elasticsearch/_async/client/cat.py [1496:1673]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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"}
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
elasticsearch/_sync/client/cat.py [1496:1673]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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"}
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