For example:

{* ../../docs_src/metadata/tutorial001_1_py39.py hl[31] *}

## Metadata for tags { #metadata-for-tags }

You can also add additional metadata for the different tags used to group your path operations with the parameter `openapi_tags`.

It takes a list containing one dictionary for each tag.

Each dictionary can contain:

		if collectorPath.isDescendantOf(path) {
			gatherer := h.metricsData.mgGatherers[collectorPath]

			// For Bucket metrics we need to set the buckets argument inside the
			// metric group, so that it will affect collection. If no buckets
			// are provided, we will not return bucket metrics.
			if bmg, ok := h.metricsData.bucketMGMap[collectorPath]; ok {
				if len(buckets) == 0 {
					continue
				}

 * multi-level dependency graph to a map of ordered lists that can be turned into classpaths.
 * During this process only the most relevant version of each artifact
 * (based on group ID and artifact ID) is retained, resolving conflicts and eliminating duplicates to ensure
 * that each dependency is included only once in the final build.</p>
 *

            Matcher pidMatcher = pidPattern.matcher(line);
            if (commandLineArgsMatcher.find() && pidMatcher.find()) {
                String pid = pidMatcher.group(1);
                if (!MY_PID.equals(pid)) {
                    action.accept(pid, line);
                }
            }
        });
    }

    private static List<String> ps() {

pkg log/slog, func Error(string, ...interface{}) #56345
pkg log/slog, func Float64(string, float64) Attr #56345
pkg log/slog, func Float64Value(float64) Value #56345
pkg log/slog, func Group(string, ...interface{}) Attr #59204
pkg log/slog, func GroupValue(...Attr) Value #56345
pkg log/slog, func InfoContext(context.Context, string, ...interface{}) #61200
pkg log/slog, func Info(string, ...interface{}) #56345

    You could have custom internal logic to separate it by colon characters (`:`) or
    similar, and get the two parts `items` and `read`. Many applications do that to
    group and organize permissions, you could do it as well in your application, just
    know that that it is application specific, it's not part of the specification.
    """

    def __init__(
        self,
        *,

		t.Errorf("joins should be ordered, but got %v", stmt.SQL.String())
	}

	iv := DB.Table(`table_invoices`).Select(`seller, SUM(total) as total, SUM(paid) as paid, SUM(balance) as balance`).Group(`seller`)
	stmt = dryDB.Table(`table_employees`).Select(`id, name, iv.total, iv.paid, iv.balance`).Joins(`LEFT JOIN (?) AS iv ON iv.seller = table_employees.id`, iv).Scan(&user).Statement

                    Arrays.toString(ValidationReportLevel.values()));
            return DEFAULT_VALIDATION_LEVEL;
        }
    }

    private String pluginKey(String groupId, String artifactId, String version) {
        return groupId + ":" + artifactId + ":" + version;
    }

    private String pluginKey(MojoDescriptor mojoDescriptor) {
        PluginDescriptor pd = mojoDescriptor.getPluginDescriptor();

3802 1332 232 1 Manhattan 023200 1023200 E MN03 Central Harlem North-Polo Grounds 3803 3389529 2 2014-03-25 13:13:26 2014-03-25 13:15:03 N 1 -73.953834533691406 40.811191558837891 -73.938751220703125 40.813190460205078 1 0.30 3.5 0 0.5 0 0 4 2 1 166 42 green 0.00 0.0 0.0 39 26 5.82 1312 209.01 1 Manhattan 020901 1020901 E MN09 Morningside Heights 3802 1596 212 1 Manhattan 021200 1021200 I MN03 Central Harlem North-Polo Grounds 3803 3389530 2 2014-03-20 16:11:35 2014-03-20 16:52:09 N 1 -73.953887939453125...

# Modelos de Parâmetros do Cabeçalho { #header-parameter-models }

Se você possui um grupo de **parâmetros de cabeçalho** relacionados, você pode criar um **modelo do Pydantic** para declará-los.

Isso vai lhe permitir **reusar o modelo** em **múltiplos lugares** e também declarar validações e metadados para todos os parâmetros de uma vez. 😎

/// note | Nota

Isso é possível desde a versão `0.115.0` do FastAPI. 🤓

///