# Licensed to Elasticsearch B.V. under one or more contributor # license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright # ownership. Elasticsearch B.V. licenses this file to you under # the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import typing as t from elastic_transport import ObjectApiResponse, TextApiResponse from ._base import NamespacedClient from .utils import SKIP_IN_PATH, _quote, _rewrite_parameters class CatClient(NamespacedClient): @_rewrite_parameters() async def aliases( self, *, name: t.Optional[t.Union[str, t.Sequence[str]]] = None, error_trace: t.Optional[bool] = None, expand_wildcards: t.Optional[ t.Union[ t.Sequence[ t.Union[str, t.Literal["all", "closed", "hidden", "none", "open"]] ], t.Union[str, t.Literal["all", "closed", "hidden", "none", "open"]], ] ] = None, filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None, format: t.Optional[str] = None, h: t.Optional[t.Union[str, t.Sequence[str]]] = None, help: t.Optional[bool] = None, human: t.Optional[bool] = None, master_timeout: t.Optional[t.Union[str, t.Literal[-1], t.Literal[0]]] = None, pretty: t.Optional[bool] = None, s: t.Optional[t.Union[str, t.Sequence[str]]] = None, v: t.Optional[bool] = None, ) -> t.Union[ObjectApiResponse[t.Any], TextApiResponse]: """ .. raw:: html

Get aliases.

Get the cluster's index aliases, including filter and routing information. This API does not return data stream aliases.

IMPORTANT: CAT APIs are only intended for human consumption using the command line or the Kibana console. They are not intended for use by applications. For application consumption, use the aliases API.

``_ :param name: A comma-separated list of aliases to retrieve. Supports wildcards (`*`). To retrieve all aliases, omit this parameter or use `*` or `_all`. :param expand_wildcards: The type of index that wildcard patterns can match. If the request can target data streams, this argument determines whether wildcard expressions match hidden data streams. It supports comma-separated values, such as `open,hidden`. :param format: Specifies the format to return the columnar data in, can be set to `text`, `json`, `cbor`, `yaml`, or `smile`. :param h: List of columns to appear in the response. Supports simple wildcards. :param help: When set to `true` will output available columns. This option can't be combined with any other query string option. :param master_timeout: The period to wait for a connection to the master node. If the master node is not available before the timeout expires, the request fails and returns an error. To indicated that the request should never timeout, you can set it to `-1`. :param s: List of columns that determine how the table should be sorted. Sorting defaults to ascending and can be changed by setting `:asc` or `:desc` as a suffix to the column name. :param v: When set to `true` will enable verbose output. """ __path_parts: t.Dict[str, str] if name not in SKIP_IN_PATH: __path_parts = {"name": _quote(name)} __path = f'/_cat/aliases/{__path_parts["name"]}' else: __path_parts = {} __path = "/_cat/aliases" __query: t.Dict[str, t.Any] = {} if error_trace is not None: __query["error_trace"] = error_trace if expand_wildcards is not None: __query["expand_wildcards"] = expand_wildcards if filter_path is not None: __query["filter_path"] = filter_path if format is not None: __query["format"] = format if h is not None: __query["h"] = h if help is not None: __query["help"] = help if human is not None: __query["human"] = human if master_timeout is not None: __query["master_timeout"] = master_timeout if pretty is not None: __query["pretty"] = pretty if s is not None: __query["s"] = s if v is not None: __query["v"] = v __headers = {"accept": "text/plain,application/json"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.aliases", path_parts=__path_parts, ) @_rewrite_parameters() async def component_templates( self, *, name: t.Optional[str] = None, error_trace: t.Optional[bool] = None, filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None, format: t.Optional[str] = None, h: t.Optional[t.Union[str, t.Sequence[str]]] = None, help: t.Optional[bool] = None, human: t.Optional[bool] = None, local: t.Optional[bool] = None, master_timeout: t.Optional[t.Union[str, t.Literal[-1], t.Literal[0]]] = None, pretty: t.Optional[bool] = None, s: t.Optional[t.Union[str, t.Sequence[str]]] = None, v: t.Optional[bool] = None, ) -> t.Union[ObjectApiResponse[t.Any], TextApiResponse]: """ .. raw:: html

Get component templates.

Get information about component templates in a cluster. Component templates are building blocks for constructing index templates that specify index mappings, settings, and aliases.

IMPORTANT: CAT APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the get component template API.

