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Patient Management API

RESTful Healthcare Records System

RESTful API built with FastAPI and Pydantic for managing patient records with automatic BMI calculation and health assessment. Features complete CRUD operations, data validation, sorting capabilities, and interactive Swagger/Redoc documentation. Demonstrates API design, error handling, and clean code practices.

GitHub
Case study snapshot
Role
Full-stack/data builder
Audience
users, reviewers, and hiring teams
Timeline
2025-01
Role
Full-stack/data builder
Audience
users, reviewers, and hiring teams
Date
2025-01
Problem

Why it mattered

Sub-millisecond response times; Complete CRUD operations; Automatic health assessments

Solution

What shipped

RESTful API built with FastAPI and Pydantic for managing patient records with automatic BMI calculation and health assessment. Features complete CRUD operations, data validation, sorting capabilities, and interactive Swagger/Redoc documentation. Demonstrates API design, error handling, and clean code practices.

Impact

Proof signal

Sub-millisecond response times; Complete CRUD operations; Automatic health assessments

< architecture />

System flow

Request Parsing -> Data Validation -> BMI Calculation -> Health Assessment -> JSON Response.

Request Parsing
Data Validation
BMI Calculation
Health Assessment
JSON Response
Visual architecture
01
Request Parsing
02
Data Validation
03
BMI Calculation
04
Health Assessment
05
JSON Response
quality score

Honest maturity snapshot

Code Quality9/10
UI / UX7/10
Scalability7/10
Production Ready8/10
Before

A workflow or idea that needed clearer structure, validation, and delivery.

After

A working product surface with defined features, links, and a reviewable case study.

capabilities

Features

  • FastAPI integrated into the workflow.
  • Pydantic integrated into the workflow.
  • Python integrated into the workflow.
  • JSON integrated into the workflow.
  • Request Parsing stage documented in the delivery flow.
  • Data Validation stage documented in the delivery flow.
tradeoffs

Engineering challenges

  • Keeping the implementation clear enough to explain while still solving the core technical problem.
  • Choosing a scope that could be shipped, tested, and documented.
  • Turning technical work into proof a visitor can evaluate quickly.
proof

Results

  • Sub-millisecond response times; Complete CRUD operations; Automatic health assessments
  • Documented the engineering path and important learnings.
  • Made source code or technical proof available for review.
reflection

What I learned

  • Tradeoff learned: Keeping the implementation clear enough to explain while still solving the core technical problem.
  • Proof learned: Sub-millisecond response times; Complete CRUD operations; Automatic health assessments
  • Next iteration: Add richer screenshots or a narrated demo.
< stack />
FastAPIPydanticPythonJSONUvicorn
< next iteration />

Future improvements

Add richer screenshots or a narrated demo.
Add before/after metrics and usage notes.
Package the project as a reusable template or deployable demo.