I need a small‐to‐mid size web application built with Python 3.x and Django that analyses patient medical records stored in a PostgreSQL database, then turns the insights into clear, interactive visuals and downloadable reports. Core scope • Build the Django backend, including models that capture standard patient information, visit history, diagnostics, medications, and lab results. • Create a secure REST or GraphQL layer so new records can be ingested from our existing EHR feed. • Process the incoming data with Pandas or a comparable library, preparing it for analysis. • Develop dashboards that allow clinicians to explore trends (e.g., vitals over time, medication adherence) using Plotly, Chart.js, or another modern JS charting tool. • Implement one-click PDF/CSV report generation per patient and for cohort summaries. Key requirements – The entire stack must be containerised with Docker so we can deploy to AWS Fargate later. – Role-based access: physicians, nurses, and admin each see only the charts and reports tied to their permissions. – HIPAA compliance on data storage and transmission; please note any libraries you rely on for encryption and audit logging. – Clean, documented code plus a short README that lets my internal dev lead run the project locally with `docker-compose up`. Acceptance criteria 1. Demo site running locally that loads a provided sample dataset of 5,000 anonymised patient records. 2. At least three interactive charts (line, bar, pie) that update when filters change. 3. Downloadable PDF report matches the on-screen view and is generated in under 10 seconds. 4. Unit tests covering critical models, views, and utilities with ≥85 % coverage. Future work could add predictive analytics, so structuring the code for easy extension is a plus, but for this milestone I only need data visualisation and report generation. If you have delivered similar Django analytics portals before, I would love to see a link or screenshot in your bid.