LookoutEquipmentClient#
Index > LookoutEquipment > LookoutEquipmentClient
Auto-generated documentation for LookoutEquipment type annotations stubs module mypy-boto3-lookoutequipment.
LookoutEquipmentClient#
Type annotations and code completion for boto3.client("lookoutequipment")
.
boto3 documentation
# LookoutEquipmentClient usage example
from boto3.session import Session
from mypy_boto3_lookoutequipment.client import LookoutEquipmentClient
def get_lookoutequipment_client() -> LookoutEquipmentClient:
return Session().client("lookoutequipment")
Exceptions#
boto3
client exceptions are generated in runtime.
This class provides code completion for boto3.client("lookoutequipment").exceptions
structure.
# Exceptions.exceptions usage example
client = boto3.client("lookoutequipment")
try:
do_something(client)
except (
client.exceptions.AccessDeniedException,
client.exceptions.ClientError,
client.exceptions.ConflictException,
client.exceptions.InternalServerException,
client.exceptions.ResourceNotFoundException,
client.exceptions.ServiceQuotaExceededException,
client.exceptions.ThrottlingException,
client.exceptions.ValidationException,
) as e:
print(e)
# Exceptions.exceptions type checking example
from mypy_boto3_lookoutequipment.client import Exceptions
def handle_error(exc: Exceptions.AccessDeniedException) -> None:
...
Methods#
can_paginate#
Check if an operation can be paginated.
Type annotations and code completion for boto3.client("lookoutequipment").can_paginate
method.
boto3 documentation
# can_paginate method definition
def can_paginate(
self,
operation_name: str,
) -> bool:
...
close#
Closes underlying endpoint connections.
Type annotations and code completion for boto3.client("lookoutequipment").close
method.
boto3 documentation
# close method definition
def close(
self,
) -> None:
...
create_dataset#
Creates a container for a collection of data being ingested for analysis.
Type annotations and code completion for boto3.client("lookoutequipment").create_dataset
method.
boto3 documentation
# create_dataset method definition
def create_dataset(
self,
*,
DatasetName: str,
ClientToken: str,
DatasetSchema: DatasetSchemaTypeDef = ..., # (1)
ServerSideKmsKeyId: str = ...,
Tags: Sequence[TagTypeDef] = ..., # (2)
) -> CreateDatasetResponseTypeDef: # (3)
...
# create_dataset method usage example with argument unpacking
kwargs: CreateDatasetRequestRequestTypeDef = { # (1)
"DatasetName": ...,
"ClientToken": ...,
}
parent.create_dataset(**kwargs)
create_inference_scheduler#
Creates a scheduled inference.
Type annotations and code completion for boto3.client("lookoutequipment").create_inference_scheduler
method.
boto3 documentation
# create_inference_scheduler method definition
def create_inference_scheduler(
self,
*,
ModelName: str,
InferenceSchedulerName: str,
DataUploadFrequency: DataUploadFrequencyType, # (1)
DataInputConfiguration: InferenceInputConfigurationTypeDef, # (2)
DataOutputConfiguration: InferenceOutputConfigurationTypeDef, # (3)
RoleArn: str,
ClientToken: str,
DataDelayOffsetInMinutes: int = ...,
ServerSideKmsKeyId: str = ...,
Tags: Sequence[TagTypeDef] = ..., # (4)
) -> CreateInferenceSchedulerResponseTypeDef: # (5)
...
- See DataUploadFrequencyType
- See InferenceInputConfigurationTypeDef
- See InferenceOutputConfigurationTypeDef
- See TagTypeDef
- See CreateInferenceSchedulerResponseTypeDef
# create_inference_scheduler method usage example with argument unpacking
kwargs: CreateInferenceSchedulerRequestRequestTypeDef = { # (1)
"ModelName": ...,
"InferenceSchedulerName": ...,
"DataUploadFrequency": ...,
"DataInputConfiguration": ...,
"DataOutputConfiguration": ...,
"RoleArn": ...,
"ClientToken": ...,
}
parent.create_inference_scheduler(**kwargs)
create_label#
Creates a label for an event.
Type annotations and code completion for boto3.client("lookoutequipment").create_label
method.
boto3 documentation
# create_label method definition
def create_label(
self,
*,
LabelGroupName: str,
StartTime: Union[datetime, str],
EndTime: Union[datetime, str],
Rating: LabelRatingType, # (1)
ClientToken: str,
FaultCode: str = ...,
Notes: str = ...,
Equipment: str = ...,
) -> CreateLabelResponseTypeDef: # (2)
...
