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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)
    ...
  1. See DatasetSchemaTypeDef
  2. See TagTypeDef
  3. See CreateDatasetResponseTypeDef 
# create_dataset method usage example with argument unpacking

kwargs: CreateDatasetRequestRequestTypeDef = {  # (1)
    "DatasetName": ...,
    "ClientToken": ...,
}

parent.create_dataset(**kwargs)
  1. See CreateDatasetRequestRequestTypeDef

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)
    ...
  1. See DataUploadFrequencyType
  2. See InferenceInputConfigurationTypeDef
  3. See InferenceOutputConfigurationTypeDef
  4. See TagTypeDef
  5. 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)
  1. See CreateInferenceSchedulerRequestRequestTypeDef

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: TimestampTypeDef,
    EndTime: TimestampTypeDef,
    Rating: LabelRatingType,  # (1)
    ClientToken: str,
    FaultCode: str = ...,
    Notes: str = ...,
    Equipment: str = ...,
) -> CreateLabelResponseTypeDef:  # (2)
    ...
  1. See LabelRatingType
  2. See CreateLabelResponseTypeDef 
# create_label method usage example with argument unpacking

kwargs: CreateLabelRequestRequestTypeDef = {  # (1)
    "LabelGroupName": ...,
    "StartTime": ...,
    "EndTime": ...,
    "Rating": ...,
    "ClientToken": ...,
}

parent.create_label(**kwargs)
  1. See CreateLabelRequestRequestTypeDef

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)
    ...
  1. See TagTypeDef
  2. See CreateLabelGroupResponseTypeDef 
# create_label_group method usage example with argument unpacking

kwargs: CreateLabelGroupRequestRequestTypeDef = {  # (1)
    "LabelGroupName": ...,
    "ClientToken": ...,
}

parent.create_label_group(**kwargs)
  1. See CreateLabelGroupRequestRequestTypeDef

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: TimestampTypeDef = ...,
    TrainingDataEndTime: TimestampTypeDef = ...,
    EvaluationDataStartTime: TimestampTypeDef = ...,
    EvaluationDataEndTime: TimestampTypeDef = ...,
    RoleArn: str = ...,
    DataPreProcessingConfiguration: DataPreProcessingConfigurationTypeDef = ...,  # (3)
    ServerSideKmsKeyId: str = ...,
    Tags: Sequence[TagTypeDef] = ...,  # (4)
    OffCondition: str = ...,
    ModelDiagnosticsOutputConfiguration: ModelDiagnosticsOutputConfigurationTypeDef = ...,  # (5)
) -> CreateModelResponseTypeDef:  # (6)
    ...
  1. See DatasetSchemaTypeDef
  2. See LabelsInputConfigurationTypeDef
  3. See DataPreProcessingConfigurationTypeDef
  4. See TagTypeDef
  5. See ModelDiagnosticsOutputConfigurationTypeDef
  6. See CreateModelResponseTypeDef 
# create_model method usage example with argument unpacking

kwargs: CreateModelRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
    "DatasetName": ...,
    "ClientToken": ...,
}

parent.create_model(**kwargs)
  1. See CreateModelRequestRequestTypeDef

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: TimestampTypeDef = ...,
    PromoteMode: ModelPromoteModeType = ...,  # (1)
) -> CreateRetrainingSchedulerResponseTypeDef:  # (2)
    ...
  1. See ModelPromoteModeType
  2. See CreateRetrainingSchedulerResponseTypeDef 
# create_retraining_scheduler method usage example with argument unpacking

kwargs: CreateRetrainingSchedulerRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
    "RetrainingFrequency": ...,
    "LookbackWindow": ...,
    "ClientToken": ...,
}

parent.create_retraining_scheduler(**kwargs)
  1. See CreateRetrainingSchedulerRequestRequestTypeDef