``_ :param name: The name of the component template. It accepts wildcard expressions. If it is omitted, all component templates are returned. :param format: Specifies the format to return the columnar data in, can be set to `text`, `json`, `cbor`, `yaml`, or `smile`. :param h: List of columns to appear in the response. Supports simple wildcards. :param help: When set to `true` will output available columns. This option can't be combined with any other query string option. :param local: If `true`, the request computes the list of selected nodes from the local cluster state. If `false` the list of selected nodes are computed from the cluster state of the master node. In both cases the coordinating node will send requests for further information to each selected node. :param master_timeout: The period to wait for a connection to the master node. :param s: List of columns that determine how the table should be sorted. Sorting defaults to ascending and can be changed by setting `:asc` or `:desc` as a suffix to the column name. :param v: When set to `true` will enable verbose output. """ __path_parts: t.Dict[str, str] if name not in SKIP_IN_PATH: __path_parts = {"name": _quote(name)} __path = f'/_cat/component_templates/{__path_parts["name"]}' else: __path_parts = {} __path = "/_cat/component_templates" __query: t.Dict[str, t.Any] = {} if error_trace is not None: __query["error_trace"] = error_trace if filter_path is not None: __query["filter_path"] = filter_path if format is not None: __query["format"] = format if h is not None: __query["h"] = h if help is not None: __query["help"] = help if human is not None: __query["human"] = human if local is not None: __query["local"] = local if master_timeout is not None: __query["master_timeout"] = master_timeout if pretty is not None: __query["pretty"] = pretty if s is not None: __query["s"] = s if v is not None: __query["v"] = v __headers = {"accept": "text/plain,application/json"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.component_templates", path_parts=__path_parts, ) @_rewrite_parameters() async def count( self, *, index: t.Optional[t.Union[str, t.Sequence[str]]] = None, error_trace: t.Optional[bool] = None, filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None, format: t.Optional[str] = None, h: t.Optional[t.Union[str, t.Sequence[str]]] = None, help: t.Optional[bool] = None, human: t.Optional[bool] = None, pretty: t.Optional[bool] = None, s: t.Optional[t.Union[str, t.Sequence[str]]] = None, v: t.Optional[bool] = None, ) -> t.Union[ObjectApiResponse[t.Any], TextApiResponse]: """ .. raw:: html

Get a document count.

Get quick access to a document count for a data stream, an index, or an entire cluster. The document count only includes live documents, not deleted documents which have not yet been removed by the merge process.

IMPORTANT: CAT APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use the count API.

``_ :param index: A comma-separated list of data streams, indices, and aliases used to limit the request. It supports wildcards (`*`). To target all data streams and indices, omit this parameter or use `*` or `_all`. :param format: Specifies the format to return the columnar data in, can be set to `text`, `json`, `cbor`, `yaml`, or `smile`. :param h: List of columns to appear in the response. Supports simple wildcards. :param help: When set to `true` will output available columns. This option can't be combined with any other query string option. :param s: List of columns that determine how the table should be sorted. Sorting defaults to ascending and can be changed by setting `:asc` or `:desc` as a suffix to the column name. :param v: When set to `true` will enable verbose output. """ __path_parts: t.Dict[str, str] if index not in SKIP_IN_PATH: __path_parts = {"index": _quote(index)} __path = f'/_cat/count/{__path_parts["index"]}' else: __path_parts = {} __path = "/_cat/count" __query: t.Dict[str, t.Any] = {} if error_trace is not None: __query["error_trace"] = error_trace if filter_path is not None: __query["filter_path"] = filter_path if format is not None: __query["format"] = format if h is not None: __query["h"] = h if help is not None: __query["help"] = help if human is not None: __query["human"] = human if pretty is not None: __query["pretty"] = pretty if s is not None: __query["s"] = s if v is not None: __query["v"] = v __headers = {"accept": "text/plain,application/json"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.count", path_parts=__path_parts, ) @_rewrite_parameters() async def help(self) -> TextApiResponse: """ .. raw:: html

Get CAT help.

Get help for the CAT APIs.

