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Waiters#

Index > MachineLearning > Waiters

Auto-generated documentation for MachineLearning type annotations stubs module mypy-boto3-machinelearning.

BatchPredictionAvailableWaiter#

Type annotations and code completion for boto3.client("machinelearning").get_waiter("batch_prediction_available"). boto3 documentation

# BatchPredictionAvailableWaiter usage example

from boto3.session import Session

from mypy_boto3_machinelearning.waiter import BatchPredictionAvailableWaiter


session = Session()

client = session.client("machinelearning")  # (1)
waiter: BatchPredictionAvailableWaiter = client.get_waiter("batch_prediction_available")  # (2)
await waiter.wait()
  1. client: MachineLearningClient
  2. waiter: BatchPredictionAvailableWaiter

wait#

Type annotations and code completion for BatchPredictionAvailableWaiter.wait method.

# wait method definition

def wait(
    self,
    *,
    FilterVariable: BatchPredictionFilterVariableType = ...,  # (1)
    EQ: str = ...,
    GT: str = ...,
    LT: str = ...,
    GE: str = ...,
    LE: str = ...,
    NE: str = ...,
    Prefix: str = ...,
    SortOrder: SortOrderType = ...,  # (2)
    NextToken: str = ...,
    Limit: int = ...,
    WaiterConfig: WaiterConfigTypeDef = ...,  # (3)
) -> None:
    ...
  1. See BatchPredictionFilterVariableType
  2. See SortOrderType
  3. See WaiterConfigTypeDef
# wait method usage example with argument unpacking

kwargs: DescribeBatchPredictionsInputBatchPredictionAvailableWaitTypeDef = {  # (1)
    "FilterVariable": ...,
}

parent.wait(**kwargs)
  1. See DescribeBatchPredictionsInputBatchPredictionAvailableWaitTypeDef

DataSourceAvailableWaiter#

Type annotations and code completion for boto3.client("machinelearning").get_waiter("data_source_available"). boto3 documentation

# DataSourceAvailableWaiter usage example

from boto3.session import Session

from mypy_boto3_machinelearning.waiter import DataSourceAvailableWaiter


session = Session()

client = session.client("machinelearning")  # (1)
waiter: DataSourceAvailableWaiter = client.get_waiter("data_source_available")  # (2)
await waiter.wait()
  1. client: MachineLearningClient
  2. waiter: DataSourceAvailableWaiter

wait#

Type annotations and code completion for DataSourceAvailableWaiter.wait method.

# wait method definition

def wait(
    self,
    *,
    FilterVariable: DataSourceFilterVariableType = ...,  # (1)
    EQ: str = ...,
    GT: str = ...,
    LT: str = ...,
    GE: str = ...,
    LE: str = ...,
    NE: str = ...,
    Prefix: str = ...,
    SortOrder: SortOrderType = ...,  # (2)
    NextToken: str = ...,
    Limit: int = ...,
    WaiterConfig: WaiterConfigTypeDef = ...,  # (3)
) -> None:
    ...
  1. See DataSourceFilterVariableType
  2. See SortOrderType
  3. See WaiterConfigTypeDef
# wait method usage example with argument unpacking

kwargs: DescribeDataSourcesInputDataSourceAvailableWaitTypeDef = {  # (1)
    "FilterVariable": ...,
}

parent.wait(**kwargs)
  1. See DescribeDataSourcesInputDataSourceAvailableWaitTypeDef

EvaluationAvailableWaiter#

Type annotations and code completion for boto3.client("machinelearning").get_waiter("evaluation_available"). boto3 documentation

# EvaluationAvailableWaiter usage example

from boto3.session import Session

from mypy_boto3_machinelearning.waiter import EvaluationAvailableWaiter


session = Session()

client = session.client("machinelearning")  # (1)
waiter: EvaluationAvailableWaiter = client.get_waiter("evaluation_available")  # (2)
await waiter.wait()
  1. client: MachineLearningClient
  2. waiter: EvaluationAvailableWaiter

wait#

Type annotations and code completion for EvaluationAvailableWaiter.wait method.

# wait method definition

def wait(
    self,
    *,
    FilterVariable: EvaluationFilterVariableType = ...,  # (1)
    EQ: str = ...,
    GT: str = ...,
    LT: str = ...,
    GE: str = ...,
    LE: str = ...,
    NE: str = ...,
    Prefix: str = ...,
    SortOrder: SortOrderType = ...,  # (2)
    NextToken: str = ...,
    Limit: int = ...,
    WaiterConfig: WaiterConfigTypeDef = ...,  # (3)
) -> None:
    ...
  1. See EvaluationFilterVariableType
  2. See SortOrderType
  3. See WaiterConfigTypeDef
# wait method usage example with argument unpacking

kwargs: DescribeEvaluationsInputEvaluationAvailableWaitTypeDef = {  # (1)
    "FilterVariable": ...,
}

parent.wait(**kwargs)
  1. See DescribeEvaluationsInputEvaluationAvailableWaitTypeDef

MLModelAvailableWaiter#

Type annotations and code completion for boto3.client("machinelearning").get_waiter("ml_model_available"). boto3 documentation

# MLModelAvailableWaiter usage example

from boto3.session import Session

from mypy_boto3_machinelearning.waiter import MLModelAvailableWaiter


session = Session()

client = session.client("machinelearning")  # (1)
waiter: MLModelAvailableWaiter = client.get_waiter("ml_model_available")  # (2)
await waiter.wait()
  1. client: MachineLearningClient
  2. waiter: MLModelAvailableWaiter

wait#

Type annotations and code completion for MLModelAvailableWaiter.wait method.

# wait method definition

def wait(
    self,
    *,
    FilterVariable: MLModelFilterVariableType = ...,  # (1)
    EQ: str = ...,
    GT: str = ...,
    LT: str = ...,
    GE: str = ...,
    LE: str = ...,
    NE: str = ...,
    Prefix: str = ...,
    SortOrder: SortOrderType = ...,  # (2)
    NextToken: str = ...,
    Limit: int = ...,
    WaiterConfig: WaiterConfigTypeDef = ...,  # (3)
) -> None:
    ...
  1. See MLModelFilterVariableType
  2. See SortOrderType
  3. See WaiterConfigTypeDef
# wait method usage example with argument unpacking

kwargs: DescribeMLModelsInputMLModelAvailableWaitTypeDef = {  # (1)
    "FilterVariable": ...,
}

parent.wait(**kwargs)
  1. See DescribeMLModelsInputMLModelAvailableWaitTypeDef