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)
    ...
  1. See EmptyResponseMetadataTypeDef 
# delete_dataset method usage example with argument unpacking

kwargs: DeleteDatasetRequestRequestTypeDef = {  # (1)
    "DatasetName": ...,
}

parent.delete_dataset(**kwargs)
  1. See DeleteDatasetRequestRequestTypeDef

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)
    ...
  1. See EmptyResponseMetadataTypeDef 
# delete_inference_scheduler method usage example with argument unpacking

kwargs: DeleteInferenceSchedulerRequestRequestTypeDef = {  # (1)
    "InferenceSchedulerName": ...,
}

parent.delete_inference_scheduler(**kwargs)
  1. See DeleteInferenceSchedulerRequestRequestTypeDef

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)
    ...
  1. See EmptyResponseMetadataTypeDef 
# delete_label method usage example with argument unpacking

kwargs: DeleteLabelRequestRequestTypeDef = {  # (1)
    "LabelGroupName": ...,
    "LabelId": ...,
}

parent.delete_label(**kwargs)
  1. See DeleteLabelRequestRequestTypeDef

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)
    ...
  1. See EmptyResponseMetadataTypeDef 
# delete_label_group method usage example with argument unpacking

kwargs: DeleteLabelGroupRequestRequestTypeDef = {  # (1)
    "LabelGroupName": ...,
}

parent.delete_label_group(**kwargs)
  1. See DeleteLabelGroupRequestRequestTypeDef

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)
    ...
  1. See EmptyResponseMetadataTypeDef 
# delete_model method usage example with argument unpacking

kwargs: DeleteModelRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
}

parent.delete_model(**kwargs)
  1. See DeleteModelRequestRequestTypeDef

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)
    ...
  1. See EmptyResponseMetadataTypeDef 
# delete_resource_policy method usage example with argument unpacking

kwargs: DeleteResourcePolicyRequestRequestTypeDef = {  # (1)
    "ResourceArn": ...,
}

parent.delete_resource_policy(**kwargs)
  1. See DeleteResourcePolicyRequestRequestTypeDef

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)
    ...
  1. See EmptyResponseMetadataTypeDef 
# delete_retraining_scheduler method usage example with argument unpacking

kwargs: DeleteRetrainingSchedulerRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
}

parent.delete_retraining_scheduler(**kwargs)
  1. See DeleteRetrainingSchedulerRequestRequestTypeDef

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)
    ...
  1. See DescribeDataIngestionJobResponseTypeDef 
# describe_data_ingestion_job method usage example with argument unpacking

kwargs: DescribeDataIngestionJobRequestRequestTypeDef = {  # (1)
    "JobId": ...,
}

parent.describe_data_ingestion_job(**kwargs)
  1. See DescribeDataIngestionJobRequestRequestTypeDef

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)
    ...
  1. See DescribeDatasetResponseTypeDef 
# describe_dataset method usage example with argument unpacking

kwargs: DescribeDatasetRequestRequestTypeDef = {  # (1)
    "DatasetName": ...,
}

parent.describe_dataset(**kwargs)
  1. See DescribeDatasetRequestRequestTypeDef

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)
    ...
  1. See DescribeInferenceSchedulerResponseTypeDef 
# describe_inference_scheduler method usage example with argument unpacking

kwargs: DescribeInferenceSchedulerRequestRequestTypeDef = {  # (1)
    "InferenceSchedulerName": ...,
}

parent.describe_inference_scheduler(**kwargs)
  1. See DescribeInferenceSchedulerRequestRequestTypeDef

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)
    ...
  1. See DescribeLabelResponseTypeDef 
# describe_label method usage example with argument unpacking

kwargs: DescribeLabelRequestRequestTypeDef = {  # (1)
    "LabelGroupName": ...,
    "LabelId": ...,
}

parent.describe_label(**kwargs)
  1. See DescribeLabelRequestRequestTypeDef

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)
    ...
  1. See DescribeLabelGroupResponseTypeDef 
# describe_label_group method usage example with argument unpacking

kwargs: DescribeLabelGroupRequestRequestTypeDef = {  # (1)
    "LabelGroupName": ...,
}

parent.describe_label_group(**kwargs)
  1. See DescribeLabelGroupRequestRequestTypeDef

