Voici un petit bout de cette histoire.

## Alternatives

Je crée des API avec des exigences complexes depuis plusieurs années (Machine Learning, systèmes distribués, jobs asynchrones, bases de données NoSQL, etc), en dirigeant plusieurs équipes de développeurs.

Dans ce cadre, j'ai dû étudier, tester et utiliser de nombreuses alternatives.

* Based on Python type hints.
* Validation and documentation from these types.
* Dependency Injection system.

It doesn't use a data validation, serialization and documentation third-party library like Pydantic, it has its own. So, these data type definitions would not be reusable as easily.

    dependency.

    Read more about it in the
    [FastAPI docs for HTTP Basic Auth](https://fastapi.tiangolo.com/advanced/security/http-basic-auth/).
    """

    username: Annotated[str, Doc("The HTTP Basic username.")]
    password: Annotated[str, Doc("The HTTP Basic password.")]


class HTTPAuthorizationCredentials(BaseModel):
    """
    The HTTP authorization credentials in the result of using `HTTPBearer` or

# Génération de projets - Modèle

Vous pouvez utiliser un générateur de projet pour commencer, qui réalisera pour vous la mise en place de bases côté architecture globale, sécurité, base de données et premières routes d'API.

Un générateur de projet fera toujours une mise en place très subjective que vous devriez modifier et adapter suivant vos besoins, mais cela reste un bon point de départ pour vos projets.

## Full Stack FastAPI PostgreSQL

    client_id: optional string. OAuth2 recommends sending the client_id and client_secret (if any)
        using HTTP Basic auth, as: client_id:client_secret
    client_secret: optional string. OAuth2 recommends sending the client_id and client_secret (if any)
        using HTTP Basic auth, as: client_id:client_secret
    """

    def __init__(
        self,
        grant_type: Annotated[
            str,

    The new docs will include Pydantic v2 and will use <a href="https://sqlmodel.tiangolo.com/" class="external-link" target="_blank">SQLModel</a> (which is also based on SQLAlchemy) once it is updated to use Pydantic v2 as well.

You can use the same dependency overrides from [Testing Dependencies with Overrides](testing-dependencies.md){.internal-link target=_blank} to alter a database for testing.

    It helps a lot during **development**, but you **shouldn't** use it in **production**.

## Hypercorn with Trio

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker

SQLALCHEMY_DATABASE_URL = "sqlite:///./sql_app.db"
# SQLALCHEMY_DATABASE_URL = "postgresql://user:password@postgresserver/db"

engine = create_engine(
    SQLALCHEMY_DATABASE_URL, connect_args={"check_same_thread": False}
)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

# GraphQL

As **FastAPI** is based on the **ASGI** standard, it's very easy to integrate any **GraphQL** library also compatible with ASGI.

You can combine normal FastAPI *path operations* with GraphQL on the same application.

!!! tip
    **GraphQL** solves some very specific use cases.

    It has **advantages** and **disadvantages** when compared to common **web APIs**.

### Bảo mật và xác thực

Bảo mật và xác thực đã tích hợp mà không làm tổn hại tới cơ sở dữ liệu hoặc data models.

Tất cả cơ chế bảo mật định nghĩa trong OpenAPI, bao gồm:

* HTTP Basic.
* **OAuth2** (với **JWT tokens**). Xem hướng dẫn [OAuth2 with JWT](tutorial/security/oauth2-jwt.md){.internal-link target=_blank}.
* API keys in:
    * Headers.
    * Các tham số trong query string.
    * Cookies, etc.