# create_label method usage example with argument unpacking
kwargs: CreateLabelRequestRequestTypeDef = { # (1)
"LabelGroupName": ...,
"StartTime": ...,
"EndTime": ...,
"Rating": ...,
"ClientToken": ...,
}
parent.create_label(**kwargs)
create_label_group#
Creates a group of labels.
Type annotations and code completion for boto3.client("lookoutequipment").create_label_group
method.
boto3 documentation
# create_label_group method definition
def create_label_group(
self,
*,
LabelGroupName: str,
ClientToken: str,
FaultCodes: Sequence[str] = ...,
Tags: Sequence[TagTypeDef] = ..., # (1)
) -> CreateLabelGroupResponseTypeDef: # (2)
...
# create_label_group method usage example with argument unpacking
kwargs: CreateLabelGroupRequestRequestTypeDef = { # (1)
"LabelGroupName": ...,
"ClientToken": ...,
}
parent.create_label_group(**kwargs)
create_model#
Creates a machine learning model for data inference.
Type annotations and code completion for boto3.client("lookoutequipment").create_model
method.
boto3 documentation
# create_model method definition
def create_model(
self,
*,
ModelName: str,
DatasetName: str,
ClientToken: str,
DatasetSchema: DatasetSchemaTypeDef = ..., # (1)
LabelsInputConfiguration: LabelsInputConfigurationTypeDef = ..., # (2)
TrainingDataStartTime: Union[datetime, str] = ...,
TrainingDataEndTime: Union[datetime, str] = ...,
EvaluationDataStartTime: Union[datetime, str] = ...,
EvaluationDataEndTime: Union[datetime, str] = ...,
RoleArn: str = ...,
DataPreProcessingConfiguration: DataPreProcessingConfigurationTypeDef = ..., # (3)
ServerSideKmsKeyId: str = ...,
Tags: Sequence[TagTypeDef] = ..., # (4)
OffCondition: str = ...,
) -> CreateModelResponseTypeDef: # (5)
...
- See DatasetSchemaTypeDef
- See LabelsInputConfigurationTypeDef
- See DataPreProcessingConfigurationTypeDef
- See TagTypeDef
- See CreateModelResponseTypeDef
# create_model method usage example with argument unpacking
kwargs: CreateModelRequestRequestTypeDef = { # (1)
"ModelName": ...,
"DatasetName": ...,
"ClientToken": ...,
}
parent.create_model(**kwargs)
create_retraining_scheduler#
Creates a retraining scheduler on the specified model.
Type annotations and code completion for boto3.client("lookoutequipment").create_retraining_scheduler
method.
boto3 documentation
# create_retraining_scheduler method definition
def create_retraining_scheduler(
self,
*,
ModelName: str,
RetrainingFrequency: str,
LookbackWindow: str,
ClientToken: str,
RetrainingStartDate: Union[datetime, str] = ...,
PromoteMode: ModelPromoteModeType = ..., # (1)
) -> CreateRetrainingSchedulerResponseTypeDef: # (2)
...
# create_retraining_scheduler method usage example with argument unpacking
kwargs: CreateRetrainingSchedulerRequestRequestTypeDef = { # (1)
"ModelName": ...,
"RetrainingFrequency": ...,
"LookbackWindow": ...,
"ClientToken": ...,
}
parent.create_retraining_scheduler(**kwargs)
delete_dataset#
Deletes a dataset and associated artifacts.
Type annotations and code completion for boto3.client("lookoutequipment").delete_dataset
method.
boto3 documentation
# delete_dataset method definition
def delete_dataset(
self,
*,
DatasetName: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_dataset method usage example with argument unpacking
kwargs: DeleteDatasetRequestRequestTypeDef = { # (1)
"DatasetName": ...,
}
parent.delete_dataset(**kwargs)
delete_inference_scheduler#
Deletes an inference scheduler that has been set up.
Type annotations and code completion for boto3.client("lookoutequipment").delete_inference_scheduler
method.
boto3 documentation
# delete_inference_scheduler method definition
def delete_inference_scheduler(
self,
*,
InferenceSchedulerName: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_inference_scheduler method usage example with argument unpacking
kwargs: DeleteInferenceSchedulerRequestRequestTypeDef = { # (1)
"InferenceSchedulerName": ...,
}
parent.delete_inference_scheduler(**kwargs)
delete_label#
Deletes a label.
Type annotations and code completion for boto3.client("lookoutequipment").delete_label
method.
boto3 documentation
# delete_label method definition
def delete_label(
self,
*,
LabelGroupName: str,
LabelId: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_label method usage example with argument unpacking
kwargs: DeleteLabelRequestRequestTypeDef = { # (1)
"LabelGroupName": ...,
"LabelId": ...,
}
parent.delete_label(**kwargs)
delete_label_group#
Deletes a group of labels.