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)
    ...
  1. See DescribeModelResponseTypeDef 
# describe_model method usage example with argument unpacking

kwargs: DescribeModelRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
}

parent.describe_model(**kwargs)
  1. See DescribeModelRequestRequestTypeDef

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)
    ...
  1. See DescribeModelVersionResponseTypeDef 
# describe_model_version method usage example with argument unpacking

kwargs: DescribeModelVersionRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
    "ModelVersion": ...,
}

parent.describe_model_version(**kwargs)
  1. See DescribeModelVersionRequestRequestTypeDef

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)
    ...
  1. See DescribeResourcePolicyResponseTypeDef 
# describe_resource_policy method usage example with argument unpacking

kwargs: DescribeResourcePolicyRequestRequestTypeDef = {  # (1)
    "ResourceArn": ...,
}

parent.describe_resource_policy(**kwargs)
  1. See DescribeResourcePolicyRequestRequestTypeDef

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)
    ...
  1. See DescribeRetrainingSchedulerResponseTypeDef 
# describe_retraining_scheduler method usage example with argument unpacking

kwargs: DescribeRetrainingSchedulerRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
}

parent.describe_retraining_scheduler(**kwargs)
  1. See DescribeRetrainingSchedulerRequestRequestTypeDef

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)
    ...
  1. See TagTypeDef
  2. See ImportDatasetResponseTypeDef 
# import_dataset method usage example with argument unpacking

kwargs: ImportDatasetRequestRequestTypeDef = {  # (1)
    "SourceDatasetArn": ...,
    "ClientToken": ...,
}

parent.import_dataset(**kwargs)
  1. See ImportDatasetRequestRequestTypeDef

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)
    ...
  1. See LabelsInputConfigurationTypeDef
  2. See TagTypeDef
  3. See InferenceDataImportStrategyType
  4. See ImportModelVersionResponseTypeDef 
# import_model_version method usage example with argument unpacking

kwargs: ImportModelVersionRequestRequestTypeDef = {  # (1)
    "SourceModelVersionArn": ...,
    "DatasetName": ...,
    "ClientToken": ...,
}

parent.import_model_version(**kwargs)
  1. See ImportModelVersionRequestRequestTypeDef

list_data_ingestion_jobs#

Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.

Type annotations and code completion for boto3.client("lookoutequipment").list_data_ingestion_jobs method. boto3 documentation

# list_data_ingestion_jobs method definition

def list_data_ingestion_jobs(
    self,
    *,
    DatasetName: str = ...,
    NextToken: str = ...,
    MaxResults: int = ...,
    Status: IngestionJobStatusType = ...,  # (1)
) -> ListDataIngestionJobsResponseTypeDef:  # (2)
    ...
  1. See IngestionJobStatusType
  2. See ListDataIngestionJobsResponseTypeDef 
# list_data_ingestion_jobs method usage example with argument unpacking

kwargs: ListDataIngestionJobsRequestRequestTypeDef = {  # (1)
    "DatasetName": ...,
}

parent.list_data_ingestion_jobs(**kwargs)
  1. See ListDataIngestionJobsRequestRequestTypeDef

list_datasets#

Lists all datasets currently available in your account, filtering on the dataset name.

Type annotations and code completion for boto3.client("lookoutequipment").list_datasets method. boto3 documentation

# list_datasets method definition

def list_datasets(
    self,
    *,
    NextToken: str = ...,
    MaxResults: int = ...,
    DatasetNameBeginsWith: str = ...,
) -> ListDatasetsResponseTypeDef:  # (1)
    ...
  1. See ListDatasetsResponseTypeDef 
# list_datasets method usage example with argument unpacking

kwargs: ListDatasetsRequestRequestTypeDef = {  # (1)
    "NextToken": ...,
}

parent.list_datasets(**kwargs)
  1. See ListDatasetsRequestRequestTypeDef

list_inference_events#

Lists all inference events that have been found for the specified inference scheduler.

