もしあなたがPythonの専門家で、すでに型ヒントについてすべて知っているのであれば、次の章まで読み飛ばしてください。

///

## 動機

簡単な例から始めてみましょう:

```Python
{!../../docs_src/python_types/tutorial001.py!}
```

このプログラムを実行すると以下が出力されます:

```
John Doe
```

この関数は以下のようなことを行います:

* `first_name`と`last_name`を取得します。
* `title()`を用いて、それぞれの最初の文字を大文字に変換します。
* 真ん中にスペースを入れて<abbr title="次から次へと中身を入れて一つにまとめる">連結</abbr>します。

```Python hl_lines="2"

    private final T value;
    private boolean done;

    SingletonIterator(T value) {
      this.value = value;
    }

    @Override
    public boolean hasNext() {
      return !done;
    }

    @Override
    @ParametricNullness
    public T next() {
      if (done) {
        throw new NoSuchElementException();
      }
      done = true;
      return value;
    }
  }

          // that case)
          // Can't represent anything higher, and realistically there probably isn't anything that
          // can actually be done anyway with the supposed 8+ exbibytes of data the source is
          // claiming to have if we get here, so just stop.
          return Optional.of(Long.MAX_VALUE);
        }
      }
      return Optional.of(result);

	if [ $# -ne 0 ]; then
		echo "error on line $1"
		for site in sitea siteb sitec; do
			echo "$site server logs ========="
			cat "/tmp/${site}_1.log"
			echo "==========================="
			cat "/tmp/${site}_2.log"
		done
	fi

	echo "Cleaning up instances of MinIO"
	pkill minio
	pkill -9 minio
	rm -rf /tmp/multisitea
	rm -rf /tmp/multisiteb
	rm -rf /tmp/multisitec
	if [ $# -ne 0 ]; then
		exit $#
	fi
}

catch

    return nullptr;
  }
  TF_DataType dtype;
  absl::Status s = TfDataTypeFormDlDataType(dl_tensor->dtype, &dtype);
  if (!s.ok()) {
    status->status = std::move(s);
    return nullptr;
  }
  int num_dims = dl_tensor->ndim;
  const int64_t* dims = dl_tensor->shape;
  void* data = dl_tensor->data;

  if (dl_tensor->byte_offset != 0) {

 * Implementation detail for the internal structure of {@link Range} instances. Represents a unique
 * way of "cutting" a "number line" (actually of instances of type {@code C}, not necessarily
 * "numbers") into two sections; this can be done below a certain value, above a certain value,
 * below all values or above all values. With this object defined in this way, an interval can
 * always be represented by a pair of {@code Cut} instances.
 *

        "/users/me", headers={"Authorization": f"Bearer {access_token}"}
    )
    assert response.status_code == 200, response.text
    assert response.json() == {
        "username": "johndoe",
        "full_name": "John Doe",
        "email": "******@****.***",
        "disabled": False,
    }


@needs_py310
def test_incorrect_token(client: TestClient):

        "/users/me", headers={"Authorization": f"Bearer {access_token}"}
    )
    assert response.status_code == 200, response.text
    assert response.json() == {
        "username": "johndoe",
        "full_name": "John Doe",
        "email": "******@****.***",
        "disabled": False,
    }


@needs_py39
def test_incorrect_token(client: TestClient):

	bytesData := []struct {
		byteData []byte
	}{
		{generateBytesData(6 * humanize.MiByte)},
	}
	// set of inputs for uploading the objects before tests for downloading is done.
	putObjectInputs := []struct {
		bucketName    string
		objectName    string
		contentLength int64
		textData      []byte
		metaData      map[string]string
	}{

# Un modèle Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```
Qui peuvent ensuite être utilisés comme cela:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

/// info