# Query Parameter Models { #query-parameter-models }

If you have a group of **query parameters** that are related, 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`. 🤓

///

import java.util.Arrays;

/**
 * Entity class representing a request parameter with a name and associated values.
 * This class encapsulates HTTP request parameters that can have multiple values,
 * such as query parameters, form parameters, or other request-related data.
 *
 * <p>This class is immutable and thread-safe. Once created, the parameter name
 * and values cannot be modified.</p>
 *
 */
public class RequestParameter {

///

## Request body + path parameters { #request-body-path-parameters }

You can declare path parameters and request body at the same time.

**FastAPI** will recognize that the function parameters that match path parameters should be **taken from the path**, and that function parameters that are declared to be Pydantic models should be **taken from the request body**.

{* ../../docs_src/body/tutorial002_py310.py *}

## Request body + parámetros de path

Puedes declarar parámetros de path y request body al mismo tiempo.

**FastAPI** reconocerá que los parámetros de función que coinciden con los parámetros de path deben ser **tomados del path**, y que los parámetros de función que se declaran como modelos de Pydantic deben ser **tomados del request body**.

///

### Declare a *path parameter* { #declare-a-path-parameter }

Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`):

{* ../../docs_src/path_params/tutorial005.py hl[16] *}

### Check the docs { #check-the-docs }

Because the available values for the *path parameter* are predefined, the interactive docs can show them nicely:

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** **extraerá** los datos para **cada campo** de los **parámetros query** en el request y te proporcionará el modelo de Pydantic que definiste.

## Revisa la Documentación

Puedes ver los parámetros query en la UI de documentación en `/docs`:

    /**
     * Add the created action message for the key 'constraints.Size.message' with parameters.
     * <pre>
     * message: The size of {item} must be between {min} and {max}.
     * </pre>
     * @param property The property name for the message. (NotNull)
     * @param min The parameter min for message. (NotNull)
     * @param max The parameter max for message. (NotNull)
     * @return this. (NotNull)
     */

# Header Parameter Models { #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`. 🤓

///

   * the dummy value of a constructor or method parameter is unknown.
   */
  @VisibleForTesting
  static final class ParameterNotInstantiableException extends Exception {
    public ParameterNotInstantiableException(Parameter parameter) {
      super(
          "Cannot determine value for parameter "
              + parameter
              + " of "
              + parameter.getDeclaringInvokable());
    }
  }

    }
  }

  /*
   * Preconditions.checkNotNull is *intended* for performing eager null checks on parameters that a
   * nullness checker can already "prove" are non-null. That means that the first parameter to
   * checkNotNull *should* be annotated to require it to be non-null.
   *
   * However, for a variety of reasons, Google developers have written a ton of code over the past