Type annotations and code completion for boto3.client("lookoutequipment").list_inference_events method. boto3 documentation

# list_inference_events method definition

def list_inference_events(
    self,
    *,
    InferenceSchedulerName: str,
    IntervalStartTime: TimestampTypeDef,
    IntervalEndTime: TimestampTypeDef,
    NextToken: str = ...,
    MaxResults: int = ...,
) -> ListInferenceEventsResponseTypeDef:  # (1)
    ...
  1. See ListInferenceEventsResponseTypeDef 
# list_inference_events method usage example with argument unpacking

kwargs: ListInferenceEventsRequestRequestTypeDef = {  # (1)
    "InferenceSchedulerName": ...,
    "IntervalStartTime": ...,
    "IntervalEndTime": ...,
}

parent.list_inference_events(**kwargs)
  1. See ListInferenceEventsRequestRequestTypeDef

list_inference_executions#

Lists all inference executions that have been performed by the specified inference scheduler.

Type annotations and code completion for boto3.client("lookoutequipment").list_inference_executions method. boto3 documentation

# list_inference_executions method definition

def list_inference_executions(
    self,
    *,
    InferenceSchedulerName: str,
    NextToken: str = ...,
    MaxResults: int = ...,
    DataStartTimeAfter: TimestampTypeDef = ...,
    DataEndTimeBefore: TimestampTypeDef = ...,
    Status: InferenceExecutionStatusType = ...,  # (1)
) -> ListInferenceExecutionsResponseTypeDef:  # (2)
    ...
  1. See InferenceExecutionStatusType
  2. See ListInferenceExecutionsResponseTypeDef 
# list_inference_executions method usage example with argument unpacking

kwargs: ListInferenceExecutionsRequestRequestTypeDef = {  # (1)
    "InferenceSchedulerName": ...,
}

parent.list_inference_executions(**kwargs)
  1. See ListInferenceExecutionsRequestRequestTypeDef

list_inference_schedulers#

Retrieves a list of all inference schedulers currently available for your account.

Type annotations and code completion for boto3.client("lookoutequipment").list_inference_schedulers method. boto3 documentation

# list_inference_schedulers method definition

def list_inference_schedulers(
    self,
    *,
    NextToken: str = ...,
    MaxResults: int = ...,
    InferenceSchedulerNameBeginsWith: str = ...,
    ModelName: str = ...,
    Status: InferenceSchedulerStatusType = ...,  # (1)
) -> ListInferenceSchedulersResponseTypeDef:  # (2)
    ...
  1. See InferenceSchedulerStatusType
  2. See ListInferenceSchedulersResponseTypeDef 
# list_inference_schedulers method usage example with argument unpacking

kwargs: ListInferenceSchedulersRequestRequestTypeDef = {  # (1)
    "NextToken": ...,
}

parent.list_inference_schedulers(**kwargs)
  1. See ListInferenceSchedulersRequestRequestTypeDef

list_label_groups#

Returns a list of the label groups.

Type annotations and code completion for boto3.client("lookoutequipment").list_label_groups method. boto3 documentation

# list_label_groups method definition

def list_label_groups(
    self,
    *,
    LabelGroupNameBeginsWith: str = ...,
    NextToken: str = ...,
    MaxResults: int = ...,
) -> ListLabelGroupsResponseTypeDef:  # (1)
    ...
  1. See ListLabelGroupsResponseTypeDef 
# list_label_groups method usage example with argument unpacking

kwargs: ListLabelGroupsRequestRequestTypeDef = {  # (1)
    "LabelGroupNameBeginsWith": ...,
}

parent.list_label_groups(**kwargs)
  1. See ListLabelGroupsRequestRequestTypeDef

list_labels#

Provides a list of labels.

