Model-driven backend platform for FastAPI: REST + GraphQL + search + version history + admin UI from a single msgspec.Struct
Project description
Model-driven backend platform for FastAPI
Generate REST APIs, GraphQL, search, version history, and an admin UI from a single Python model.
Renamed from
autocrudtospecstar(v0.10.0). The old name still installs as a deprecation shim that redirects everyautocrud[.X]import tospecstar[.X]. New projects shouldpip install specstar. See the migration guide.
Focus on business logic, not infrastructure.
⭐ If you find this project useful, consider giving it a star.
Why SpecStar
Modern backend development repeatedly rebuilds the same infrastructure:
- CRUD APIs
- validation
- search and filtering
- version history
- permissions
- background jobs
- admin tools
Most of this code is not business logic.
SpecStar eliminates this repetition by using a model-driven architecture.
Define your model once, and the framework generates the rest.
Example
Define a resource model:
from msgspec import Struct
class User(Struct):
name: str
email: str
Register the model:
from fastapi import FastAPI
from specstar import spec
app = FastAPI()
spec.add_model(User)
spec.apply(app)
Start the server:
uvicorn main:app
Optional startup tuning:
export SPECSTAR_DEFAULT_QUERY_LIMIT=1000
This controls the default page size for list endpoints. Per-request limit
still overrides it.
You now automatically get:
POST /users
GET /users
GET /users/{id}
PUT /users/{id}
PATCH /users/{id}
DELETE /users/{id}
OpenAPI documentation is generated automatically.
Architecture
graph TD
FastAPI --> SpecStar
SpecStar --> ResourceManager
ResourceManager --> Storage
Storage --> MetaStore
Storage --> RevisionStore
Storage --> BlobStore
SpecStar --> REST_API
SpecStar --> GraphQL_API
SpecStar --> UI_Generator
Core Features
Model-driven APIs
SpecStar generates APIs directly from Python models.
Model
↓
REST API
GraphQL API
OpenAPI
Versioned resources
Every resource maintains immutable revision history.
Resource
├── r1
├── r2
└── r3
Advantages:
- audit history
- rollback
- draft workflows
- debugging
Built-in search
Search operates on indexed metadata instead of scanning full resource payloads.
QueryBuilder
↓
ResourceManager.search()
↓
MetaStore.search()
Background jobs
Jobs are modeled as resources.
create()
↓
message_queue.put(resource_id)
Workers process jobs through:
ResourceManager.start_consume()
Storage abstraction
SpecStar supports multiple storage backends.
| Backend | Meta | Revision | Blob |
|---|---|---|---|
| Memory | memory | memory | memory |
| Disk | SQLite | files | filesystem |
| S3 | SQLite | S3 | S3 |
| Postgres | PostgreSQL | S3 | S3 |
You can also implement custom storage systems.
UI generation
SpecStar can generate a web interface directly from the API.
API
↓
UI generator
↓
admin dashboard
This allows rapid creation of internal tools.
Comparison
| Feature | SpecStar | Hasura | Django |
|---|---|---|---|
| REST API | ✅ | ❌ | ✅ |
| GraphQL | ✅ | ✅ | ⚠️ |
| Version history | ✅ | ❌ | ❌ |
| Search engine | ✅ | SQL | ORM |
| Storage | pluggable | PostgreSQL | relational |
| Background jobs | built-in | external | external |
| UI generation | ✅ | console | admin |
Quickstart
Install:
pip install specstar
Run your app:
uvicorn main:app
Open:
http://localhost:8000/docs
Documentation
Full documentation:
https://hychou0515.github.io/specstar/
Example use cases
SpecStar works well for:
- internal tools
- content systems
- configuration management
- job processing systems
- administrative APIs
- workflow management systems
License
MIT
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