import org.apache.maven.execution.ProfileActivation;
import org.apache.maven.execution.ProjectActivation;
import org.apache.maven.execution.ProjectDependencyGraph;
import org.apache.maven.graph.GraphBuilder;
import org.apache.maven.graph.ProjectSelector;
import org.apache.maven.internal.impl.DefaultSessionFactory;
import org.apache.maven.internal.impl.InternalMavenSession;
import org.apache.maven.lifecycle.LifecycleExecutionException;

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.google.common.graph;

import static java.lang.annotation.ElementType.FIELD;
import static java.lang.annotation.ElementType.METHOD;
import static java.lang.annotation.ElementType.PARAMETER;
import static java.lang.annotation.RetentionPolicy.CLASS;

 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.repository.metadata;

import org.apache.maven.artifact.ArtifactScopeEnum;

/**
 * metadata graph vertice - just a wrapper around artifact's metadata
 *
 */
@Deprecated
public class MetadataGraphVertex implements Comparable<MetadataGraphVertex> {
    ArtifactMetadata md;

* Llamar a tu función de dependencia ("dependable") con los parámetros correctos.
* Obtener el resultado de tu función.
* Asignar ese resultado al parámetro en tu *path operation function*.

```mermaid
graph TB

common_parameters(["common_parameters"])
read_items["/items/"]
read_users["/users/"]

common_parameters --> read_items
common_parameters --> read_users
```

///

### 同一アプリでの Pydantic v1 と v2 { #pydantic-v1-and-v2-on-the-same-app }

Pydantic v2 のモデルのフィールドに Pydantic v1 のモデルを（またはその逆を）埋め込むことは、Pydantic では「サポートされていません」。

```mermaid
graph TB
    subgraph "❌ Not Supported"
        direction TB
        subgraph V2["Pydantic v2 Model"]
            V1Field["Pydantic v1 Model"]
        end
        subgraph V1["Pydantic v1 Model"]

* Chamar sua dependência ("dependable") com os parâmetros corretos.
* Obter o resultado da função.
* Atribuir esse resultado para o parâmetro em sua *função de operação de rota*.

```mermaid
graph TB

common_parameters(["common_parameters"])
read_items["/items/"]
read_users["/users/"]

common_parameters --> read_items
common_parameters --> read_users
```

### Aynı Uygulamada Pydantic v1 ve v2 { #pydantic-v1-and-v2-on-the-same-app }

Pydantic açısından, alanları (field) Pydantic v1 modelleriyle tanımlanmış bir Pydantic v2 modeli (ya da tersi) kullanmak **desteklenmez**.

```mermaid
graph TB
    subgraph "❌ Not Supported"
        direction TB
        subgraph V2["Pydantic v2 Model"]
            V1Field["Pydantic v1 Model"]
        end
        subgraph V1["Pydantic v1 Model"]

///

### Pydantic v1 і v2 в одній програмі { #pydantic-v1-and-v2-on-the-same-app }

Pydantic не підтримує ситуацію, коли модель Pydantic v2 має власні поля, визначені як моделі Pydantic v1, або навпаки.

```mermaid
graph TB
    subgraph "❌ Not Supported"
        direction TB
        subgraph V2["Pydantic v2 Model"]
            V1Field["Pydantic v1 Model"]
        end
        subgraph V1["Pydantic v1 Model"]

But **FastAPI** will know that it has to solve `query_extractor` first, to pass the results of that to `query_or_cookie_extractor` while calling it.

///

```mermaid
graph TB

query_extractor(["query_extractor"])
query_or_cookie_extractor(["query_or_cookie_extractor"])

read_query["/items/"]

query_extractor --> query_or_cookie_extractor --> read_query
```

Але FastAPI знатиме, що спочатку треба розв'язати `query_extractor`, щоб передати його результат у `query_or_cookie_extractor` під час виклику.

///

```mermaid
graph TB

query_extractor(["query_extractor"])
query_or_cookie_extractor(["query_or_cookie_extractor"])

read_query["/items/"]

query_extractor --> query_or_cookie_extractor --> read_query
```