Type annotations and code completion for boto3.client("lookoutequipment").delete_label_group
method.
boto3 documentation
# delete_label_group method definition
def delete_label_group(
self,
*,
LabelGroupName: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_label_group method usage example with argument unpacking
kwargs: DeleteLabelGroupRequestRequestTypeDef = { # (1)
"LabelGroupName": ...,
}
parent.delete_label_group(**kwargs)
delete_model#
Deletes a machine learning model currently available for Amazon Lookout for Equipment.
Type annotations and code completion for boto3.client("lookoutequipment").delete_model
method.
boto3 documentation
# delete_model method definition
def delete_model(
self,
*,
ModelName: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_model method usage example with argument unpacking
kwargs: DeleteModelRequestRequestTypeDef = { # (1)
"ModelName": ...,
}
parent.delete_model(**kwargs)
delete_resource_policy#
Deletes the resource policy attached to the resource.
Type annotations and code completion for boto3.client("lookoutequipment").delete_resource_policy
method.
boto3 documentation
# delete_resource_policy method definition
def delete_resource_policy(
self,
*,
ResourceArn: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_resource_policy method usage example with argument unpacking
kwargs: DeleteResourcePolicyRequestRequestTypeDef = { # (1)
"ResourceArn": ...,
}
parent.delete_resource_policy(**kwargs)
delete_retraining_scheduler#
Deletes a retraining scheduler from a model.
Type annotations and code completion for boto3.client("lookoutequipment").delete_retraining_scheduler
method.
boto3 documentation
# delete_retraining_scheduler method definition
def delete_retraining_scheduler(
self,
*,
ModelName: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_retraining_scheduler method usage example with argument unpacking
kwargs: DeleteRetrainingSchedulerRequestRequestTypeDef = { # (1)
"ModelName": ...,
}
parent.delete_retraining_scheduler(**kwargs)
describe_data_ingestion_job#
Provides information on a specific data ingestion job such as creation time, dataset ARN, and status.
Type annotations and code completion for boto3.client("lookoutequipment").describe_data_ingestion_job
method.
boto3 documentation
# describe_data_ingestion_job method definition
def describe_data_ingestion_job(
self,
*,
JobId: str,
) -> DescribeDataIngestionJobResponseTypeDef: # (1)
...
# describe_data_ingestion_job method usage example with argument unpacking
kwargs: DescribeDataIngestionJobRequestRequestTypeDef = { # (1)
"JobId": ...,
}
parent.describe_data_ingestion_job(**kwargs)
describe_dataset#
Provides a JSON description of the data in each time series dataset, including names, column names, and data types.
Type annotations and code completion for boto3.client("lookoutequipment").describe_dataset
method.
boto3 documentation
# describe_dataset method definition
def describe_dataset(
self,
*,
DatasetName: str,
) -> DescribeDatasetResponseTypeDef: # (1)
...
# describe_dataset method usage example with argument unpacking
kwargs: DescribeDatasetRequestRequestTypeDef = { # (1)
"DatasetName": ...,
}
parent.describe_dataset(**kwargs)
describe_inference_scheduler#
Specifies information about the inference scheduler being used, including name, model, status, and associated metadata See also: AWS API Documentation.
Type annotations and code completion for boto3.client("lookoutequipment").describe_inference_scheduler
method.
boto3 documentation
# describe_inference_scheduler method definition
def describe_inference_scheduler(
self,
*,
InferenceSchedulerName: str,
) -> DescribeInferenceSchedulerResponseTypeDef: # (1)
...
# describe_inference_scheduler method usage example with argument unpacking
kwargs: DescribeInferenceSchedulerRequestRequestTypeDef = { # (1)
"InferenceSchedulerName": ...,
}
parent.describe_inference_scheduler(**kwargs)
describe_label#
Returns the name of the label.
Type annotations and code completion for boto3.client("lookoutequipment").describe_label
method.
boto3 documentation
# describe_label method definition
def describe_label(
self,
*,
LabelGroupName: str,
LabelId: str,
) -> DescribeLabelResponseTypeDef: # (1)
...
# describe_label method usage example with argument unpacking
kwargs: DescribeLabelRequestRequestTypeDef = { # (1)
"LabelGroupName": ...,
"LabelId": ...,
}
parent.describe_label(**kwargs)
describe_label_group#
Returns information about the label group.
Type annotations and code completion for boto3.client("lookoutequipment").describe_label_group
method.
boto3 documentation
# describe_label_group method definition
def describe_label_group(
self,
*,
LabelGroupName: str,
) -> DescribeLabelGroupResponseTypeDef: # (1)
...
