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ForecastServiceClient#

Index > ForecastService > ForecastServiceClient

Auto-generated documentation for ForecastService type annotations stubs module mypy-boto3-forecast.

ForecastServiceClient#

Type annotations and code completion for boto3.client("forecast"). boto3 documentation

# ForecastServiceClient usage example

from boto3.session import Session
from mypy_boto3_forecast.client import ForecastServiceClient

def get_forecast_client() -> ForecastServiceClient:
    return Session().client("forecast")

Exceptions#

boto3 client exceptions are generated in runtime. This class provides code completion for boto3.client("forecast").exceptions structure.

# Exceptions.exceptions usage example

client = boto3.client("forecast")

try:
    do_something(client)
except (
    client.exceptions.ClientError,
    client.exceptions.InvalidInputException,
    client.exceptions.InvalidNextTokenException,
    client.exceptions.LimitExceededException,
    client.exceptions.ResourceAlreadyExistsException,
    client.exceptions.ResourceInUseException,
    client.exceptions.ResourceNotFoundException,
) as e:
    print(e)
# Exceptions.exceptions type checking example

from mypy_boto3_forecast.client import Exceptions

def handle_error(exc: Exceptions.ClientError) -> None:
    ...

Methods#

can_paginate#

Check if an operation can be paginated.

Type annotations and code completion for boto3.client("forecast").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("forecast").close method. boto3 documentation

# close method definition

def close(
    self,
) -> None:
    ...

create_auto_predictor#

Creates an Amazon Forecast predictor.

Type annotations and code completion for boto3.client("forecast").create_auto_predictor method. boto3 documentation

# create_auto_predictor method definition

def create_auto_predictor(
    self,
    *,
    PredictorName: str,
    ForecastHorizon: int = ...,
    ForecastTypes: Sequence[str] = ...,
    ForecastDimensions: Sequence[str] = ...,
    ForecastFrequency: str = ...,
    DataConfig: DataConfigTypeDef = ...,  # (1)
    EncryptionConfig: EncryptionConfigTypeDef = ...,  # (2)
    ReferencePredictorArn: str = ...,
    OptimizationMetric: OptimizationMetricType = ...,  # (3)
    ExplainPredictor: bool = ...,
    Tags: Sequence[TagTypeDef] = ...,  # (4)
    MonitorConfig: MonitorConfigTypeDef = ...,  # (5)
    TimeAlignmentBoundary: TimeAlignmentBoundaryTypeDef = ...,  # (6)
) -> CreateAutoPredictorResponseTypeDef:  # (7)
    ...
  1. See DataConfigTypeDef
  2. See EncryptionConfigTypeDef
  3. See OptimizationMetricType
  4. See TagTypeDef
  5. See MonitorConfigTypeDef
  6. See TimeAlignmentBoundaryTypeDef
  7. See CreateAutoPredictorResponseTypeDef 
# create_auto_predictor method usage example with argument unpacking

kwargs: CreateAutoPredictorRequestRequestTypeDef = {  # (1)
    "PredictorName": ...,
}

parent.create_auto_predictor(**kwargs)
  1. See CreateAutoPredictorRequestRequestTypeDef

create_dataset#

Creates an Amazon Forecast dataset.

Type annotations and code completion for boto3.client("forecast").create_dataset method. boto3 documentation

# create_dataset method definition

def create_dataset(
    self,
    *,
    DatasetName: str,
    Domain: DomainType,  # (1)
    DatasetType: DatasetTypeType,  # (2)
    Schema: SchemaTypeDef,  # (3)
    DataFrequency: str = ...,
    EncryptionConfig: EncryptionConfigTypeDef = ...,  # (4)
    Tags: Sequence[TagTypeDef] = ...,  # (5)
) -> CreateDatasetResponseTypeDef:  # (6)
    ...
  1. See DomainType
  2. See DatasetTypeType
  3. See SchemaTypeDef
  4. See EncryptionConfigTypeDef
  5. See TagTypeDef
  6. See CreateDatasetResponseTypeDef 
# create_dataset method usage example with argument unpacking

kwargs: CreateDatasetRequestRequestTypeDef = {  # (1)
    "DatasetName": ...,
    "Domain": ...,
    "DatasetType": ...,
    "Schema": ...,
}

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

create_dataset_group#

Creates a dataset group, which holds a collection of related datasets.

