from fastapi import FastAPI
from fastapi.routing import APIRoute
from pydantic import BaseModel


def custom_generate_unique_id(route: APIRoute):
    return f"{route.tags[0]}-{route.name}"


app = FastAPI(generate_unique_id_function=custom_generate_unique_id)


class Item(BaseModel):
    name: str
    price: float


class ResponseMessage(BaseModel):
    message: str


class User(BaseModel):
    username: str

import peewee

from .database import db


class User(peewee.Model):
    email = peewee.CharField(unique=True, index=True)
    hashed_password = peewee.CharField()
    is_active = peewee.BooleanField(default=True)

    class Meta:
        database = db


class Item(peewee.Model):
    title = peewee.CharField(index=True)
    description = peewee.CharField(index=True)
    owner = peewee.ForeignKeyField(User, backref="items")

Pour un exemple plus courant dans la "vie réelle", imaginez une banque.

Jusqu'à récemment, la plupart des banques avaient plusieurs caisses (et banquiers) 👨‍💼👨‍💼👨‍💼👨‍💼 et une unique file d'attente 🕙🕙🕙🕙🕙🕙🕙🕙.

Tous les banquiers faisaient l'intégralité du travail avec chaque client avant de passer au suivant 👨‍💼⏯.

    tags: set[str] = set()


@app.post(
    "/items/",
    response_model=Item,
    summary="Create an item",
    description="Create an item with all the information, name, description, price, tax and a set of unique tags",
)
async def create_item(item: Item):

    tags: set[str] = set()


@app.post(
    "/items/",
    response_model=Item,
    summary="Create an item",
    description="Create an item with all the information, name, description, price, tax and a set of unique tags",
)
async def create_item(item: Item):

from sqlalchemy.orm import relationship

from .database import Base


class User(Base):
    __tablename__ = "users"

    id = Column(Integer, primary_key=True)
    email = Column(String, unique=True, index=True)
    hashed_password = Column(String)
    is_active = Column(Boolean, default=True)

    items = relationship("Item", back_populates="owner")


class Item(Base):
    __tablename__ = "items"

    - **name**: each item must have a name
    - **description**: a long description
    - **price**: required
    - **tax**: if the item doesn't have tax, you can omit this
    - **tags**: a set of unique tag strings for this item
    """

    - **name**: each item must have a name
    - **description**: a long description
    - **price**: required
    - **tax**: if the item doesn't have tax, you can omit this
    - **tags**: a set of unique tag strings for this item
    """

    {!> ../../../docs_src/body_nested_models/tutorial002.py!}
    ```

## Set types

But then we think about it, and realize that tags shouldn't repeat, they would probably be unique strings.

And Python has a special data type for sets of unique items, the `set`.

Then we can declare `tags` as a set of strings:

=== "Python 3.10+"

    ```Python hl_lines="12"

* Data validation.
* Automatic annotation and documentation.

## Other data types

Here are some of the additional data types you can use:

* `UUID`:
    * A standard "Universally Unique Identifier", common as an ID in many databases and systems.
    * In requests and responses will be represented as a `str`.
* `datetime.datetime`:
    * A Python `datetime.datetime`.