``_ """ __path_parts: t.Dict[str, str] = {} __path = "/_cat" __query: t.Dict[str, t.Any] = {} __headers = {"accept": "text/plain"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.help", path_parts=__path_parts, ) @_rewrite_parameters() async def indices( self, *, index: t.Optional[t.Union[str, t.Sequence[str]]] = None, bytes: t.Optional[ t.Union[str, t.Literal["b", "gb", "kb", "mb", "pb", "tb"]] ] = None, error_trace: t.Optional[bool] = None, expand_wildcards: t.Optional[ t.Union[ t.Sequence[ t.Union[str, t.Literal["all", "closed", "hidden", "none", "open"]] ], t.Union[str, t.Literal["all", "closed", "hidden", "none", "open"]], ] ] = None, filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None, format: t.Optional[str] = None, h: t.Optional[t.Union[str, t.Sequence[str]]] = None, health: t.Optional[t.Union[str, t.Literal["green", "red", "yellow"]]] = None, help: t.Optional[bool] = None, human: t.Optional[bool] = None, include_unloaded_segments: t.Optional[bool] = None, master_timeout: t.Optional[t.Union[str, t.Literal[-1], t.Literal[0]]] = None, pretty: t.Optional[bool] = None, pri: t.Optional[bool] = None, s: t.Optional[t.Union[str, t.Sequence[str]]] = None, time: t.Optional[ t.Union[str, t.Literal["d", "h", "m", "micros", "ms", "nanos", "s"]] ] = None, v: t.Optional[bool] = None, ) -> t.Union[ObjectApiResponse[t.Any], TextApiResponse]: """ .. raw:: html

Get index information.

Get high-level information about indices in a cluster, including backing indices for data streams.

Use this request to get the following information for each index in a cluster:

  • shard count
  • document count
  • deleted document count
  • primary store size
  • total store size of all shards, including shard replicas

These metrics are retrieved directly from Lucene, which Elasticsearch uses internally to power indexing and search. As a result, all document counts include hidden nested documents. To get an accurate count of Elasticsearch documents, use the cat count or count APIs.

CAT APIs are only intended for human consumption using the command line or Kibana console. They are not intended for use by applications. For application consumption, use an index endpoint.

``_ :param index: Comma-separated list of data streams, indices, and aliases used to limit the request. Supports wildcards (`*`). To target all data streams and indices, omit this parameter or use `*` or `_all`. :param bytes: The unit used to display byte values. :param expand_wildcards: The type of index that wildcard patterns can match. :param format: Specifies the format to return the columnar data in, can be set to `text`, `json`, `cbor`, `yaml`, or `smile`. :param h: List of columns to appear in the response. Supports simple wildcards. :param health: The health status used to limit returned indices. By default, the response includes indices of any health status. :param help: When set to `true` will output available columns. This option can't be combined with any other query string option. :param include_unloaded_segments: If true, the response includes information from segments that are not loaded into memory. :param master_timeout: Period to wait for a connection to the master node. :param pri: If true, the response only includes information from primary shards. :param s: List of columns that determine how the table should be sorted. Sorting defaults to ascending and can be changed by setting `:asc` or `:desc` as a suffix to the column name. :param time: The unit used to display time values. :param v: When set to `true` will enable verbose output. """ __path_parts: t.Dict[str, str] if index not in SKIP_IN_PATH: __path_parts = {"index": _quote(index)} __path = f'/_cat/indices/{__path_parts["index"]}' else: __path_parts = {} __path = "/_cat/indices" __query: t.Dict[str, t.Any] = {} if bytes is not None: __query["bytes"] = bytes if error_trace is not None: __query["error_trace"] = error_trace if expand_wildcards is not None: __query["expand_wildcards"] = expand_wildcards if filter_path is not None: __query["filter_path"] = filter_path if format is not None: __query["format"] = format if h is not None: __query["h"] = h if health is not None: __query["health"] = health if help is not None: __query["help"] = help if human is not None: __query["human"] = human if include_unloaded_segments is not None: __query["include_unloaded_segments"] = include_unloaded_segments if master_timeout is not None: __query["master_timeout"] = master_timeout if pretty is not None: __query["pretty"] = pretty if pri is not None: __query["pri"] = pri if s is not None: __query["s"] = s if time is not None: __query["time"] = time if v is not None: __query["v"] = v __headers = {"accept": "text/plain,application/json"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.indices", path_parts=__path_parts, ) @_rewrite_parameters() async def ml_data_frame_analytics( self, *, 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, h: t.Optional[ t.Union[ t.Sequence[ t.Union[ str, t.Literal[ "assignment_explanation", "create_time", "description", "dest_index", "failure_reason", "id", "model_memory_limit", "node.address", "node.ephemeral_id", "node.id", "node.name", "progress", "source_index", "state", "type", "version", ], ] ], t.Union[ str, t.Literal[ "assignment_explanation", "create_time", "description", "dest_index", "failure_reason", "id", "model_memory_limit", "node.address", "node.ephemeral_id", "node.id", "node.name", "progress", "source_index", "state", "type", "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[ "assignment_explanation", "create_time", "description", "dest_index", "failure_reason", "id", "model_memory_limit", "node.address", "node.ephemeral_id", "node.id", "node.name", "progress", "source_index", "state", "type", "version", ], ] ], t.Union[ str, t.Literal[ "assignment_explanation", "create_time", "description", "dest_index", "failure_reason", "id", "model_memory_limit", "node.address", "node.ephemeral_id", "node.id", "node.name", "progress", "source_index", "state", "type", "version", ], ], ] ] = None, time: t.Optional[ t.Union[str, t.Literal["d", "h", "m", "micros", "ms", "nanos", "s"]] ] = None, v: t.Optional[bool] = None, ) -> t.Union[ObjectApiResponse[t.Any], TextApiResponse]: """ .. raw:: html