Type annotations and code completion for boto3.client("forecast").create_dataset_group method. boto3 documentation

# create_dataset_group method definition

def create_dataset_group(
    self,
    *,
    DatasetGroupName: str,
    Domain: DomainType,  # (1)
    DatasetArns: Sequence[str] = ...,
    Tags: Sequence[TagTypeDef] = ...,  # (2)
) -> CreateDatasetGroupResponseTypeDef:  # (3)
    ...
  1. See DomainType
  2. See TagTypeDef
  3. See CreateDatasetGroupResponseTypeDef 
# create_dataset_group method usage example with argument unpacking

kwargs: CreateDatasetGroupRequestRequestTypeDef = {  # (1)
    "DatasetGroupName": ...,
    "Domain": ...,
}

parent.create_dataset_group(**kwargs)
  1. See CreateDatasetGroupRequestRequestTypeDef

create_dataset_import_job#

Imports your training data to an Amazon Forecast dataset.

Type annotations and code completion for boto3.client("forecast").create_dataset_import_job method. boto3 documentation

# create_dataset_import_job method definition

def create_dataset_import_job(
    self,
    *,
    DatasetImportJobName: str,
    DatasetArn: str,
    DataSource: DataSourceTypeDef,  # (1)
    TimestampFormat: str = ...,
    TimeZone: str = ...,
    UseGeolocationForTimeZone: bool = ...,
    GeolocationFormat: str = ...,
    Tags: Sequence[TagTypeDef] = ...,  # (2)
    Format: str = ...,
    ImportMode: ImportModeType = ...,  # (3)
) -> CreateDatasetImportJobResponseTypeDef:  # (4)
    ...
  1. See DataSourceTypeDef
  2. See TagTypeDef
  3. See ImportModeType
  4. See CreateDatasetImportJobResponseTypeDef 
# create_dataset_import_job method usage example with argument unpacking

kwargs: CreateDatasetImportJobRequestRequestTypeDef = {  # (1)
    "DatasetImportJobName": ...,
    "DatasetArn": ...,
    "DataSource": ...,
}

parent.create_dataset_import_job(**kwargs)
  1. See CreateDatasetImportJobRequestRequestTypeDef

create_explainability#

.

Type annotations and code completion for boto3.client("forecast").create_explainability method. boto3 documentation

# create_explainability method definition

def create_explainability(
    self,
    *,
    ExplainabilityName: str,
    ResourceArn: str,
    ExplainabilityConfig: ExplainabilityConfigTypeDef,  # (1)
    DataSource: DataSourceTypeDef = ...,  # (2)
    Schema: SchemaTypeDef = ...,  # (3)
    EnableVisualization: bool = ...,
    StartDateTime: str = ...,
    EndDateTime: str = ...,
    Tags: Sequence[TagTypeDef] = ...,  # (4)
) -> CreateExplainabilityResponseTypeDef:  # (5)
    ...
  1. See ExplainabilityConfigTypeDef
  2. See DataSourceTypeDef
  3. See SchemaTypeDef
  4. See TagTypeDef
  5. See CreateExplainabilityResponseTypeDef 
# create_explainability method usage example with argument unpacking

kwargs: CreateExplainabilityRequestRequestTypeDef = {  # (1)
    "ExplainabilityName": ...,
    "ResourceArn": ...,
    "ExplainabilityConfig": ...,
}

parent.create_explainability(**kwargs)
  1. See CreateExplainabilityRequestRequestTypeDef

create_explainability_export#

Exports an Explainability resource created by the CreateExplainability operation.

