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FastAPI Data Service

Planned

A production-ready REST API built on top of the data pipeline database. Supports filtering, pagination, and aggregation endpoints with full Pydantic validation and Swagger docs. Dockerized for deployment.

PythonFastAPISQLAlchemyPydanticDockerREST API

Overview

A FastAPI service that exposes the pipeline database through a clean, validated REST API — the bridge between the data layer and anything that consumes it.

Problem

Data sitting in a database is only useful if something can query it. This project builds the API layer that makes the data accessible to frontends, agents, and ML models.

Approach

FastAPI with SQLAlchemy ORM, Pydantic v2 schemas for request/response validation, and a dependency-injected database session pattern. Every endpoint is documented automatically via Swagger UI.

Tech Stack

  • FastAPI — async API framework
  • SQLAlchemy — ORM with session management
  • Pydantic v2 — data validation
  • Uvicorn — ASGI server
  • Docker — containerized deployment

Key Decisions

  • Dependency injection for DB sessions (get_db) ensures sessions are always closed — no leaks
  • Pagination on all list endpoints by default, not as an afterthought
  • Separated CRUD logic from route handlers for testability

What I’d Do Differently

Add JWT authentication from the start. Even for a portfolio project, showing auth-aware API design signals production readiness.