Security and documentation
JWT, RBAC, exception handling and OpenAPI documentation are selectable from Pro / Startup. Enterprise options include SSO and attribute-based access control.
PYTHON BACKEND GENERATOR
A FastAPI backend, shaped by your schema.
Generate Python APIs with FastAPI routers, validation schemas, services and database models in an editable project.
Python / FastAPI
Architecture you can work with.
FastAPI routers define HTTP endpoints, validation schemas describe inputs and outputs, and services keep application behavior separate from persistence.
Choose FastAPI for a Python application with explicit request and response schemas. SQLAlchemy sessions isolate database work per request. The Python generator also offers a retrieval starter on eligible plans; that optional capability is separate from deterministic backend generation.
Database integration
PostgreSQL and MySQL use SQLAlchemy models and sessions. MongoDB uses a separate database dependency and document persistence path. Choose the database before reviewing the generated models.
REPRESENTATIVE PROJECT
app/
main.py
models/
schemas/
routers/
services/
repositories/
database.py
requirements.txtschemas/customer.py
from pydantic import BaseModel, ConfigDict
class CustomerResponse(BaseModel):
model_config = ConfigDict(from_attributes=True)
id: int
email: strIllustrative excerpt. The full output depends on schema and configuration.
Schema to Python source.
The same structured input, rendered through templates for your selected framework.
schema.sql INPUT
CREATE TABLE customers (
id BIGINT PRIMARY KEY,
email VARCHAR(255) NOT NULL
);
CREATE TABLE orders (
id BIGINT PRIMARY KEY,
customer_id BIGINT REFERENCES customers(id),
total DECIMAL(10, 2) NOT NULL
);SrujanX engineDeterministic by design
- Analyze schema
- Map relationships
- Generate source
- Package project
Python / FastAPI OUTPUT
app/
main.py
models/
schemas/
routers/
services/
repositories/
database.py
requirements.txt Yours to inspect. Yours to extend.
WHAT YOU GET
A foundation, with the pieces connected.
Generate models, data access, a service layer and CRUD endpoints from tables and relationships. Add application-specific business rules to the source you download.
Deployment and operations
Dockerfiles are available from Pro; Team adds Redis caching and tracing. Agency Scale adds Kubernetes manifests, Helm and CI/CD configuration. Review secrets, infrastructure and tests before deploying.
Source you can extend
Single-module projects keep the initial structure straightforward. Eligible plans can separate the contract and implementation into modules within one deployable application.
Read the usage guide →A CLEAR PATH TO SOURCE
Less setup.
More application.
From an existing schema or a structured requirement to a project you control.
- 01
Upload a schema
Start with SQL or describe your requirements. Review the structured schema, tables and relationships.
- 02
Choose your configuration
Select the stack, database and architecture. Add the capabilities available in your plan.
- 03
Generate. Download. Build.
Generate the source, download your project and configure it for your environment. Extend it with your business logic.
SQL / structured schemaSrujanX engineSpring Boot · Node.js · NestJS · Go · Python
Natural-language input is structured before generation. The backend source is generated deterministically.
The current Python stack is FastAPI, with SQLAlchemy for relational databases. It does not generate a Django application.
BUILD WHAT COMES NEXT
Your schema already
defines the backend.
Let SrujanX build the foundations. Keep the source.
Make the application yours.
schema.sql
→ models + relationships
→ services + REST APIs
→ your next application