Task

PubMedImporter addresses a practical need: PubMedImporter is a PHP-based tool designed to simplify the process of importing and managing medical research articles from PubMed. It is a WordPress plugin that allows users to query a set of articles via API and keywords, and then, if necessary, add them directly to their blog.

The project is part of commercial development, has been completed, and is currently in use. It is related to services: Full-stack web applications and dashboards.

The case demonstrates an approach to tasks in the field of "Full-stack web applications and dashboards": from task definition to delivery with a clear module structure.

Before starting, we established readiness criteria: a clear first screen, predictable form errors, and the ability to make improvements without rewriting half of the codebase.

Solution

A closed commercial tool has been implemented: the interface and logic are tailored to everyday user scenarios, without unnecessary screens.

The scenarios are designed so that the main actions fit within one or two screens: fewer switches, fewer input errors. Navigation and field labels are aligned with familiar patterns—users do not need to "learn the interface."

Particular attention is given to loading states and empty lists: skeleton/spinner where data arrives asynchronously, and clear empty-state texts instead of an empty table.

Architecture and stack

Server and data: PHP.

Language distribution in the repository: PHP (96%), CSS (2.4%), JavaScript (1.6%).

Layers are separated so that the UI does not know the details of transport: API/storage adapters, domain types, presentation components. This simplifies backend replacement and targeted UX adjustments.

Key features

• PHP is used in product logic: it reduces the amount of custom code and speeds up the addition of new screens.

Additionally:

• Integration and use of PHP in product logic and interface.
• User input validation and clear error messages.
• Responsive design for desktop and mobile.

Result

The project has been brought to a working state: the team/user receives a stable tool instead of manual tables and correspondence. Time for routine operations has been reduced due to automation in the interface.

The code is closed per client requirements; architectural solutions and stack are described on this page for transparency of expertise and SEO.

What I would improve

The next step would be observability (logs/metrics), regression auto-tests, and API documentation for integrators. For high-load scenarios—profiling bottlenecks and caching reference data.