This client could be a browser with a frontend, a code from someone else, an IoT device, etc.

You could need to tell the client that:

* The client doesn't have enough privileges for that operation.
* The client doesn't have access to that resource.
* The item the client was trying to access doesn't exist.
* etc.

    * And validators allow complex data schemas to be clearly and easily defined, checked and documented as JSON Schema.
    * You can have deeply **nested JSON** objects and have them all validated and annotated.
* **Extensible**:
    * Pydantic allows custom data types to be defined or you can extend validation with methods on a model decorated with the validator decorator.

@GwtCompatible
public final class Futures extends GwtFuturesCatchingSpecialization {

  // A note on memory visibility.
  // Many of the utilities in this class (transform, withFallback, withTimeout, asList, combine)
  // have two requirements that significantly complicate their design.
  // 1. Cancellation should propagate from the returned future to the input future(s).
  // 2. The returned futures shouldn't unnecessarily 'pin' their inputs after completion.

Blocking APIs may be inefficient because you hold a thread idle while waiting on the network. Threads are expensive because they have both a memory overhead and a context-switching overhead.

#### Framed protocols

// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package cmd

import (
	"io"
	"maps"
	"math"
	"net/http"
	"time"

   * @param sampleKey a key of the same type as that contained by {@code multimap}. {@code multimap}
   *     may or may not have {@code sampleKey} as a key.
   * @param sampleValue a key of the same type as that contained by {@code multimap}. {@code
   *     multimap} may or may not have {@code sampleValue} as a key.
   */
  public static <K extends @Nullable Object, V extends @Nullable Object>

      return putBytesInternal(readBuffer);
    } finally {
      readBuffer.order(order);
    }
  }

  @CanIgnoreReturnValue
  private Hasher putBytesInternal(ByteBuffer readBuffer) {
    // If we have room for all of it, this is easy
    if (readBuffer.remaining() <= buffer.remaining()) {
      buffer.put(readBuffer);
      munchIfFull();
      return this;
    }

                    EmptyIterator iterator3 = new EmptyIterator()) {
                assertFalse(iterator1.hasNext(), "First instance should have no elements");
                assertFalse(iterator2.hasNext(), "Second instance should have no elements");
                assertFalse(iterator3.hasNext(), "Third instance should have no elements");

                assertNull(iterator1.next(), "First instance next() should return null");

Instead, you want to provide a different dependency that will be used only during tests (possibly only some specific tests), and will provide a value that can be used where the value of the original dependency was used.

### Use cases: external service { #use-cases-external-service }

An example could be that you have an external authentication provider that you need to call.

If you want to secure your API, there are several better things you can do, for example:

* Make sure you have well defined Pydantic models for your request bodies and responses.
* Configure any required permissions and roles using dependencies.
* Never store plaintext passwords, only password hashes.