{* ../../docs_src/response_model/tutorial003_01_py310.py hl[7:10,13:14,18] *}

With this, we get tooling support, from editors and mypy as this code is correct in terms of types, but we also get the data filtering from FastAPI.

How does this work? Let's check that out. 🤓

### Type Annotations and Tooling { #type-annotations-and-tooling }

First let's see how editors, mypy and other tools would see this.

  stars: 3213
  owner_login: TracecatHQ
  owner_html_url: https://github.com/TracecatHQ
- name: opyrator
  html_url: https://github.com/ml-tooling/opyrator
  stars: 3131
  owner_login: ml-tooling
  owner_html_url: https://github.com/ml-tooling
- name: docarray
  html_url: https://github.com/docarray/docarray
  stars: 3098
  owner_login: docarray
  owner_html_url: https://github.com/docarray

/// tip

Some editors check for unused function parameters, and show them as errors.

Using these `dependencies` in the *path operation decorator* you can make sure they are executed while avoiding editor/tooling errors.

It might also help avoid confusion for new developers that see an unused parameter in your code and could think it's unnecessary.

///

/// info

import jcifs.SmbTransport;
import jcifs.SmbTransportPool;
import jcifs.util.transport.TransportException;

/**
 * Implementation of the SMB transport pool for managing SMB connections.
 * Provides connection pooling and reuse for improved performance.
 *
 * @author mbechler
 *
 * <p>This class is intended for internal use.</p>
 */
public class SmbTransportPoolImpl implements SmbTransportPool {

    /**