import com.google.common.collect.ForwardingMap;
import com.google.common.collect.ForwardingMapEntry;
import com.google.common.collect.ForwardingSet;
import com.google.common.collect.Iterators;
import com.google.common.collect.Maps;
import com.google.errorprone.annotations.CanIgnoreReturnValue;
import com.google.errorprone.annotations.DoNotCall;
import java.util.Iterator;
import java.util.Map;
import java.util.Set;

<img src="/img/tutorial/metadata/image01.png">

## 🗃 🔖

👆 💪 🚮 🌖 🗃 🎏 🔖 ⚙️ 👪 👆 ➡ 🛠️ ⏮️ 🔢 `openapi_tags`.

⚫️ ✊ 📇 ⚗ 1️⃣ 📖 🔠 🔖.

🔠 📖 💪 🔌:

* `name` (**✔**): `str` ⏮️ 🎏 📛 👆 ⚙️ `tags` 🔢 👆 *➡ 🛠️* &amp; `APIRouter`Ⓜ.
* `description`: `str` ⏮️ 📏 📛 🔖. ⚫️ 💪 ✔️ ✍ &amp; 🔜 🎦 🩺 🎚.
* `externalDocs`: `dict` 🔬 🔢 🧾 ⏮️:
    * `description`: `str` ⏮️ 📏 📛 🔢 🩺.
    * `url` (**✔**): `str` ⏮️ 📛 🔢 🧾.

// limitations under the License.

package nodeagent

import (
	"errors"
	"fmt"
	"path/filepath"
	"runtime"
	"sync"

	corev1 "k8s.io/api/core/v1"

	"istio.io/istio/pkg/maps"
	"istio.io/istio/pkg/zdsapi"
)

var ErrPodNotFound = errors.New("netns not provided, but is needed as pod is not in cache")

type PodNetnsCache interface {
	ReadCurrentPodSnapshot() map[string]WorkloadInfo
}

Он принимает список, содержащий один словарь для каждого тега.

Каждый словарь может содержать в себе:

* `name` (**обязательно**): `str`-значение с тем же именем тега, которое вы используете в параметре `tags` в ваших *операциях пути* и `APIRouter`ах.
* `description`: `str`-значение с кратким описанием для тега. Может содержать Markdown и будет отображаться в UI документации.

class Image(BaseModel):
    url: HttpUrl
    name: str


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None
    tags: Set[str] = set()
    images: Union[List[Image], None] = None


class Offer(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    items: List[Item]

			if !stringsHasPrefixFold(v.Name, "x-amz-meta") {
				meta["x-amz-meta-"+v.Name] = v.Value
				continue
			}
			meta[v.Name] = v.Value
		}
		if tags := rreq.OutputLocation.S3.Tagging.String(); tags != "" {
			meta[xhttp.AmzObjectTagging] = tags
		}
		if rreq.OutputLocation.S3.Encryption.EncryptionType != "" {
			meta[xhttp.AmzServerSideEncryption] = xhttp.AmzEncryptionAES
		}
		return ObjectOptions{

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: list[str] = []


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):
    results = {"item_id": item_id, "item": item}

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: set[str] = set()


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):
    results = {"item_id": item_id, "item": item}

# ==============================================================================
TFCI_INSTALLER_WHL_ENABLE=1
TFCI_INSTALLER_WHL_PROJECT_NAME="tensorflow_cpu"
TFCI_INSTALLER_WHL_NIGHTLY_PROJECT_NAME="tf_nightly_cpu"
# Supported wheel tags are stored as strings in TFCI_INSTALLER_WHL_TAGS
# separated by spaces.
TFCI_INSTALLER_WHL_TAGS="cp39-cp39-win_amd64 cp310-cp310-win_amd64 cp311-cp311-win_amd64 cp312-cp312-win_amd64"

        } catch (final Exception e) {
            final String msg = "Failed to index from document: searchWord=" + searchWord//
                    + ", fields=" + Arrays.toString(fields)//
                    + ", tags=" + Arrays.toString(tags)//
                    + ", roles=" + Arrays.toString(roles)//
                    + ", langs=" + Arrays.toString(langs)//
                    + ", num=" + num;
            if (logger.isDebugEnabled()) {