*       <i>removing</i> that key from the multimap.
 *   <li>The total entry count is available as {@link #size}.
 *   <li>Many complex operations become easier; for example, {@code
 *       Collections.min(multimap.values())} finds the smallest value across all keys.
 * </ul>
 *
 * <h3>Implementations</h3>
 *
 * <ul>
 *   <li>{@link ImmutableListMultimap}

Esse desacoplamento de partes, e sendo um "microframework" que pode ser extendido para cobrir exatamente o que é necessário era um recurso chave que eu queria manter.

Dada a simplicidade do Flask, parecia uma ótima opção para construção de APIs. A próxima coisa a procurar era um "Django REST Framework" para Flask.

/// check | **FastAPI** inspirado para

// converted to int they correspond to the rune size that was read.
type readOp int8

// Don't use iota for these, as the values need to correspond with the
// names and comments, which is easier to see when being explicit.
const (
	opRead      readOp = -1 // Any other read operation.
	opInvalid   readOp = 0  // Non-read operation.
	opReadRune1 readOp = 1  // Read rune of size 1.

    Put this annotation on a `MockWebServer` property and the extension will start it before your
    test executes and stop it after it completes. No further configuration is required.

    ```kotlin
    @StartStop val server = MockWebServer()
    ```

 *  Breaking: Don't automatically start `MockWebServer` after calls to accessors like `port`. Now
    these accessors will throw an `IllegalStateException` if the service has not yet been started.

    return Traverser.forTree(FILE_TREE);
  }

  private static final SuccessorsFunction<File> FILE_TREE =
      file -> {
        // check isDirectory() just because it may be faster than listFiles() on a non-directory
        if (file.isDirectory()) {
          File[] files = file.listFiles();
          if (files != null) {
            return unmodifiableList(Arrays.asList(files));
          }

	beforeDrives := formatsToDrivesInfo(s.endpoints.Endpoints, formats, sErrs)

	res.After.Drives = make([]madmin.HealDriveInfo, len(beforeDrives))
	res.Before.Drives = make([]madmin.HealDriveInfo, len(beforeDrives))
	// Copy "after" drive state too from before.
	for k, v := range beforeDrives {
		res.Before.Drives[k] = v
		res.After.Drives[k] = v
	}

	if countErrs(sErrs, errUnformattedDisk) == 0 {

 * }
 *
 * <h3>Alternatives</h3>
 *
 * <h4>Frameworks</h4>
 *
 * <p>When chaining together a graph of asynchronous operations, you will often find it easier to
 * use a framework. Frameworks automate the process, often adding features like monitoring,
 * debugging, and cancellation. Examples of frameworks include:
 *
 * <ul>

)

// tagKey returns the tag-based key to use in the pkgCache.
// It is a comma-separated string; the first part is dir, the rest tags.
// The satisfied tags are derived from context but only those that
// matter (the ones listed in the tags argument plus GOOS and GOARCH) are used.
// The tags list, which came from go/build's Package.AllTags,
// is known to be sorted.
func tagKey(dir string, context *build.Context, tags []string) string {

	if r.UnreadRune() == nil {
		t.Error("expected error after UnreadRune (1)")
	}
	// Test error after Read.
	_, _, err = r.ReadRune() // reset state
	if err != nil {
		t.Error("unexpected error on ReadRune (2):", err)
	}
	_, err = r.Read(buf)
	if err != nil {
		t.Error("unexpected error on Read (2):", err)
	}
	if r.UnreadRune() == nil {
		t.Error("expected error after Read (2)")
	}
	// Test error after ReadByte.

And still, you would probably not want the application to stay dead because there was an error in one place, you probably want it to **continue running** at least for the *path operations* that are not broken.

### Restart After Crash { #restart-after-crash }

But in those cases with really bad errors that crash the running **process**, you would want an external component that is in charge of **restarting** the process, at least a couple of times...

/// tip