Type annotations and code completion for boto3.client("lookoutequipment").list_labels method. boto3 documentation

# list_labels method definition

def list_labels(
    self,
    *,
    LabelGroupName: str,
    IntervalStartTime: TimestampTypeDef = ...,
    IntervalEndTime: TimestampTypeDef = ...,
    FaultCode: str = ...,
    Equipment: str = ...,
    NextToken: str = ...,
    MaxResults: int = ...,
) -> ListLabelsResponseTypeDef:  # (1)
    ...
  1. See ListLabelsResponseTypeDef 
# list_labels method usage example with argument unpacking

kwargs: ListLabelsRequestRequestTypeDef = {  # (1)
    "LabelGroupName": ...,
}

parent.list_labels(**kwargs)
  1. See ListLabelsRequestRequestTypeDef

list_model_versions#

Generates a list of all model versions for a given model, including the model version, model version ARN, and status.

Type annotations and code completion for boto3.client("lookoutequipment").list_model_versions method. boto3 documentation

# list_model_versions method definition

def list_model_versions(
    self,
    *,
    ModelName: str,
    NextToken: str = ...,
    MaxResults: int = ...,
    Status: ModelVersionStatusType = ...,  # (1)
    SourceType: ModelVersionSourceTypeType = ...,  # (2)
    CreatedAtEndTime: TimestampTypeDef = ...,
    CreatedAtStartTime: TimestampTypeDef = ...,
    MaxModelVersion: int = ...,
    MinModelVersion: int = ...,
) -> ListModelVersionsResponseTypeDef:  # (3)
    ...
  1. See ModelVersionStatusType
  2. See ModelVersionSourceTypeType
  3. See ListModelVersionsResponseTypeDef 
# list_model_versions method usage example with argument unpacking

kwargs: ListModelVersionsRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
}

parent.list_model_versions(**kwargs)
  1. See ListModelVersionsRequestRequestTypeDef

list_models#

Generates a list of all models in the account, including model name and ARN, dataset, and status.

Type annotations and code completion for boto3.client("lookoutequipment").list_models method. boto3 documentation

# list_models method definition

def list_models(
    self,
    *,
    NextToken: str = ...,
    MaxResults: int = ...,
    Status: ModelStatusType = ...,  # (1)
    ModelNameBeginsWith: str = ...,
    DatasetNameBeginsWith: str = ...,
) -> ListModelsResponseTypeDef:  # (2)
    ...
  1. See ModelStatusType
  2. See ListModelsResponseTypeDef 
# list_models method usage example with argument unpacking

kwargs: ListModelsRequestRequestTypeDef = {  # (1)
    "NextToken": ...,
}

parent.list_models(**kwargs)
  1. See ListModelsRequestRequestTypeDef

list_retraining_schedulers#

Lists all retraining schedulers in your account, filtering by model name prefix and status.

Type annotations and code completion for boto3.client("lookoutequipment").list_retraining_schedulers method. boto3 documentation

# list_retraining_schedulers method definition

def list_retraining_schedulers(
    self,
    *,
    ModelNameBeginsWith: str = ...,
    Status: RetrainingSchedulerStatusType = ...,  # (1)
    NextToken: str = ...,
    MaxResults: int = ...,
) -> ListRetrainingSchedulersResponseTypeDef:  # (2)
    ...
  1. See RetrainingSchedulerStatusType
  2. See ListRetrainingSchedulersResponseTypeDef 
# list_retraining_schedulers method usage example with argument unpacking

kwargs: ListRetrainingSchedulersRequestRequestTypeDef = {  # (1)
    "ModelNameBeginsWith": ...,
}

parent.list_retraining_schedulers(**kwargs)
  1. See ListRetrainingSchedulersRequestRequestTypeDef

list_sensor_statistics#

Lists statistics about the data collected for each of the sensors that have been successfully ingested in the particular dataset.

