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Project description
TLDR
- A versatile framework for building FastAPI applications with dynamic model generation.
- Easily define your data models and let the framework auto-generate corresponding CRUD API routes.
- Make use of async database operations for improved performance.
- Tailor to a wide range of applications from simple CRUD APIs to complex data management systems.
Overview
This project is a robust and scalable FastAPI framework designed for efficient data management and API development. Leveraging the power of Python's async capabilities and SQLAlchemy for database interactions, this framework offers a versatile approach to creating APIs with dynamic model generation and flexible storage solutions.
Key Features
- Dynamic API Route Generation: Automatically generates API routes based on configurable entities.
- Modular Storage Management: Integrates with PostgreSQL, ensuring efficient data storage and retrieval.
- Type-Safe Operations: Utilizes Pydantic for rigorous data validation and type checking.
- Asynchronous Support: Leverages Python's async features for non-blocking database operations.
- Scalable Architecture: Designed to accommodate growing data needs and additional functionalities.
Use Cases
- Rapid API Development: Streamlines the process of creating and deploying APIs for data-intensive applications.
- Customizable Data Models: Tailor data models and API endpoints to specific business requirements.
- Data Management: Ideal for applications requiring robust database operations, including CRMs, e-commerce platforms, and content management systems.
Getting Started
To get started with this framework:
-
Installation: Clone the repository and install dependencies using Poetry.
git clone <repository-url> cd <repository-name> poetry install
-
Configuration: Set up your database credentials and other configurations in
examples/config.py. -
Run the Application:
poetry run python examples/app.py
Examples
Defining a Configurable Entity:
# examples/config.py
from dyapi.entities.config import Config, ConfigField
configs: list[Config] = [
Config(
name="Entity1",
api_tags=["Entity1"],
fields=[
ConfigField(name="field_1", type=int, location="path"),
# Add more fields as needed
],
),
]
Starting the Server: Run the server with Uvicorn:
poetry run uvicorn examples.app:application --reload
Contributing
We welcome contributions! Please read our contributing guidelines for instructions on how to submit pull requests.
License
This project is licensed under MIT License.
For more detailed information, refer to the documentation. Happy coding!
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