fraudshield/backend/pyproject.toml
Felipe Domingues 989202648d feat: implement FraudShield MVP — backend API + frontend alerts
Backend (Python 3.12/FastAPI):
- 5 models: Transaction, DetectionRule, FraudAlert, AuditLog, RuleSnapshot
- Rule engine: 4 rule types (amount, location, time, pattern)
- 11 API routes: health, auth, transactions, alerts
- Sync ingestion pipeline with explanation generation
- JWT auth with 3 roles (analyst, admin, senior)
- Seed script with 5 default rules + 50 synthetic transactions

Frontend (React 19/TypeScript/Tailwind):
- Auth: login page, JWT token management, role-based routing
- Alerts: queue with filters, detail panel, decision workflow
- Layout: responsive sidebar, top bar, protected routes
- Full TypeScript, zero ts-ignore, Tailwind CSS

Build: Backend imports clean, Frontend tsc --noEmit passes,
vite build produces 296KB production bundle.
2026-05-12 16:54:03 -03:00

28 lines
643 B
TOML

[project]
name = "fraudshield"
version = "0.1.0"
description = "Motor de detecção de fraudes bancárias"
requires-python = ">=3.12"
dependencies = [
"fastapi[standard]>=0.115.0",
"uvicorn[standard]>=0.32.0",
"sqlalchemy[asyncio]>=2.0.36",
"asyncpg>=0.30.0",
"alembic>=1.14.0",
"pydantic-settings>=2.6.0",
"redis[hiredis]>=5.2.0",
"python-jose[cryptography]>=3.3.0",
"passlib[bcrypt]>=1.7.4",
"structlog>=24.4.0",
]
[project.optional-dependencies]
dev = [
"pytest>=8.3.0",
"pytest-asyncio>=0.24.0",
"httpx>=0.28.0",
]
[tool.pytest.ini_options]
asyncio_mode = "auto"
testpaths = ["tests"]