```console
$ docker run -d --name mycontainer -p 80:80 myimage
```

</div>

Vous disposez maintenant d'un serveur FastAPI optimisé dans un conteneur Docker. Configuré automatiquement pour votre
serveur actuel (et le nombre de cœurs du CPU).

## Vérifier

{* ../../docs_src/dependencies/tutorial001_02_an_py310.py hl[12,16,21] *}

/// tip

This is just standard Python, it's called a "type alias", it's actually not specific to **FastAPI**.

But because **FastAPI** is based on the Python standards, including `Annotated`, you can use this trick in your code. 😎

///

 * the License.
 */
package com.google.common.collect;

import java.util.Collection;
import org.checkerframework.checker.nullness.qual.Nullable;

/** Never actually created; instead delegates to JdkBackedImmutableMultiset. */
@ElementTypesAreNonnullByDefault
class RegularImmutableMultiset<E> extends ImmutableMultiset<E> {
  static final ImmutableMultiset<Object> EMPTY =

import java.util.concurrent.Callable;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * A TimeLimiter implementation which actually does not attempt to limit time at all. This may be
 * desirable to use in some unit tests. More importantly, attempting to debug a call which is

        // I'm fully aware that the file could just be moved using File.rename but
        // there are bugs in various JVM that have problems doing this across
        // different filesystem. So we'll incur the small hit to actually copy
        // here and be safe. jvz.
        // ----------------------------------------------------------------------------

        try {
            Files.createDirectories(destination.toPath().getParent());

* Retrieve the stored data.
* Put that data in a Pydantic model.
* Generate a `dict` without default values from the input model (using `exclude_unset`).
    * This way you can update only the values actually set by the user, instead of overriding values already stored with default values in your model.
* Create a copy of the stored model, updating its attributes with the received partial updates (using the `update` parameter).

     * it.
     */
    setResult(transformResult);
  }

  /** Template method for subtypes to actually run the transform. */
  @ForOverride
  @ParametricNullness
  abstract T doTransform(F function, @ParametricNullness I result) throws Exception;

  /** Template method for subtypes to actually set the result. */
  @ForOverride
  abstract void setResult(@ParametricNullness T result);

  @Override

  public int hashCode() {
    return delegate.hashCode();
  }

  private void validate() {
    // Don't use checkState(), because we don't want the overhead of generating the error message
    // unless it's actually going to be used; validate() is called for all set method calls, so it
    // needs to be fast.
    // (We could instead generate the message once, when the set is created, but zero is better.)
    if (!validator.get()) {

      - uses: actions/checkout@v4
      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - name: Setup uv
        uses: astral-sh/setup-uv@v3
        with:
          version: "0.4.15"
          enable-cache: true
          cache-dependency-glob: |
            requirements**.txt
            pyproject.toml

/// note | "Technical Details"

You could also use `from starlette.staticfiles import StaticFiles`.

**FastAPI** provides the same `starlette.staticfiles` as `fastapi.staticfiles` just as a convenience for you, the developer. But it actually comes directly from Starlette.

///

### What is "Mounting"

"Mounting" means adding a complete "independent" application in a specific path, that then takes care of handling all the sub-paths.