Task

Med Tracker Bot addresses a practical task: a Telegram bot for medication reminders and tracking intake. Asynchronous Python, state management, and careful logging.

This is a personal learning project (in active development) where specific patterns and tools were practiced without unnecessary overhead.

The case demonstrates an approach to tasks in the area of "Chatbots and process automation": 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 enhance without rewriting half of the codebase.

Solution

A learning yet fully functional implementation has been made, focusing on code readability and reproducible builds.

The scenarios are designed so that the main actions fit into one or two screens: fewer switches, fewer input errors. Navigation and field labels are aligned with familiar patterns — the user doesn’t need to "learn the interface".

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

Architecture and stack

Server and data: Python.

Infrastructure and utilities: Telegram, asyncio.

Language distribution in the repository: Python (90%), Shell (9.8%), Dockerfile (0.2%).

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 tweaks.

Key features

• Python — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• Telegram — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• asyncio — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.

Additionally:

• Integration and use of Python in product logic and interface.
• Integration and use of Telegram in product logic and interface.
• Integration and use of asyncio in product logic and interface.

Result

The MVP already covers the key scenario; next — expanding reporting, tests, and monitoring.

The source code is open: https://github.com/astropsy999/med-tracker-bot — you can evaluate the module structure and commit style.

What I would improve

The next step is observability (logs/metrics), regression tests, and API documentation for integrators. For high-load scenarios — profiling bottlenecks and caching references.