*   <li>Optionally removing duplicate terms based on a flag.</li>
 *   <li>Limiting the maximum size of alphanumeric and symbol terms.</li>
 * </ul>
 *
 * <p>The {@link TextNormalizeContext} class provides a fluent API to configure the text
 * normalization process, including setting initial buffer capacity, maximum term sizes,
 * duplicate term removal, and custom space characters.
 *
 * <p>Example usage:

        RenderDataUtil.register(data, "relatedQueryItems", relatedQueryService.getRelatedQueryList(relatedQueryPager)); // page navi

        // restore from pager
        copyBeanToBean(relatedQueryPager, form, op -> op.include("term", "queries"));
    }

    // ===================================================================================
    //                                                                        Edit Execute

Translate to Portuguese (Português).

Language code: pt.

For instructions or titles in imperative, keep them in imperative, for example "Import FastAPI" to "Importe o FastAPI".

Keep existing translations as they are if the term is already translated.

        RenderDataUtil.register(data, "keyMatchItems", keyMatchService.getKeyMatchList(keyMatchPager)); // page navi

        // restore from pager
        copyBeanToBean(keyMatchPager, form, op -> op.include("term", "query"));
    }

    // ===================================================================================
    //                                                                        Edit Execute

package gradlebuild

import org.gradle.api.tasks.testing.Test
import org.gradle.internal.os.OperatingSystem


val propagatedEnvironmentVariables = listOf(
    // Obviously necessary
    "HOME",
    "SHELL",
    "TERM",

    // Otherwise Windows complains "Unrecognized Windows Sockets error: 10106"
    "SystemRoot",
    "OS",

    // For Android tests
    "ANDROID_HOME",
    "ANDROID_SDK_ROOT",

    }

    private static String parse(String rule, Set<String> dup) {
        String[] values = CSVUtil.parse(rule);
        if (dup.add(values[0]) == false) {
            throw new IllegalArgumentException("Found duplicate term [" + values[0] + "] in user dictionary.");
        }
        return rule;
    }

    public static UserDictionary getUserDictionary(Environment env, Settings settings) {

        // restore from pager
        copyBeanToBean(relatedContentPager, form, op -> op.include("term", "content"));
    }

    // ===================================================================================
    //                                                                        Edit Execute

Ви можете отримати метадані про завантажений файл.
* Він має <a href="https://docs.python.org/3/glossary.html#term-file-like-object" class="external-link" target="_blank">file-like</a> `асинхронний файловий інтерфейс` interface.

            doColumn("maxSize");
        }

        public void columnQuery() {
            doColumn("query");
        }

        public void columnTerm() {
            doColumn("term");
        }

        public void columnUpdatedBy() {
            doColumn("updatedBy");
        }

        public void columnUpdatedTime() {
            doColumn("updatedTime");
        }

        /**
         * Constructs a Field from OpenSearch Terms aggregation.
         * Decodes the field name and processes all term buckets to extract
         * field values and their document counts.
         *
         * @param termFacet the OpenSearch Terms aggregation containing field facet data
         */
        public Field(final Terms termFacet) {