Introduction — Aquilia Documentation
Comprehensive guide and documentation for Introduction in the Aquilia framework. View API reference, examples, and implementation patterns.
import from 'lucide-react' const RequestLifecycle = () => , , , , , , ] return ( ))} ) } const FEATURE_SPINE_DATA = [ , right: }, , right: }, , right: }, , right: }, , right: }, , right: }, , right: }, , right: }, , right: }, , right: } ] function FeatureArchitectureVisualizer( : ) onMouseLeave= `} > • setHoveredId(row.right.id)} onMouseLeave= `} > • ); })} ); } v · " " Aquilia Framework Production-ready async Python web framework Stop writing routing, config, and deployment boilerplate. Focus only on business logic. Quick Start Architecture What is Aquilia? An async-first Python framework built on an auto-discovery architecture. It ships a built-in ORM, production-ready infrastructure generation, and ML deployment — removing the friction of wiring components together manually. Who is it for? Teams building production APIs who want clean architecture, auto-discovery, and built-in deployment tooling — without the wiring boilerplate of microframeworks or the bloat of legacy monoliths. Core Philosophy Aquilia shifts framework architecture from manual configuration boilerplate to declarative autodiscovery. ✕ Legacy Wiring Manual configuration of components, services, and routing topologies. Wiring boilerplate accumulates as the codebase grows. ✓ Auto-Discovery Programmatic registry structures the module and DI graph automatically. Sensible defaults eliminate setup overhead. ✕ Manual Infra Deployment infrastructure, Dockerfiles, and container charts are treated as an afterthought left to separate operations. ✓ Infra Generation First-class generators build production Render, Docker, and Kubernetes configurations natively from the code topology. ✕ Fragile MLOps Machine Learning serving, metrics, and experimental tracking require building a separate, disjointed middleware stack. ✓ Integrated ML Integrated MLOps serving, experimental tracking, and pipeline plugins are supported out of the box by the runtime. ✕ Boilerplate Overhead Writing repetitive boilerplate code for session storage, clearance guards, cache invalidation, and task queue workers. ✓ Unified Modules Unified batteries-included modules cover clearance access levels, multi-layer caching, mail, and worker pools. Feature Architecture Click on any node in the tactical radar engine schema to inspect its subsystem mapping, declarative syntax, and source code files. Architecture at a Glance Aquilia boots using a programmatic entrypoint that loads the workspace, resolves integrations, auto-discovers manifests, and instantiates the ASGI application: app.py Once booted, inbound requests flow through a deterministic pipeline: Minimal Example A complete Aquilia application with a modern manifest-driven structure, typed database integration, pure-Python ORM model, validation contract, service, and controller: workspace.py modules/core/manifest.py modules/core/contracts.py modules/core/controllers.py Response: users = await self.user_service.list_users() return Response.json( ) @POST("/") async def create_user(self, ctx: RequestCtx) -> Response: contract = UserCreateContract(data=await ctx.json()) await contract.is_sealed_async(raise_fault=True) user = await self.user_service.create_user(contract.validated_data) return Response.json(user.to_dict(), status=201)`} language="python" /> modules/core/services.py list[User]: return await User.objects.all() async def create_user(self, data: dict) -> User: return await User.objects.create( name=data["name"], email=data["email"], )`} language="python" /> modules/core/models.py Run it: aq run or python -m aquilia.cli run — starts the development server with auto-reload on port 8000. Subsystem Map Aquilia is organized into cohesive subsystems, each covered in depth by this documentation: Subsystem Package Key Classes ))} Where to Go Next , , , , , , ].map((link, i) => ( ))} )
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