{* ../../docs_src/query_params_str_validations/tutorial015_an_py310.py hl[5,16:19,24] *}

/// info

This is available with Pydantic version 2 or above. 😎

///

video/mpeg                     mpeg mpg mpe     # MPEG Movie File
video/quicktime                qt mov           # Quicktime Movie File
video/x-ms-asf                 asf asx          # Windows Media  File
video/x-msvideo                avi              # AVI Movie File

            logger.log(format("ECL0017", e.getMessage()), e);
        }
    }

    /**
     * Moves the result set to the next position.
     *
     * @param resultSet
     *            The result set. Must not be {@literal null}.
     * @return Whether the result set successfully moved to the next position.
     */
    public static boolean next(final ResultSet resultSet) {

    /**
     * Copies properties from one Bean to another Bean.
     *
     * @param src The source Bean. Must not be {@literal null}.
     * @param dest The destination Bean. Must not be {@literal null}.
     */
    public static void copyBeanToBean(final Object src, final Object dest) {
        copyBeanToBean(src, dest, DEFAULT_OPTIONS);
    }

    /**
     * Copies properties from one Bean to another Bean.

    protected static final int DEFAULT_BUF_SIZE = 4096;

    // ////////////////////////////////////////////////////////////////
    // from InputStream to OutputStream
    //
    /**
     * Copies from an input stream to an output stream.
     * <p>
     * Neither the input stream nor the output stream is closed.
     * </p>
     *
     * @param in the input stream (must not be {@literal null})

{* ../../docs_src/body_nested_models/tutorial007_py310.py hl[7,12,18,21,25] *}

/// info

Notice how `Offer` has a list of `Item`s, which in turn have an optional list of `Image`s

///

## Bodies of pure lists { #bodies-of-pure-lists }

If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models:

```Python

///

## Use cases { #use-cases }

Some use cases include:

* Converting non-JSON request bodies to JSON (e.g. <a href="https://msgpack.org/index.html" class="external-link" target="_blank">`msgpack`</a>).
* Decompressing gzip-compressed request bodies.
* Automatically logging all request bodies.

## Handling custom request body encodings { #handling-custom-request-body-encodings }

import javax.crypto.Cipher;
import javax.crypto.spec.GCMParameterSpec;
import javax.crypto.spec.SecretKeySpec;

import org.bouncycastle.crypto.engines.AESEngine;
import org.bouncycastle.crypto.modes.AEADBlockCipher;
import org.bouncycastle.crypto.modes.CCMBlockCipher;
import org.bouncycastle.crypto.params.AEADParameters;
import org.bouncycastle.crypto.params.KeyParameter;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

But that is still not that useful.

Let's make it give us the current user.

## Create a user model { #create-a-user-model }

First, let's create a Pydantic user model.

The same way we use Pydantic to declare bodies, we can use it anywhere else:

{* ../../docs_src/security/tutorial002_an_py310.py hl[5,12:6] *}

## Create a `get_current_user` dependency { #create-a-get-current-user-dependency }

  /** Creates a new {@code CharBuffer} for buffering reads or writes. */
  static CharBuffer createBuffer() {
    return CharBuffer.allocate(DEFAULT_BUF_SIZE);
  }

  private CharStreams() {}

  /**
   * Copies all characters between the {@link Readable} and {@link Appendable} objects. Does not
   * close or flush either object.
   *
   * @param from the object to read from
   * @param to the object to write to