Get data frame analytics jobs.

Get configuration and usage information about data frame analytics jobs.

IMPORTANT: CAT APIs are only intended for human consumption using the Kibana console or command line. They are not intended for use by applications. For application consumption, use the get data frame analytics jobs statistics API.

``_ :param id: The ID of the data frame analytics to fetch :param allow_no_match: Whether to ignore if a wildcard expression matches no configs. (This includes `_all` string or when no configs have been specified) :param bytes: The unit in which to display byte values :param format: Specifies the format to return the columnar data in, can be set to `text`, `json`, `cbor`, `yaml`, or `smile`. :param h: Comma-separated list of column names to display. :param help: When set to `true` will output available columns. This option can't be combined with any other query string option. :param s: Comma-separated list of column names or column aliases used to sort the response. :param time: Unit used to display time values. :param v: When set to `true` will enable verbose output. """ __path_parts: t.Dict[str, str] if id not in SKIP_IN_PATH: __path_parts = {"id": _quote(id)} __path = f'/_cat/ml/data_frame/analytics/{__path_parts["id"]}' else: __path_parts = {} __path = "/_cat/ml/data_frame/analytics" __query: t.Dict[str, t.Any] = {} if allow_no_match is not None: __query["allow_no_match"] = allow_no_match if bytes is not None: __query["bytes"] = bytes if error_trace is not None: __query["error_trace"] = error_trace if filter_path is not None: __query["filter_path"] = filter_path if format is not None: __query["format"] = format if h is not None: __query["h"] = h if help is not None: __query["help"] = help if human is not None: __query["human"] = human if pretty is not None: __query["pretty"] = pretty if s is not None: __query["s"] = s if time is not None: __query["time"] = time if v is not None: __query["v"] = v __headers = {"accept": "text/plain,application/json"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.ml_data_frame_analytics", path_parts=__path_parts, ) @_rewrite_parameters() async def ml_datafeeds( self, *, datafeed_id: t.Optional[str] = None, allow_no_match: t.Optional[bool] = None, error_trace: t.Optional[bool] = None, filter_path: t.Optional[t.Union[str, t.Sequence[str]]] = None, format: t.Optional[str] = None, h: t.Optional[ t.Union[ t.Sequence[ t.Union[ str, t.Literal[ "ae", "bc", "id", "na", "ne", "ni", "nn", "s", "sba", "sc", "seah", "st", ], ] ], t.Union[ str, t.Literal[ "ae", "bc", "id", "na", "ne", "ni", "nn", "s", "sba", "sc", "seah", "st", ], ], ] ] = 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[ "ae", "bc", "id", "na", "ne", "ni", "nn", "s", "sba", "sc", "seah", "st", ], ] ], t.Union[ str, t.Literal[ "ae", "bc", "id", "na", "ne", "ni", "nn", "s", "sba", "sc", "seah", "st", ], ], ] ] = None, time: t.Optional[ t.Union[str, t.Literal["d", "h", "m", "micros", "ms", "nanos", "s"]] ] = None, v: t.Optional[bool] = None, ) -> t.Union[ObjectApiResponse[t.Any], TextApiResponse]: """ .. raw:: html

Get datafeeds.

Get configuration and usage information about datafeeds. This API returns a maximum of 10,000 datafeeds. If the Elasticsearch security features are enabled, you must have monitor_ml, monitor, manage_ml, or manage cluster privileges to use this API.