# describe_label_group method usage example with argument unpacking
kwargs: DescribeLabelGroupRequestRequestTypeDef = { # (1)
"LabelGroupName": ...,
}
parent.describe_label_group(**kwargs)
describe_model#
Provides a JSON containing the overall information about a specific machine learning model, including model name and ARN, dataset, training and evaluation information, status, and so on.
Type annotations and code completion for boto3.client("lookoutequipment").describe_model
method.
boto3 documentation
# describe_model method definition
def describe_model(
self,
*,
ModelName: str,
) -> DescribeModelResponseTypeDef: # (1)
...
# describe_model method usage example with argument unpacking
kwargs: DescribeModelRequestRequestTypeDef = { # (1)
"ModelName": ...,
}
parent.describe_model(**kwargs)
describe_model_version#
Retrieves information about a specific machine learning model version.
Type annotations and code completion for boto3.client("lookoutequipment").describe_model_version
method.
boto3 documentation
# describe_model_version method definition
def describe_model_version(
self,
*,
ModelName: str,
ModelVersion: int,
) -> DescribeModelVersionResponseTypeDef: # (1)
...
# describe_model_version method usage example with argument unpacking
kwargs: DescribeModelVersionRequestRequestTypeDef = { # (1)
"ModelName": ...,
"ModelVersion": ...,
}
parent.describe_model_version(**kwargs)
describe_resource_policy#
Provides the details of a resource policy attached to a resource.
Type annotations and code completion for boto3.client("lookoutequipment").describe_resource_policy
method.
boto3 documentation
# describe_resource_policy method definition
def describe_resource_policy(
self,
*,
ResourceArn: str,
) -> DescribeResourcePolicyResponseTypeDef: # (1)
...
# describe_resource_policy method usage example with argument unpacking
kwargs: DescribeResourcePolicyRequestRequestTypeDef = { # (1)
"ResourceArn": ...,
}
parent.describe_resource_policy(**kwargs)
describe_retraining_scheduler#
Provides a description of the retraining scheduler, including information such as the model name and retraining parameters.
Type annotations and code completion for boto3.client("lookoutequipment").describe_retraining_scheduler
method.
boto3 documentation
# describe_retraining_scheduler method definition
def describe_retraining_scheduler(
self,
*,
ModelName: str,
) -> DescribeRetrainingSchedulerResponseTypeDef: # (1)
...
# describe_retraining_scheduler method usage example with argument unpacking
kwargs: DescribeRetrainingSchedulerRequestRequestTypeDef = { # (1)
"ModelName": ...,
}
parent.describe_retraining_scheduler(**kwargs)
generate_presigned_url#
Generate a presigned url given a client, its method, and arguments.
Type annotations and code completion for boto3.client("lookoutequipment").generate_presigned_url
method.
boto3 documentation
# generate_presigned_url method definition
def generate_presigned_url(
self,
ClientMethod: str,
Params: Mapping[str, Any] = ...,
ExpiresIn: int = 3600,
HttpMethod: str = ...,
) -> str:
...
import_dataset#
Imports a dataset.
Type annotations and code completion for boto3.client("lookoutequipment").import_dataset
method.
boto3 documentation
# import_dataset method definition
def import_dataset(
self,
*,
SourceDatasetArn: str,
ClientToken: str,
DatasetName: str = ...,
ServerSideKmsKeyId: str = ...,
Tags: Sequence[TagTypeDef] = ..., # (1)
) -> ImportDatasetResponseTypeDef: # (2)
...
# import_dataset method usage example with argument unpacking
kwargs: ImportDatasetRequestRequestTypeDef = { # (1)
"SourceDatasetArn": ...,
"ClientToken": ...,
}
parent.import_dataset(**kwargs)
import_model_version#
Imports a model that has been trained successfully.
Type annotations and code completion for boto3.client("lookoutequipment").import_model_version
method.
boto3 documentation
# import_model_version method definition
def import_model_version(
self,
*,
SourceModelVersionArn: str,
DatasetName: str,
ClientToken: str,
ModelName: str = ...,
LabelsInputConfiguration: LabelsInputConfigurationTypeDef = ..., # (1)
RoleArn: str = ...,
ServerSideKmsKeyId: str = ...,
Tags: Sequence[TagTypeDef] = ..., # (2)
InferenceDataImportStrategy: InferenceDataImportStrategyType = ..., # (3)
) -> ImportModelVersionResponseTypeDef: # (4)
...
- See LabelsInputConfigurationTypeDef
- See TagTypeDef
- See InferenceDataImportStrategyType
- See ImportModelVersionResponseTypeDef
# import_model_version method usage example with argument unpacking
kwargs: ImportModelVersionRequestRequestTypeDef = { # (1)
"SourceModelVersionArn": ...,
"DatasetName": ...,
"ClientToken": ...,
}
parent.import_model_version(**kwargs)