Type annotations and code completion for boto3.client("lookoutequipment").list_sensor_statistics method. boto3 documentation

# list_sensor_statistics method definition

def list_sensor_statistics(
    self,
    *,
    DatasetName: str,
    IngestionJobId: str = ...,
    MaxResults: int = ...,
    NextToken: str = ...,
) -> ListSensorStatisticsResponseTypeDef:  # (1)
    ...
  1. See ListSensorStatisticsResponseTypeDef 
# list_sensor_statistics method usage example with argument unpacking

kwargs: ListSensorStatisticsRequestRequestTypeDef = {  # (1)
    "DatasetName": ...,
}

parent.list_sensor_statistics(**kwargs)
  1. See ListSensorStatisticsRequestRequestTypeDef

list_tags_for_resource#

Lists all the tags for a specified resource, including key and value.

Type annotations and code completion for boto3.client("lookoutequipment").list_tags_for_resource method. boto3 documentation

# list_tags_for_resource method definition

def list_tags_for_resource(
    self,
    *,
    ResourceArn: str,
) -> ListTagsForResourceResponseTypeDef:  # (1)
    ...
  1. See ListTagsForResourceResponseTypeDef 
# list_tags_for_resource method usage example with argument unpacking

kwargs: ListTagsForResourceRequestRequestTypeDef = {  # (1)
    "ResourceArn": ...,
}

parent.list_tags_for_resource(**kwargs)
  1. See ListTagsForResourceRequestRequestTypeDef

put_resource_policy#

Creates a resource control policy for a given resource.

Type annotations and code completion for boto3.client("lookoutequipment").put_resource_policy method. boto3 documentation

# put_resource_policy method definition

def put_resource_policy(
    self,
    *,
    ResourceArn: str,
    ResourcePolicy: str,
    ClientToken: str,
    PolicyRevisionId: str = ...,
) -> PutResourcePolicyResponseTypeDef:  # (1)
    ...
  1. See PutResourcePolicyResponseTypeDef 
# put_resource_policy method usage example with argument unpacking

kwargs: PutResourcePolicyRequestRequestTypeDef = {  # (1)
    "ResourceArn": ...,
    "ResourcePolicy": ...,
    "ClientToken": ...,
}

parent.put_resource_policy(**kwargs)
  1. See PutResourcePolicyRequestRequestTypeDef

start_data_ingestion_job#

Starts a data ingestion job.

Type annotations and code completion for boto3.client("lookoutequipment").start_data_ingestion_job method. boto3 documentation

# start_data_ingestion_job method definition

def start_data_ingestion_job(
    self,
    *,
    DatasetName: str,
    IngestionInputConfiguration: IngestionInputConfigurationTypeDef,  # (1)
    RoleArn: str,
    ClientToken: str,
) -> StartDataIngestionJobResponseTypeDef:  # (2)
    ...
  1. See IngestionInputConfigurationTypeDef
  2. See StartDataIngestionJobResponseTypeDef 
# start_data_ingestion_job method usage example with argument unpacking

kwargs: StartDataIngestionJobRequestRequestTypeDef = {  # (1)
    "DatasetName": ...,
    "IngestionInputConfiguration": ...,
    "RoleArn": ...,
    "ClientToken": ...,
}

parent.start_data_ingestion_job(**kwargs)
  1. See StartDataIngestionJobRequestRequestTypeDef

start_inference_scheduler#

Starts an inference scheduler.

Type annotations and code completion for boto3.client("lookoutequipment").start_inference_scheduler method. boto3 documentation

# start_inference_scheduler method definition

def start_inference_scheduler(
    self,
    *,
    InferenceSchedulerName: str,
) -> StartInferenceSchedulerResponseTypeDef:  # (1)
    ...
  1. See StartInferenceSchedulerResponseTypeDef 
# start_inference_scheduler method usage example with argument unpacking

kwargs: StartInferenceSchedulerRequestRequestTypeDef = {  # (1)
    "InferenceSchedulerName": ...,
}

parent.start_inference_scheduler(**kwargs)
  1. See StartInferenceSchedulerRequestRequestTypeDef

start_retraining_scheduler#

Starts a retraining scheduler.