IMPORTANT: CAT APIs are only intended for human consumption using the Kibana console or command line. They are not intended for use by applications. For application consumption, use the get datafeed statistics API.

``_ :param datafeed_id: A numerical character string that uniquely identifies the datafeed. :param allow_no_match: Specifies what to do when the request: * Contains wildcard expressions and there are no datafeeds that match. * Contains the `_all` string or no identifiers and there are no matches. * Contains wildcard expressions and there are only partial matches. If `true`, the API returns an empty datafeeds array when there are no matches and the subset of results when there are partial matches. If `false`, the API returns a 404 status code when there are no matches or only partial matches. :param format: Specifies the format to return the columnar data in, can be set to `text`, `json`, `cbor`, `yaml`, or `smile`. :param h: Comma-separated list of column names to display. :param help: When set to `true` will output available columns. This option can't be combined with any other query string option. :param s: Comma-separated list of column names or column aliases used to sort the response. :param time: The unit used to display time values. :param v: When set to `true` will enable verbose output. """ __path_parts: t.Dict[str, str] if datafeed_id not in SKIP_IN_PATH: __path_parts = {"datafeed_id": _quote(datafeed_id)} __path = f'/_cat/ml/datafeeds/{__path_parts["datafeed_id"]}' else: __path_parts = {} __path = "/_cat/ml/datafeeds" __query: t.Dict[str, t.Any] = {} if allow_no_match is not None: __query["allow_no_match"] = allow_no_match if error_trace is not None: __query["error_trace"] = error_trace if filter_path is not None: __query["filter_path"] = filter_path if format is not None: __query["format"] = format if h is not None: __query["h"] = h if help is not None: __query["help"] = help if human is not None: __query["human"] = human if pretty is not None: __query["pretty"] = pretty if s is not None: __query["s"] = s if time is not None: __query["time"] = time if v is not None: __query["v"] = v __headers = {"accept": "text/plain,application/json"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.ml_datafeeds", path_parts=__path_parts, ) @_rewrite_parameters() async def ml_jobs( self, *, job_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, h: t.Optional[ t.Union[ t.Sequence[ t.Union[ str, t.Literal[ "assignment_explanation", "buckets.count", "buckets.time.exp_avg", "buckets.time.exp_avg_hour", "buckets.time.max", "buckets.time.min", "buckets.time.total", "data.buckets", "data.earliest_record", "data.empty_buckets", "data.input_bytes", "data.input_fields", "data.input_records", "data.invalid_dates", "data.last", "data.last_empty_bucket", "data.last_sparse_bucket", "data.latest_record", "data.missing_fields", "data.out_of_order_timestamps", "data.processed_fields", "data.processed_records", "data.sparse_buckets", "forecasts.memory.avg", "forecasts.memory.max", "forecasts.memory.min", "forecasts.memory.total", "forecasts.records.avg", "forecasts.records.max", "forecasts.records.min", "forecasts.records.total", "forecasts.time.avg", "forecasts.time.max", "forecasts.time.min", "forecasts.time.total", "forecasts.total", "id", "model.bucket_allocation_failures", "model.by_fields", "model.bytes", "model.bytes_exceeded", "model.categorization_status", "model.categorized_doc_count", "model.dead_category_count", "model.failed_category_count", "model.frequent_category_count", "model.log_time", "model.memory_limit", "model.memory_status", "model.over_fields", "model.partition_fields", "model.rare_category_count", "model.timestamp", "model.total_category_count", "node.address", "node.ephemeral_id", "node.id", "node.name", "opened_time", "state", ], ] ], t.Union[ str, t.Literal[ "assignment_explanation", "buckets.count", "buckets.time.exp_avg", "buckets.time.exp_avg_hour", "buckets.time.max", "buckets.time.min", "buckets.time.total", "data.buckets", "data.earliest_record", "data.empty_buckets", "data.input_bytes", "data.input_fields", "data.input_records", "data.invalid_dates", "data.last", "data.last_empty_bucket", "data.last_sparse_bucket", "data.latest_record", "data.missing_fields", "data.out_of_order_timestamps", "data.processed_fields", "data.processed_records", "data.sparse_buckets", "forecasts.memory.avg", "forecasts.memory.max", "forecasts.memory.min", "forecasts.memory.total", "forecasts.records.avg", "forecasts.records.max", "forecasts.records.min", "forecasts.records.total", "forecasts.time.avg", "forecasts.time.max", "forecasts.time.min", "forecasts.time.total", "forecasts.total", "id", "model.bucket_allocation_failures", "model.by_fields", "model.bytes", "model.bytes_exceeded", "model.categorization_status", "model.categorized_doc_count", "model.dead_category_count", "model.failed_category_count", "model.frequent_category_count", "model.log_time", "model.memory_limit", "model.memory_status", "model.over_fields", "model.partition_fields", "model.rare_category_count", "model.timestamp", "model.total_category_count", "node.address", "node.ephemeral_id", "node.id", "node.name", "opened_time", "state", ], ], ] ] = 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[ "assignment_explanation", "buckets.count", "buckets.time.exp_avg", "buckets.time.exp_avg_hour", "buckets.time.max", "buckets.time.min", "buckets.time.total", "data.buckets", "data.earliest_record", "data.empty_buckets", "data.input_bytes", "data.input_fields", "data.input_records", "data.invalid_dates", "data.last", "data.last_empty_bucket", "data.last_sparse_bucket", "data.latest_record", "data.missing_fields", "data.out_of_order_timestamps", "data.processed_fields", "data.processed_records", "data.sparse_buckets", "forecasts.memory.avg", "forecasts.memory.max", "forecasts.memory.min", "forecasts.memory.total", "forecasts.records.avg", "forecasts.records.max", "forecasts.records.min", "forecasts.records.total", "forecasts.time.avg", "forecasts.time.max", "forecasts.time.min", "forecasts.time.total", "forecasts.total", "id", "model.bucket_allocation_failures", "model.by_fields", "model.bytes", "model.bytes_exceeded", "model.categorization_status", "model.categorized_doc_count", "model.dead_category_count", "model.failed_category_count", "model.frequent_category_count", "model.log_time", "model.memory_limit", "model.memory_status", "model.over_fields", "model.partition_fields", "model.rare_category_count", "model.timestamp", "model.total_category_count", "node.address", "node.ephemeral_id", "node.id", "node.name", "opened_time", "state", ], ] ], t.Union[ str, t.Literal[ "assignment_explanation", "buckets.count", "buckets.time.exp_avg", "buckets.time.exp_avg_hour", "buckets.time.max", "buckets.time.min", "buckets.time.total", "data.buckets", "data.earliest_record", "data.empty_buckets", "data.input_bytes", "data.input_fields", "data.input_records", "data.invalid_dates", "data.last", "data.last_empty_bucket", "data.last_sparse_bucket", "data.latest_record", "data.missing_fields", "data.out_of_order_timestamps", "data.processed_fields", "data.processed_records", "data.sparse_buckets", "forecasts.memory.avg", "forecasts.memory.max", "forecasts.memory.min", "forecasts.memory.total", "forecasts.records.avg", "forecasts.records.max", "forecasts.records.min", "forecasts.records.total", "forecasts.time.avg", "forecasts.time.max", "forecasts.time.min", "forecasts.time.total", "forecasts.total", "id", "model.bucket_allocation_failures", "model.by_fields", "model.bytes", "model.bytes_exceeded", "model.categorization_status", "model.categorized_doc_count", "model.dead_category_count", "model.failed_category_count", "model.frequent_category_count", "model.log_time", "model.memory_limit", "model.memory_status", "model.over_fields", "model.partition_fields", "model.rare_category_count", "model.timestamp", "model.total_category_count", "node.address", "node.ephemeral_id", "node.id", "node.name", "opened_time", "state", ], ], ] ] = None, time: t.Optional[ t.Union[str, t.Literal["d", "h", "m", "micros", "ms", "nanos", "s"]] ] = None, v: t.Optional[bool] = None, ) -> t.Union[ObjectApiResponse[t.Any], TextApiResponse]: """ .. raw:: html

