return foo

    with pytest.raises(
        AssertionError,
        match=(
            "Cannot specify `Depends` in `Annotated` and default value"
            " together for 'foo'"
        ),
    ):

        @app.get("/")
        async def get2(foo: Annotated[int, Depends(dep)] = Depends(dep)):
            pass  # pragma: nocover

    with pytest.raises(

///

### `startup` and `shutdown` together { #startup-and-shutdown-together }

There's a high chance that the logic for your *startup* and *shutdown* is connected, you might want to start something and then finish it, acquire a resource and then release it, etc.

    /**
     * Shortcut for {@code getService(ArtifactResolver.class).resolve(...)}.
     *
     * @param coordinates coordinates of the artifact to resolve
     * @return requested artifact together with the path to its file
     * @throws org.apache.maven.api.services.ArtifactResolverException if the artifact resolution failed
     *
     * @see org.apache.maven.api.services.ArtifactResolver#resolve(Session, Collection)

# Gradle architecture documentation

This directory contains documentation that describes Gradle's architecture and how the various pieces fit together and work.

## Architecture decision records (ADRs)

The Gradle team uses ADRs to record architectural decisions that the team has made.

See [Architecture decisions records](standards) for the list of ADRs.

# Gradle runtimes

Gradle is made up of the following processes that work together to "run the build":

- Gradle daemon. This is the process that actually runs the build. It hosts build logic and coordinates the lifecycle of the build. It is a long-running daemon process.
- CLI client. This is the `gradle` or `gradlew` command, and is responsible for locating, starting and interacting with the Gradle daemon, potentially downloading the Gradle distribution. 

This is not a limitation of **FastAPI**, it's part of the HTTP protocol.

///

## Recap { #recap }

 * ListenableFuture}</a>.
 *
 * <p>This class is GWT-compatible.
 *
 * <h3>Purpose</h3>
 *
 * <p>The main purpose of {@code ListenableFuture} is to help you chain together a graph of
 * asynchronous operations. You can chain them together manually with calls to methods like {@link
 * Futures#transform(ListenableFuture, com.google.common.base.Function, Executor) Futures.transform}

During bazel build all TensorFlow's Python dependencies are pinned to their
specific versions. This is necessary to ensure reproducibility of the build.
The pinned versions of the full transitive closure of TensorFlow's dependencies
together with their corresponding hashes are specified in
`requirements_lock_<python version>.txt` files (e.g.
`requirements_lock_3_12.txt` for `Python 3.12`).

To update the lock files, make sure

   * underlying hash functions together. This can be useful if you need to generate hash codes of a
   * specific length.
   *
   * <p>For example, if you need 1024-bit hash codes, you could join two {@link Hashing#sha512} hash
   * functions together: {@code Hashing.concatenating(Hashing.sha512(), Hashing.sha512())}.
   *
   * @since 19.0
   */

    e.execute(
        new Runnable() {
          @Override
          public void run() {
            assertThat(Thread.currentThread().isInterrupted()).isFalse();
          }
        });

    // Run these together.
    fakePool.runAll();

    // Check that this thread has been marked as interrupted again now that the thread has been
    // returned by SequentialExecutor. Clear the bit while checking so that the test doesn't hose