Sebastián Ramírez <******@****.***> 1714435394 -0700

from pydantic import BaseModel


class User(BaseModel):
    id: int
    name: str = "John Doe"
    signup_ts: Union[datetime, None] = None
    friends: List[int] = []


external_data = {
    "id": "123",
    "signup_ts": "2017-06-01 12:22",
    "friends": [1, "2", b"3"],
}
user = User(**external_data)
print(user)

    try:
        return ModelField(**kwargs)  # type: ignore[arg-type]
    except (RuntimeError, PydanticSchemaGenerationError):
        raise fastapi.exceptions.FastAPIError(
            "Invalid args for response field! Hint: "
            f"check that {type_} is a valid Pydantic field type. "
            "If you are using a return type annotation that is not a valid Pydantic "

                }
            ]
        }
    )


def test_query_int_query_42():
    response = client.get("/query/int?query=42")
    assert response.status_code == 200
    assert response.json() == "foo bar 42"


def test_query_int_query_42_5():
    response = client.get("/query/int?query=42.5")
    assert response.status_code == 422
    assert response.json() == IsDict(
        {

        gt: Optional[float] = None,
        ge: Optional[float] = None,
        lt: Optional[float] = None,
        le: Optional[float] = None,
        min_length: Optional[int] = None,
        max_length: Optional[int] = None,
        pattern: Optional[str] = None,
        regex: Annotated[
            Optional[str],
            deprecated(

        if: steps.cache.outputs.cache-hit != 'true'
        run: pip install -r requirements-tests.txt
      - name: Install Pydantic v2
        run: pip install "pydantic>=2.0.2,<3.0.0"
      - name: Lint
        run: bash scripts/lint.sh

  test:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version:
          - "3.12"
          - "3.11"
          - "3.10"
          - "3.9"
          - "3.8"

            """
        ),
    ] = None,
    min_length: Annotated[
        Optional[int],
        Doc(
            """
            Minimum length for strings.
            """
        ),
    ] = None,
    max_length: Annotated[
        Optional[int],
        Doc(
            """
            Maximum length for strings.
            """
        ),
    ] = None,

@pytest.fixture(name="client")
def get_client():
    app = FastAPI()

    from pydantic import BaseModel, computed_field

    class Rectangle(BaseModel):
        width: int
        length: int

        @computed_field
        @property
        def area(self) -> int:
            return self.width * self.length

    @app.get("/")
    def read_root() -> Rectangle:
        return Rectangle(width=3, length=4)

```JSON
{
  "detail": [
    {
      "type": "int_parsing",
      "loc": [
        "path",
        "item_id"
      ],
      "msg": "Input should be a valid integer, unable to parse string as an integer",
      "input": "foo",
      "url": "https://errors.pydantic.dev/2.1/v/int_parsing"
    }
  ]
}
```

because the path parameter `item_id` had a value of `"foo"`, which is not an `int`.

    ```

=== "Python 3.9 і вище"

    ```Python hl_lines="1"
    {!> ../../../docs_src/python_types/tutorial007_py39.py!}
    ```

Це означає:

* Змінна `items_t` це `tuple` з 3 елементами, `int`, ще `int`, та `str`.
* Змінна `items_s` це `set`, і кожен його елемент типу `bytes`.

#### Dict (словник)

Щоб оголосити `dict`, вам потрібно передати 2 параметри типу, розділені комами.