Get anomaly detection jobs.

Get configuration and usage information for anomaly detection jobs. This API returns a maximum of 10,000 jobs. If the Elasticsearch security features are enabled, you must have monitor_ml, monitor, manage_ml, or manage cluster privileges to use this API.

IMPORTANT: CAT APIs are only intended for human consumption using the Kibana console or command line. They are not intended for use by applications. For application consumption, use the get anomaly detection job statistics API.

``_ :param job_id: Identifier for the anomaly detection job. :param allow_no_match: Specifies what to do when the request: * Contains wildcard expressions and there are no jobs that match. * Contains the `_all` string or no identifiers and there are no matches. * Contains wildcard expressions and there are only partial matches. If `true`, the API returns an empty jobs array when there are no matches and the subset of results when there are partial matches. If `false`, the API returns a 404 status code when there are no matches or only partial matches. :param bytes: The unit used to display byte values. :param format: Specifies the format to return the columnar data in, can be set to `text`, `json`, `cbor`, `yaml`, or `smile`. :param h: Comma-separated list of column names to display. :param help: When set to `true` will output available columns. This option can't be combined with any other query string option. :param s: Comma-separated list of column names or column aliases used to sort the response. :param time: The unit used to display time values. :param v: When set to `true` will enable verbose output. """ __path_parts: t.Dict[str, str] if job_id not in SKIP_IN_PATH: __path_parts = {"job_id": _quote(job_id)} __path = f'/_cat/ml/anomaly_detectors/{__path_parts["job_id"]}' else: __path_parts = {} __path = "/_cat/ml/anomaly_detectors" __query: t.Dict[str, t.Any] = {} if allow_no_match is not None: __query["allow_no_match"] = allow_no_match if bytes is not None: __query["bytes"] = bytes if error_trace is not None: __query["error_trace"] = error_trace if filter_path is not None: __query["filter_path"] = filter_path if format is not None: __query["format"] = format if h is not None: __query["h"] = h if help is not None: __query["help"] = help if human is not None: __query["human"] = human if pretty is not None: __query["pretty"] = pretty if s is not None: __query["s"] = s if time is not None: __query["time"] = time if v is not None: __query["v"] = v __headers = {"accept": "text/plain,application/json"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.ml_jobs", path_parts=__path_parts, ) @_rewrite_parameters( parameter_aliases={"from": "from_"}, ) async 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, ) -> t.Union[ObjectApiResponse[t.Any], TextApiResponse]: """ .. raw:: html

Get trained models.

Get configuration and usage information about inference trained models.

IMPORTANT: CAT APIs are only intended for human consumption using the Kibana console or command line. They are not intended for use by applications. For application consumption, use the get trained models statistics API.

``_ :param model_id: A unique identifier for the trained model. :param allow_no_match: Specifies what to do when the request: contains wildcard expressions and there are no models that match; contains the `_all` string or no identifiers and there are no matches; contains wildcard expressions and there are only partial matches. If `true`, the API returns an empty array when there are no matches and the subset of results when there are partial matches. If `false`, the API returns a 404 status code when there are no matches or only partial matches. :param bytes: The unit used to display byte values. :param format: Specifies the format to return the columnar data in, can be set to `text`, `json`, `cbor`, `yaml`, or `smile`. :param from_: Skips the specified number of transforms. :param h: A comma-separated list of column names to display. :param help: When set to `true` will output available columns. This option can't be combined with any other query string option. :param s: A comma-separated list of column names or aliases used to sort the response. :param size: The maximum number of transforms to display. :param time: Unit used to display time values. :param v: When set to `true` will enable verbose output. """ __path_parts: t.Dict[str, str] if model_id not in SKIP_IN_PATH: __path_parts = {"model_id": _quote(model_id)} __path = f'/_cat/ml/trained_models/{__path_parts["model_id"]}' else: __path_parts = {} __path = "/_cat/ml/trained_models" __query: t.Dict[str, t.Any] = {} if allow_no_match is not None: __query["allow_no_match"] = allow_no_match if bytes is not None: __query["bytes"] = bytes if error_trace is not None: __query["error_trace"] = error_trace if filter_path is not None: __query["filter_path"] = filter_path if format is not None: __query["format"] = format if from_ is not None: __query["from"] = from_ if h is not None: __query["h"] = h if help is not None: __query["help"] = help if human is not None: __query["human"] = human if pretty is not None: __query["pretty"] = pretty if s is not None: __query["s"] = s if size is not None: __query["size"] = size if time is not None: __query["time"] = time if v is not None: __query["v"] = v __headers = {"accept": "text/plain,application/json"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.ml_trained_models", path_parts=__path_parts, ) @_rewrite_parameters( parameter_aliases={"from": "from_"}, ) async def transforms( self, *, transform_id: t.Optional[str] = None, allow_no_match: t.Optional[bool] = 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[ "changes_last_detection_time", "checkpoint", "checkpoint_duration_time_exp_avg", "checkpoint_progress", "create_time", "delete_time", "description", "dest_index", "docs_per_second", "documents_deleted", "documents_indexed", "documents_processed", "frequency", "id", "index_failure", "index_time", "index_total", "indexed_documents_exp_avg", "last_search_time", "max_page_search_size", "pages_processed", "pipeline", "processed_documents_exp_avg", "processing_time", "reason", "search_failure", "search_time", "search_total", "source_index", "state", "transform_type", "trigger_count", "version", ], ] ], t.Union[ str, t.Literal[ "changes_last_detection_time", "checkpoint", "checkpoint_duration_time_exp_avg", "checkpoint_progress", "create_time", "delete_time", "description", "dest_index", "docs_per_second", "documents_deleted", "documents_indexed", "documents_processed", "frequency", "id", "index_failure", "index_time", "index_total", "indexed_documents_exp_avg", "last_search_time", "max_page_search_size", "pages_processed", "pipeline", "processed_documents_exp_avg", "processing_time", "reason", "search_failure", "search_time", "search_total", "source_index", "state", "transform_type", "trigger_count", "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[ "changes_last_detection_time", "checkpoint", "checkpoint_duration_time_exp_avg", "checkpoint_progress", "create_time", "delete_time", "description", "dest_index", "docs_per_second", "documents_deleted", "documents_indexed", "documents_processed", "frequency", "id", "index_failure", "index_time", "index_total", "indexed_documents_exp_avg", "last_search_time", "max_page_search_size", "pages_processed", "pipeline", "processed_documents_exp_avg", "processing_time", "reason", "search_failure", "search_time", "search_total", "source_index", "state", "transform_type", "trigger_count", "version", ], ] ], t.Union[ str, t.Literal[ "changes_last_detection_time", "checkpoint", "checkpoint_duration_time_exp_avg", "checkpoint_progress", "create_time", "delete_time", "description", "dest_index", "docs_per_second", "documents_deleted", "documents_indexed", "documents_processed", "frequency", "id", "index_failure", "index_time", "index_total", "indexed_documents_exp_avg", "last_search_time", "max_page_search_size", "pages_processed", "pipeline", "processed_documents_exp_avg", "processing_time", "reason", "search_failure", "search_time", "search_total", "source_index", "state", "transform_type", "trigger_count", "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, ) -> t.Union[ObjectApiResponse[t.Any], TextApiResponse]: """ .. raw:: html

