errors.invalid_header_for_request_file=Ongeldige headerregel: {0}
errors.could_not_delete_logged_in_user=Kan ingelogde gebruiker niet verwijderen.
errors.unauthorized_request=Ongeautoriseerd verzoek.
errors.failed_to_print_thread_dump=Kan thread-dump niet afdrukken.
errors.file_is_not_supported={0} wordt niet ondersteund.
errors.plugin_file_is_not_found={0} niet gevonden.
errors.failed_to_install_plugin=Kan {0} niet installeren.

- Bump node-problem-detector version to v0.8.5 to fix OOM detection in with Linux kernels 5.1+ ([#96716](https://github.com/kubernetes/kubernetes/pull/96716), [@tosi3k](https://github.com/tosi3k)) [SIG Cloud Provider, Scalability and Testing]

            }
    return users


def update_content(*, content_path: Path, new_content: Any) -> bool:
    old_content = content_path.read_text(encoding="utf-8")

    new_content = yaml.dump(new_content, sort_keys=False, width=200, allow_unicode=True)
    if old_content == new_content:
        logging.info(f"The content hasn't changed for {content_path}")
        return False

        )
    return tiers


def update_content(*, content_path: Path, new_content: Any) -> bool:
    old_content = content_path.read_text(encoding="utf-8")

    new_content = yaml.dump(new_content, sort_keys=False, width=200, allow_unicode=True)
    if old_content == new_content:
        logging.info(f"The content hasn't changed for {content_path}")
        return False

errors.could_not_delete_logged_in_user=Impossibile eliminare l'utente loggato.
errors.unauthorized_request=Richiesta non autorizzata.
errors.failed_to_print_thread_dump=Impossibile stampare il dump del thread.
errors.file_is_not_supported={0} non è supportato.
errors.plugin_file_is_not_found={0} non trovato.
errors.failed_to_install_plugin=Impossibile installare {0}.

{* ../../docs_src/extra_models/tutorial001_py310.py hl[7,9,14,20,22,27:28,31:33,38:39] *}

### Про `**user_in.model_dump()` { #about-user-in-model-dump }

#### `.model_dump()` из Pydantic { #pydantics-model-dump }

`user_in` — это Pydantic-модель класса `UserIn`.

У Pydantic-моделей есть метод `.model_dump()`, который возвращает `dict` с данными модели.

{* ../../docs_src/extra_models/tutorial001_py310.py hl[7,9,14,20,22,27:28,31:33,38:39] *}

### Sobre `**user_in.model_dump()` { #about-user-in-model-dump }

#### O `.model_dump()` do Pydantic { #pydantics-model-dump }

`user_in` é um modelo Pydantic da classe `UserIn`.

Os modelos Pydantic possuem um método `.model_dump()` que retorna um `dict` com os dados do modelo.

Configure the heap size.

------------------------------
./gradlew test -Dtests.heap.size=512m
------------------------------

Pass arbitrary jvm arguments.

------------------------------
# specify heap dump path
./gradlew test -Dtests.jvm.argline="-XX:HeapDumpPath=/path/to/heapdumps"
# enable gc logging
./gradlew test -Dtests.jvm.argline="-verbose:gc"
# enable security debugging

{* ../../docs_src/extra_models/tutorial001_py310.py hl[7,9,14,20,22,27:28,31:33,38:39] *}

### Über `**user_in.model_dump()` { #about-user-in-model-dump }

#### Pydantics `.model_dump()` { #pydantics-model-dump }

`user_in` ist ein Pydantic-Modell der Klasse `UserIn`.

labels.crawling_info_delete_all_link=Delete All
labels.crawling_info_delete_all_confirmation=Are you sure you want to delete all?
labels.crawling_info_delete_all_cancel=Cancel
labels.crawling_info_thread_dump=Thread Dump
labels.crawling_info_CrawlerStartTime=Crawler Start Time
labels.crawling_info_CrawlerEndTime=Crawler End Time
labels.crawling_info_CrawlerExecTime=Crawler Execution Time
labels.crawling_info_CrawlerStatus=Crawler Status