```

**Important**: Return types or response models are what filter data ensuring no sensitive information is exposed. And they are used to serialize data with Pydantic (in Rust), this is the main idea that can increase response performance.

The return type doesn't have to be a Pydantic model, it could be a different type, like a list of integers, or a dict, etc.

### When to use `response_model` instead

Java serialization is one way to implement this, however, despite its simplicity of implementation, it has several drawbacks:

- **Performance:**
Java's built-in serialization mechanism is often slower compared to other serialization solutions.
This is due to Java's use of reflection and the need to maintain a lot of metadata.

- **Size of Serialized Data:**

import japicmp.model.JApiMethod
import javassist.bytecode.SourceFileAttribute
import java.io.File


/**
 * Repository of sources for binary compatibility checks.
 *
 * `WARN` Holds resources open for performance, must be closed after use.
 */
class BinaryCompatibilityRepository internal constructor(

    private
    val sources: SourcesRepository

) : AutoCloseable {

    companion object {

     */
    public static RdmaProvider selectBestProvider() {
        // Try providers in order of preference
        List<RdmaProvider> providers = Arrays.asList(new DisniRdmaProvider(), // InfiniBand/RoCE - highest performance
                new TcpRdmaProvider() // TCP fallback - always available
        );

        for (RdmaProvider provider : providers) {
            if (provider.isAvailable()) {

 *       mutable objects as elements at all, as many users may expect your "immutable" object to be
 *       <i>deeply</i> immutable.
 * </ul>
 *
 * <h4>Performance notes</h4>
 *
 * <ul>
 *   <li>Implementations can be generally assumed to prioritize memory efficiency, then speed of
 *       access, and lastly speed of creation.

Il existe plusieurs alternatives, notamment :

* [Uvicorn](https://www.uvicorn.dev/) : un serveur ASGI haute performance.
* [Hypercorn](https://hypercorn.readthedocs.io/) : un serveur ASGI compatible avec HTTP/2 et Trio entre autres fonctionnalités.
* [Daphne](https://github.com/django/daphne) : le serveur ASGI conçu pour Django Channels.

/**
 * When run from a Continuous Integration environment, we only want to archive a subset of reports, mostly for
 * failing tasks only, to not use up unnecessary disk space on Team City. This also improves the performance of
 * artifact publishing by reducing the artifacts and packaging reports that consist of multiple files.
 *
 * Reducing the number of reports also makes it easier to find the important ones when analysing a failed build in

regular | standard | 97 | 3.6MB
regular | jstream | 175 | 2.1MB
large | standard | 92 | 305MB
large | jstream | 404 | 69MB

In a real world scenario, including initialization and reader overhead from varying blob sizes, performance can be expected as below:

that Commercial Contributor then makes performance claims, or offers warranties
related to Product X, those performance claims and warranties are such Commercial
Contributor's responsibility alone. Under this section, the Commercial Contributor
would have to defend claims against the other Contributors related to those
performance claims and warranties, and if a court requires any other Contributor

  /**
   * Creates a <i>mutable</i>, empty {@code LinkedList} instance.
   *
   * <p><b>Note:</b> if you won't be adding any elements to the list, use {@link ImmutableList#of()}
   * instead.
   *
   * <p><b>Performance note:</b> {@link ArrayList} and {@link java.util.ArrayDeque} consistently
   * outperform {@code LinkedList} except in certain rare and specific situations. Unless you have