Get transform information.

Get configuration and usage information about transforms.

CAT APIs are only intended for human consumption using the Kibana console or command line. They are not intended for use by applications. For application consumption, use the get transform statistics API.

``_ :param transform_id: A transform identifier or a wildcard expression. If you do not specify one of these options, the API returns information for all transforms. :param allow_no_match: Specifies what to do when the request: contains wildcard expressions and there are no transforms that match; contains the `_all` string or no identifiers and there are no matches; contains wildcard expressions and there are only partial matches. If `true`, it returns an empty transforms array when there are no matches and the subset of results when there are partial matches. If `false`, the request returns a 404 status code when there are no matches or only partial matches. :param format: Specifies the format to return the columnar data in, can be set to `text`, `json`, `cbor`, `yaml`, or `smile`. :param from_: Skips the specified number of transforms. :param h: Comma-separated list of column names to display. :param help: When set to `true` will output available columns. This option can't be combined with any other query string option. :param s: Comma-separated list of column names or column aliases used to sort the response. :param size: The maximum number of transforms to obtain. :param time: The unit used to display time values. :param v: When set to `true` will enable verbose output. """ __path_parts: t.Dict[str, str] if transform_id not in SKIP_IN_PATH: __path_parts = {"transform_id": _quote(transform_id)} __path = f'/_cat/transforms/{__path_parts["transform_id"]}' else: __path_parts = {} __path = "/_cat/transforms" __query: t.Dict[str, t.Any] = {} if allow_no_match is not None: __query["allow_no_match"] = allow_no_match if error_trace is not None: __query["error_trace"] = error_trace if filter_path is not None: __query["filter_path"] = filter_path if format is not None: __query["format"] = format if from_ is not None: __query["from"] = from_ if h is not None: __query["h"] = h if help is not None: __query["help"] = help if human is not None: __query["human"] = human if pretty is not None: __query["pretty"] = pretty if s is not None: __query["s"] = s if size is not None: __query["size"] = size if time is not None: __query["time"] = time if v is not None: __query["v"] = v __headers = {"accept": "text/plain,application/json"} return await self.perform_request( # type: ignore[return-value] "GET", __path, params=__query, headers=__headers, endpoint_id="cat.transforms", path_parts=__path_parts, )