# FastAPI and SQLModel for Microservices Development

FastAPI features, combined with its overall developer-friendly nature, make FastAPI a popular choice for building microservices in Python.

[Tutorial](https://sqlmodel.tiangolo.com/tutorial/fastapi/)

Code for Tutorial:

https://github.com/tiangolo/sqlmodel/tree/main/docs_src/tutorial/fastapi

## Topics to Cover

1. https://sqlmodel.tiangolo.com/tutorial/fastapi/simple-hero-api/

2. https://sqlmodel.tiangolo.com/tutorial/fastapi/response-model/

3. https://sqlmodel.tiangolo.com/tutorial/fastapi/multiple-models/

4. https://sqlmodel.tiangolo.com/tutorial/fastapi/read-one/

5. https://sqlmodel.tiangolo.com/tutorial/fastapi/limit-and-offset/

6. https://sqlmodel.tiangolo.com/tutorial/fastapi/update/

7. https://sqlmodel.tiangolo.com/tutorial/fastapi/update-extra-data/

8. https://sqlmodel.tiangolo.com/tutorial/fastapi/delete/

9. https://sqlmodel.tiangolo.com/tutorial/fastapi/session-with-dependency/

10. https://sqlmodel.tiangolo.com/tutorial/fastapi/teams/

11. https://sqlmodel.tiangolo.com/tutorial/fastapi/relationships/

12. https://sqlmodel.tiangolo.com/tutorial/fastapi/tests/


FastAPI is optimized for microservices development. This optimization is evident in several features and design choices inherent to the framework:

1. **Performance**: FastAPI is built on Starlette for the web parts and Pydantic for data validation, which makes it extremely fast. This is essential for microservices, which often need to handle a high volume of requests efficiently.

2. **Asynchronous Support**: FastAPI supports asynchronous request handling, a significant advantage for microservices. This means it can handle IO-bound and high-concurrency operations more efficiently, which is common in microservices architectures dealing with external APIs, databases, or other microservices.

3. **Easy Integration with Other Services**: FastAPI's design makes it straightforward to develop APIs that can communicate with other services, a key aspect of microservice architectures.

4. **Automatic Documentation**: The framework automatically generates documentation (using Swagger UI and ReDoc) for the API. This feature is highly beneficial in a microservices architecture, where maintaining clear and up-to-date documentation for each service is crucial for the overall system's maintainability.

5. **Data Validation and Serialization**: Thanks to Pydantic, FastAPI provides strong support for data validation and serialization, ensuring that data exchanged between microservices is correct and adheres to specified formats and standards.

6. **Containerization and Scalability**: FastAPI fits well into containerized environments (like Docker) and orchestrated by tools like Kubernetes, which are commonly used for deploying and managing microservices.

7. **Independence and Decoupling**: FastAPI allows for the development of services that are independent and loosely coupled. This is a fundamental characteristic of microservices, enabling teams to develop, deploy, and scale services independently.

8. **Community and Ecosystem**: Although relatively new, FastAPI has a rapidly growing community and ecosystem. This is important for microservices development as it often relies on community support, plugins, and integrations.

In summary, FastAPI is optimized for microservices due to its performance, support for asynchronous programming, ease of integration, automatic documentation, and data validation capabilities. It aligns well with the principles of microservices architecture, making it a suitable choice for such projects.



