Task Management API

Versión en español

REST API for managing tasks assigned to users. Built with FastAPI and JSON file persistence.

Features

• Full CRUD for tasks: create, list, retrieve, update, delete.
• Automatic request validation via Pydantic.
• Interactive API docs at /docs (Swagger UI).
• Configurable persistence path via environment variable.

Installation

All commands must be run from the project root directory (the folder that contains requirements.txt). All commands assume a Bash-compatible shell. On Windows, use Git Bash (not CMD or PowerShell).

python -m venv venv

Activate the virtual environment:

Terminal	Command
Git Bash / WSL	source venv/Scripts/activate
macOS / Linux	source venv/bin/activate

If activation succeeded, your prompt will show (venv). If it does not appear, the environment is not active and commands will use the system Python.

pip install -r requirements.txt
cp .env.example .env

Running

uvicorn src.entregable1.main:app --reload

The API is available at http://127.0.0.1:8000.

Testing

Run the test suite with coverage:

pytest tests/ -v --cov=src/entregable1 --cov-report=term-missing

Usage

Swagger UI

Open http://127.0.0.1:8000/docs in your browser.

1. Expand an endpoint and click Try it out.
2. Fill in the request body or parameters and click Execute.
3. The response (status code + JSON body) appears below.

Suggested sequence to exercise the full CRUD:

• POST /tasks/ — create a task.
• GET /tasks/ — confirm it appears in the list.
• GET /tasks/{task_id} — retrieve the task by id.
• PUT /tasks/{task_id} — update fields (e.g. change status to "completada").
• DELETE /tasks/{task_id} — delete it.
• GET /tasks/{task_id} — confirm it returns 404.

curl

# Create a task — note the returned id for the commands below
curl -s -X POST http://127.0.0.1:8000/tasks/ \
  -H "Content-Type: application/json" \
  -d '{"title":"My task","description":"Details","priority":"media","effort_hours":2.5,"status":"pendiente","assigned_to":"Ana"}'

# List all tasks
curl -s http://127.0.0.1:8000/tasks/

# Get a specific task (replace <id> with the actual id)
curl -s http://127.0.0.1:8000/tasks/<id>

# Update a task
curl -s -X PUT http://127.0.0.1:8000/tasks/<id> \
  -H "Content-Type: application/json" \
  -d '{"title":"Updated task","description":"New details","priority":"alta","effort_hours":4.0,"status":"completada","assigned_to":"Ana"}'

# Delete a task
curl -s -X DELETE http://127.0.0.1:8000/tasks/<id>

# Confirm deletion returns 404
curl -s -o /dev/null -w "%{http_code}" http://127.0.0.1:8000/tasks/<id>

Task fields

Field	Type	Values
title	string	any
description	string	any
priority	string	baja · media · alta · bloqueante
effort_hours	float	estimated hours
status	string	pendiente · en progreso · en revisión · completada
assigned_to	string	assignee name

Roadmap

#	Deliverable	Summary
1	REST API ✅	FastAPI + JSON persistence. CRUD endpoints for Task.
2	AI Endpoints	LLM-powered endpoints: description generation, effort estimation, risk audit (Azure OpenAI / Anthropic).
3	UI + Database	Jinja2 interface, MySQL via SQLAlchemy, user story generation and task breakdown.
4	Docker + CI/CD	Dockerfile, GitHub Actions pipeline, image pushed to Docker Hub.
5	Cloud Deployment	Docker Compose, Azure Container Registry, Azure Container Apps, full CI/CD pipeline.

Distribution

Files included in the delivery package (m2_proyecto_ignacio_gros.zip):

Path	Description
src/	Application source code
tests/	Test suite
requirements.txt	Pinned dependencies
.env.example	Environment variables template
pytest.ini	pytest configuration
README.md	English documentation
README_es.md	Spanish documentation

Stack

• Framework: FastAPI
• Validation: Pydantic
• Testing: pytest
• Database (phase 3+): MySQL + SQLAlchemy
• AI (phase 2+): Azure OpenAI / Anthropic
• Infra (phase 4+): Docker, GitHub Actions, Azure