agentic-studio

File	Purpose
models.py	Defines the data model for the todo items using SQLAlchemy ORM.
schemas.py	Contains Pydantic schemas for validating request and response data.
main.py	The FastAPI application, defining routes and business logic.
pyproject.toml	Project metadata and dependencies.
test_main.py	Unit tests for the FastAPI endpoints.
Dockerfile	Docker configuration to build and run the application.

Quick Start

git clone cd project uv sync uv run uvicorn main:app --reload

Docker

docker build -t todo-sovellus-fastapi---sqlite--crud-endpointit-ja-testit . docker run -p 8000:8000 todo-sovellus-fastapi---sqlite--crud-endpointit-ja-testit

API Endpoints

Method	Path	Description
POST	/todos/	Create a new todo item.
GET	/todos/	List all todos or filter by status.
GET	/todos/{id}	Retrieve a specific todo item by ID.
PUT	/todos/{id}	Update an existing todo item.
DELETE	/todos/{id}	Delete a todo item.

Architecture

The project follows a clean separation of concerns:

models.py: Defines the data model using SQLAlchemy ORM.
schemas.py: Contains Pydantic models for data validation and serialization.
main.py: Implements FastAPI routes, business logic, and database interactions.

This logical structure makes it easy to understand and maintain each component independently.

Risk Assessment

Severity	Issue
LOW	The project uses parameterized queries in the SQLAlchemy ORM which helps prevent SQL injection. However, input validation is minimal (e.g., no checks for `due_date` format).
MEDIUM	Error handling and database connection management are basic but adequate. Database connections are managed via context managers, which ensures proper closure of sessions.
LOW	The project uses consistent naming conventions for variables and functions, making the code easy to understand. However, there's room for improving documentation around API endpoints and models.

Overall assessment: "SHIP IT"