Type annotations and code completion for boto3.client("lookoutequipment").start_retraining_scheduler method. boto3 documentation

# start_retraining_scheduler method definition

def start_retraining_scheduler(
    self,
    *,
    ModelName: str,
) -> StartRetrainingSchedulerResponseTypeDef:  # (1)
    ...
  1. See StartRetrainingSchedulerResponseTypeDef 
# start_retraining_scheduler method usage example with argument unpacking

kwargs: StartRetrainingSchedulerRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
}

parent.start_retraining_scheduler(**kwargs)
  1. See StartRetrainingSchedulerRequestRequestTypeDef

stop_inference_scheduler#

Stops an inference scheduler.

Type annotations and code completion for boto3.client("lookoutequipment").stop_inference_scheduler method. boto3 documentation

# stop_inference_scheduler method definition

def stop_inference_scheduler(
    self,
    *,
    InferenceSchedulerName: str,
) -> StopInferenceSchedulerResponseTypeDef:  # (1)
    ...
  1. See StopInferenceSchedulerResponseTypeDef 
# stop_inference_scheduler method usage example with argument unpacking

kwargs: StopInferenceSchedulerRequestRequestTypeDef = {  # (1)
    "InferenceSchedulerName": ...,
}

parent.stop_inference_scheduler(**kwargs)
  1. See StopInferenceSchedulerRequestRequestTypeDef

stop_retraining_scheduler#

Stops a retraining scheduler.

Type annotations and code completion for boto3.client("lookoutequipment").stop_retraining_scheduler method. boto3 documentation

# stop_retraining_scheduler method definition

def stop_retraining_scheduler(
    self,
    *,
    ModelName: str,
) -> StopRetrainingSchedulerResponseTypeDef:  # (1)
    ...
  1. See StopRetrainingSchedulerResponseTypeDef 
# stop_retraining_scheduler method usage example with argument unpacking

kwargs: StopRetrainingSchedulerRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
}

parent.stop_retraining_scheduler(**kwargs)
  1. See StopRetrainingSchedulerRequestRequestTypeDef

tag_resource#

Associates a given tag to a resource in your account.

Type annotations and code completion for boto3.client("lookoutequipment").tag_resource method. boto3 documentation

# tag_resource method definition

def tag_resource(
    self,
    *,
    ResourceArn: str,
    Tags: Sequence[TagTypeDef],  # (1)
) -> Dict[str, Any]:
    ...
  1. See TagTypeDef 
# tag_resource method usage example with argument unpacking

kwargs: TagResourceRequestRequestTypeDef = {  # (1)
    "ResourceArn": ...,
    "Tags": ...,
}

parent.tag_resource(**kwargs)
  1. See TagResourceRequestRequestTypeDef

untag_resource#

Removes a specific tag from a given resource.

Type annotations and code completion for boto3.client("lookoutequipment").untag_resource method. boto3 documentation

# untag_resource method definition

def untag_resource(
    self,
    *,
    ResourceArn: str,
    TagKeys: Sequence[str],
) -> Dict[str, Any]:
    ...
# untag_resource method usage example with argument unpacking

kwargs: UntagResourceRequestRequestTypeDef = {  # (1)
    "ResourceArn": ...,
    "TagKeys": ...,
}

parent.untag_resource(**kwargs)
  1. See UntagResourceRequestRequestTypeDef

update_active_model_version#

Sets the active model version for a given machine learning model.

Type annotations and code completion for boto3.client("lookoutequipment").update_active_model_version method. boto3 documentation

# update_active_model_version method definition

def update_active_model_version(
    self,
    *,
    ModelName: str,
    ModelVersion: int,
) -> UpdateActiveModelVersionResponseTypeDef:  # (1)
    ...
  1. See UpdateActiveModelVersionResponseTypeDef 
# update_active_model_version method usage example with argument unpacking

kwargs: UpdateActiveModelVersionRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
    "ModelVersion": ...,
}

parent.update_active_model_version(**kwargs)
  1. See UpdateActiveModelVersionRequestRequestTypeDef

update_inference_scheduler#

Updates an inference scheduler.

