# Header Parameter Models

If you have a group of related **header parameters**, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

## Header Parameters with a Pydantic Model

# Build state model

The Gradle daemon tracks state for various elements. These are arranged in a hierarchy:

```mermaid
  graph TD

  process["build process"]
  
  session["build session"]
  process --> session
  
  build_tree["build tree"]
  session --> build_tree
  
  build1["root build"]
  build_tree --> build1
  
  project1["root project"]
  build1 --> project1
  
  project2["project"]
  build1 --> project2

Et nous analysons directement ce contenu YAML, puis nous utilisons à nouveau le même modèle Pydantic pour valider le contenu YAML :

```Python hl_lines="26-33"
{!../../docs_src/path_operation_advanced_configuration/tutorial007.py!}
```

/// tip | "Astuce"

Ici, nous réutilisons le même modèle Pydantic.

Mais nous aurions pu tout aussi bien pu le valider d'une autre manière.

 */
package org.apache.maven.model.composition;

import java.util.List;

import org.apache.maven.api.model.DependencyManagement;
import org.apache.maven.api.model.Model;
import org.apache.maven.model.building.ModelBuildingRequest;
import org.apache.maven.model.building.ModelProblemCollector;

/**
 * Handles the import of dependency management from other models into the target model.
 *

from . import models, schemas


def get_user(user_id: int):
    return models.User.filter(models.User.id == user_id).first()


def get_user_by_email(email: str):
    return models.User.filter(models.User.email == email).first()


def get_users(skip: int = 0, limit: int = 100):
    return list(models.User.select().offset(skip).limit(limit))


def create_user(user: schemas.UserCreate):

          <basedir>${project.basedir}/../../api/maven-api-settings</basedir>
          <velocityBasedir>${project.basedir}/../../src/mdo</velocityBasedir>
          <models>
            <model>src/main/mdo/settings.mdo</model>
          </models>
          <params>
            <param>forcedIOModelVersion=1.2.0</param>
            <param>packageModelV3=org.apache.maven.settings</param>

It improves editor support for Pydantic models, with:

* auto-completion
* type checks
* refactoring
* searching
* inspections

///

## Use the model

Inside of the function, you can access all the attributes of the model object directly:

{!> ../../docs_src/body/tutorial002_py310.py!}

## Request body + path parameters

client = TestClient(app)


def test_get_enums_alexnet():
    response = client.get("/models/alexnet")
    assert response.status_code == 200
    assert response.json() == {"model_name": "alexnet", "message": "Deep Learning FTW!"}


def test_get_enums_lenet():
    response = client.get("/models/lenet")
    assert response.status_code == 200

    @Inject
    public DefaultSuperPomProvider(ModelProcessor modelProcessor) {
        this.modelProcessor = modelProcessor;
    }

    @Override
    public Model getSuperModel(String version) {
        return SUPER_MODELS.computeIfAbsent(Objects.requireNonNull(version), v -> {
            String resource = "/org/apache/maven/model/pom-" + v + ".xml";

              <version>1.2.0</version>
              <velocityBasedir>${project.basedir}/../../src/mdo</velocityBasedir>
              <models>
                <model>src/main/mdo/toolchains.mdo</model>
              </models>
              <templates>
                <template>model.vm</template>
              </templates>
              <params>
                <param>packageModelV4=org.apache.maven.api.toolchain</param>