thereby minimizing backend server load during code testing and grading, and employs Codemirror to provide an interactive, IDE-like code editing experience. Evaluation indicates Py-Grader achieves high fidelity (100%) in providing feedback on code analysis and user interface intuitiveness, alongside strong usability (80% ease of navigation) from the student perspective. This paper demonstrates the potential of leveraging modern client-side technologies to revolutionise Python programming assessments’ efficiency, scalability, and pedagogical effectiveness within contemporary higher education management frameworks.