ReadingConverter readingConverter, Normalizer normalizer);

    /**
     * Parses a document and extracts suggest items based on the provided fields and converters.
     *
     * @param document The document to parse, represented as a map of field names to values.
     * @param fields The fields to extract from the document.
     * @param tagFieldNames The names of the fields that contain tags.

 */
public interface DocumentReader extends Closeable {
    /**
     * Reads a document and returns its contents as a map.
     *
     * @return a map containing the document's data, or null if there are no more documents to read.
     */
    Map<String, Object> read();

    @Override
    void close();

        fileTypeHelper.add("application/pdf", "document");
        fileTypeHelper.add("application/msword", "document");
        fileTypeHelper.add("text/plain", "text");

        String[] types = fileTypeHelper.getTypes();
        assertEquals(2, types.length);

        Arrays.sort(types);
        assertEquals("document", types[0]);
        assertEquals("text", types[1]);
    }

## Changes by Kind

### API Change

- Protobuf serialization of metav1.MicroTime timestamps (used in `Lease` and `Event` API objects) has been corrected to truncate to microsecond precision, to match the documented behavior and JSON/YAML serialization. Any existing persisted data is truncated to microsecond when read from etcd. ([#111936](https://github.com/kubernetes/kubernetes/pull/111936), [@haoruan](https://github.com/haoruan)) [SIG API Machinery]

labels.updatedTime=Bijgewerkt op
labels.urls=URL's
labels.userAgent=User-Agent
labels.username=Gebruikersnaam
labels.value=Waarde
labels.versionNo=Versienummer
labels.cronExpression=Planning
labels.dayForCleanup=Documenten ouder dan de opgegeven datum verwijderen
labels.crawlingThreadCount=Aantal gelijktijdige crawls
labels.boost=Boostwaarde
labels.crawlingConfigName=Naam
labels.crawlingConfigPath=Te crawlen pad
labels.processType=Procestype

La principale fonctionnalité que j'ai emprunté à Django REST Framework était la documentation automatique des API.

Puis j'ai découvert qu'il existait une norme pour documenter les API, en utilisant JSON (ou YAML, une extension de JSON) appelée Swagger.

Il existait déjà une interface utilisateur Web pour les API Swagger. Donc, être capable de générer une documentation

                for (final Map<String, Object> document : documentItems) {
                    if (!first1) {
                        buf.append(',');
                    } else {
                        first1 = false;
                    }
                    buf.append('{');
                    boolean first2 = true;
                    for (final Map.Entry<String, Object> entry : document.entrySet()) {

     */
    public SearchRenderData() {
        // Default constructor
    }

    /**
     * Sets the list of search result documents.
     *
     * @param documentItems The list of search result documents
     */
    public void setDocumentItems(final List<Map<String, Object>> documentItems) {
        this.documentItems = documentItems;
    }

    /**

## Follow-up Requests

When your requested URL has moved, the webserver will return a response code like `302` to indicate the document’s new URL. OkHttp will follow the redirect to retrieve a final response.

O **FastAPI** irá **extrair** as informações para **cada campo** dos **dados do formulário** na requisição e dar para você o modelo Pydantic que você definiu.

## Confira os Documentos

Você pode verificar na UI de documentação em `/docs`:

<div class="screenshot">
<img src="/img/tutorial/request-form-models/image01.png">
</div>

## Proibir Campos Extras de Formulários