Type annotations and code completion for boto3.client("forecast").create_explainability_export method. boto3 documentation

# create_explainability_export method definition

def create_explainability_export(
    self,
    *,
    ExplainabilityExportName: str,
    ExplainabilityArn: str,
    Destination: DataDestinationTypeDef,  # (1)
    Tags: Sequence[TagTypeDef] = ...,  # (2)
    Format: str = ...,
) -> CreateExplainabilityExportResponseTypeDef:  # (3)
    ...
  1. See DataDestinationTypeDef
  2. See TagTypeDef
  3. See CreateExplainabilityExportResponseTypeDef 
# create_explainability_export method usage example with argument unpacking

kwargs: CreateExplainabilityExportRequestRequestTypeDef = {  # (1)
    "ExplainabilityExportName": ...,
    "ExplainabilityArn": ...,
    "Destination": ...,
}

parent.create_explainability_export(**kwargs)
  1. See CreateExplainabilityExportRequestRequestTypeDef

create_forecast#

Creates a forecast for each item in the TARGET_TIME_SERIES dataset that was used to train the predictor.

Type annotations and code completion for boto3.client("forecast").create_forecast method. boto3 documentation

# create_forecast method definition

def create_forecast(
    self,
    *,
    ForecastName: str,
    PredictorArn: str,
    ForecastTypes: Sequence[str] = ...,
    Tags: Sequence[TagTypeDef] = ...,  # (1)
    TimeSeriesSelector: TimeSeriesSelectorTypeDef = ...,  # (2)
) -> CreateForecastResponseTypeDef:  # (3)
    ...
  1. See TagTypeDef
  2. See TimeSeriesSelectorTypeDef
  3. See CreateForecastResponseTypeDef 
# create_forecast method usage example with argument unpacking

kwargs: CreateForecastRequestRequestTypeDef = {  # (1)
    "ForecastName": ...,
    "PredictorArn": ...,
}

parent.create_forecast(**kwargs)
  1. See CreateForecastRequestRequestTypeDef

create_forecast_export_job#

Exports a forecast created by the CreateForecast operation to your Amazon Simple Storage Service (Amazon S3) bucket.

Type annotations and code completion for boto3.client("forecast").create_forecast_export_job method. boto3 documentation

# create_forecast_export_job method definition

def create_forecast_export_job(
    self,
    *,
    ForecastExportJobName: str,
    ForecastArn: str,
    Destination: DataDestinationTypeDef,  # (1)
    Tags: Sequence[TagTypeDef] = ...,  # (2)
    Format: str = ...,
) -> CreateForecastExportJobResponseTypeDef:  # (3)
    ...
  1. See DataDestinationTypeDef
  2. See TagTypeDef
  3. See CreateForecastExportJobResponseTypeDef 
# create_forecast_export_job method usage example with argument unpacking

kwargs: CreateForecastExportJobRequestRequestTypeDef = {  # (1)
    "ForecastExportJobName": ...,
    "ForecastArn": ...,
    "Destination": ...,
}

parent.create_forecast_export_job(**kwargs)
  1. See CreateForecastExportJobRequestRequestTypeDef

create_monitor#

Creates a predictor monitor resource for an existing auto predictor.

Type annotations and code completion for boto3.client("forecast").create_monitor method. boto3 documentation

# create_monitor method definition

def create_monitor(
    self,
    *,
    MonitorName: str,
    ResourceArn: str,
    Tags: Sequence[TagTypeDef] = ...,  # (1)
) -> CreateMonitorResponseTypeDef:  # (2)
    ...
  1. See TagTypeDef
  2. See CreateMonitorResponseTypeDef 
# create_monitor method usage example with argument unpacking

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

parent.create_monitor(**kwargs)
  1. See CreateMonitorRequestRequestTypeDef

create_predictor#

.

Type annotations and code completion for boto3.client("forecast").create_predictor method.