def ml_trained_models()

in elasticsearch/_sync/client/cat.py [0:0]

• 108 lines of code
• 1 McCabe index (conditional complexity)

    def ml_trained_models(
        self,
        *,
        model_id: t.Optional[str] = None,
        allow_no_match: t.Optional[bool] = None,
        bytes: t.Optional[
            t.Union[str, t.Literal["b", "gb", "kb", "mb", "pb", "tb"]]
        ] = None,
        error_trace: t.Optional[bool] = None,
        filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None,
        format: t.Optional[str] = None,
        from_: t.Optional[int] = None,
        h: t.Optional[
            t.Union[
                t.Sequence[
                    t.Union[
                        str,
                        t.Literal[
                            "create_time",
                            "created_by",
                            "data_frame_analytics_id",
                            "description",
                            "heap_size",
                            "id",
                            "ingest.count",
                            "ingest.current",
                            "ingest.failed",
                            "ingest.pipelines",
                            "ingest.time",
                            "license",
                            "operations",
                            "version",
                        ],
                    ]
                ],
                t.Union[
                    str,
                    t.Literal[
                        "create_time",
                        "created_by",
                        "data_frame_analytics_id",
                        "description",
                        "heap_size",
                        "id",
                        "ingest.count",
                        "ingest.current",
                        "ingest.failed",
                        "ingest.pipelines",
                        "ingest.time",
                        "license",
                        "operations",
                        "version",
                    ],
                ],
            ]
        ] = None,
        help: t.Optional[bool] = None,
        human: t.Optional[bool] = None,
        pretty: t.Optional[bool] = None,
        s: t.Optional[
            t.Union[
                t.Sequence[
                    t.Union[
                        str,
                        t.Literal[
                            "create_time",
                            "created_by",
                            "data_frame_analytics_id",
                            "description",
                            "heap_size",
                            "id",
                            "ingest.count",
                            "ingest.current",
                            "ingest.failed",
                            "ingest.pipelines",
                            "ingest.time",
                            "license",
                            "operations",
                            "version",
                        ],
                    ]
                ],
                t.Union[
                    str,
                    t.Literal[
                        "create_time",
                        "created_by",
                        "data_frame_analytics_id",
                        "description",
                        "heap_size",
                        "id",
                        "ingest.count",
                        "ingest.current",
                        "ingest.failed",
                        "ingest.pipelines",
                        "ingest.time",
                        "license",
                        "operations",
                        "version",
                    ],
                ],
            ]
        ] = None,
        size: t.Optional[int] = None,
        time: t.Optional[
            t.Union[str, t.Literal["d", "h", "m", "micros", "ms", "nanos", "s"]]
        ] = None,
        v: t.Optional[bool] = None,