*   It is similar to a Promise in JavaScript.
 *   It allows you to register callbacks that will be executed when the computation is complete,
 *   either successfully (resolve) or with an error (reject).
 * </p>
 *
 * <p>
 *   The Deferred class has a Promise inner class that allows you to register callbacks
 *   to be executed when the computation is complete.

Your API now has the power to control its own <abbr title="This is a joke, just in case. It has nothing to do with cookie consents, but it's funny that even the API can now reject the poor cookies. Have a cookie. 🍪">cookie consent</abbr>. 🤪🍪

You can use Pydantic's model configuration to `forbid` any `extra` fields:

{* ../../docs_src/cookie_param_models/tutorial002_an_py310.py hl[10] *}

	}

	// If we have too many waiting, reject this at once.
	if l.waitMutex.Load() > lockMutexWaitLimit {
		l.locksOverloaded.Add(1)
		return false, nil
	}
	// Wait for mutex
	defer l.getMutex()()
	if ctx.Err() != nil {
		return false, ctx.Err()
	}
	if !l.canTakeLock(args.Resources...) {
		// Not all locks can be taken on resources,
		// reject it completely.
		return false, nil
	}

## Get Started with MinIO in Erasure Code

### 1. Prerequisites

Install MinIO - [MinIO Quickstart Guide](https://docs.min.io/community/minio-object-store/operations/deployments/baremetal-deploy-minio-on-redhat-linux.html)

### 2. Run MinIO Server with Erasure Code

Example: Start MinIO server in a 12 drives setup, using MinIO binary.

```sh
minio server /data{1...12}
```

        SmbFileFilter filter = f -> f.length() > 0;

        // negative size -> reject
        when(smbFile.length()).thenReturn(-1L);
        assertFalse(filter.accept(smbFile), "Negative size should be rejected");
        verify(smbFile, times(1)).length();

        // zero size -> reject
        reset(smbFile);
        when(smbFile.length()).thenReturn(0L);

  public void testDelegateRejection() {
    AtomicInteger numCalls = new AtomicInteger();
    AtomicBoolean reject = new AtomicBoolean(true);
    SequentialExecutor executor =
        new SequentialExecutor(
            new Executor() {
              @Override
              public void execute(Runnable r) {
                if (reject.get()) {
                  throw new RejectedExecutionException();
                }

# code.
#
# https://github.com/kubernetes/test-infra/blob/master/prow/plugins/size/size.go
#
# This file is a series of lines, each of the form:
#     <type> <name>
#
# Type can be:
#    path - an exact path to a single file
#    file-name - an exact leaf filename, regardless of path
#    path-prefix - a prefix match on the file path
#    file-prefix - a prefix match of the leaf filename (no path)

/**
 * A pluggable service for processing model objects during model building.
 *
 * <p>This service allows implementations to:</p>
 * <ul>
 *   <li>Pool identical objects to reduce memory footprint</li>
 *   <li>Intern objects for faster equality comparisons</li>
 *   <li>Apply custom optimization strategies</li>
 *   <li>Transform or modify objects during building</li>
 * </ul>
 *

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

---> 100%
```

</div>

## Cliente WebSockets { #websockets-client }

### Em produção { #in-production }

Em seu sistema de produção, você provavelmente tem um frontend criado com um framework moderno como React, Vue.js ou Angular.

E para comunicar usando WebSockets com seu backend, você provavelmente usaria as utilidades do seu frontend.