Type annotations and code completion for boto3.client("lookoutequipment").update_inference_scheduler method. boto3 documentation

# update_inference_scheduler method definition

def update_inference_scheduler(
    self,
    *,
    InferenceSchedulerName: str,
    DataDelayOffsetInMinutes: int = ...,
    DataUploadFrequency: DataUploadFrequencyType = ...,  # (1)
    DataInputConfiguration: InferenceInputConfigurationTypeDef = ...,  # (2)
    DataOutputConfiguration: InferenceOutputConfigurationTypeDef = ...,  # (3)
    RoleArn: str = ...,
) -> EmptyResponseMetadataTypeDef:  # (4)
    ...
  1. See DataUploadFrequencyType
  2. See InferenceInputConfigurationTypeDef
  3. See InferenceOutputConfigurationTypeDef
  4. See EmptyResponseMetadataTypeDef 
# update_inference_scheduler method usage example with argument unpacking

kwargs: UpdateInferenceSchedulerRequestRequestTypeDef = {  # (1)
    "InferenceSchedulerName": ...,
}

parent.update_inference_scheduler(**kwargs)
  1. See UpdateInferenceSchedulerRequestRequestTypeDef

update_label_group#

Updates the label group.

Type annotations and code completion for boto3.client("lookoutequipment").update_label_group method. boto3 documentation

# update_label_group method definition

def update_label_group(
    self,
    *,
    LabelGroupName: str,
    FaultCodes: Sequence[str] = ...,
) -> EmptyResponseMetadataTypeDef:  # (1)
    ...
  1. See EmptyResponseMetadataTypeDef 
# update_label_group method usage example with argument unpacking

kwargs: UpdateLabelGroupRequestRequestTypeDef = {  # (1)
    "LabelGroupName": ...,
}

parent.update_label_group(**kwargs)
  1. See UpdateLabelGroupRequestRequestTypeDef

update_model#

Updates a model in the account.

Type annotations and code completion for boto3.client("lookoutequipment").update_model method. boto3 documentation

# update_model method definition

def update_model(
    self,
    *,
    ModelName: str,
    LabelsInputConfiguration: LabelsInputConfigurationTypeDef = ...,  # (1)
    RoleArn: str = ...,
    ModelDiagnosticsOutputConfiguration: ModelDiagnosticsOutputConfigurationTypeDef = ...,  # (2)
) -> EmptyResponseMetadataTypeDef:  # (3)
    ...
  1. See LabelsInputConfigurationTypeDef
  2. See ModelDiagnosticsOutputConfigurationTypeDef
  3. See EmptyResponseMetadataTypeDef 
# update_model method usage example with argument unpacking

kwargs: UpdateModelRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
}

parent.update_model(**kwargs)
  1. See UpdateModelRequestRequestTypeDef

update_retraining_scheduler#

Updates a retraining scheduler.

Type annotations and code completion for boto3.client("lookoutequipment").update_retraining_scheduler method. boto3 documentation

# update_retraining_scheduler method definition

def update_retraining_scheduler(
    self,
    *,
    ModelName: str,
    RetrainingStartDate: TimestampTypeDef = ...,
    RetrainingFrequency: str = ...,
    LookbackWindow: str = ...,
    PromoteMode: ModelPromoteModeType = ...,  # (1)
) -> EmptyResponseMetadataTypeDef:  # (2)
    ...
  1. See ModelPromoteModeType
  2. See EmptyResponseMetadataTypeDef 
# update_retraining_scheduler method usage example with argument unpacking

kwargs: UpdateRetrainingSchedulerRequestRequestTypeDef = {  # (1)
    "ModelName": ...,
}

parent.update_retraining_scheduler(**kwargs)
  1. See UpdateRetrainingSchedulerRequestRequestTypeDef