mypy-boto3-machinelearning 1.20.46.post1

Type annotations for boto3.MachineLearning 1.20.46 service generated by mypy-boto3-builder 6.4.1

mypy-boto3-machinelearning

Type annotations for boto3.MachineLearning 1.20.46 service compatible with VSCode, PyCharm, Emacs, Sublime Text, mypy, pyright and other tools.

Generated by mypy-boto3-builder 6.4.1.

More information can be found on boto3-stubs page and in mypy-boto3-machinelearning docs

See how it helps to find and fix potential bugs:

• mypy-boto3-machinelearning
  • How to install
    • VSCode extension
    • From PyPI with pip
  • Usage
    • VSCode
    • PyCharm
    • Other IDEs
    • mypy
    • pyright
  • Explicit type annotations
    • Client annotations
    • Paginators annotations
    • Waiters annotations
    • Literals
    • Typed dictionaries
  • Versioning
  • Documentation
  • Support and contributing

How to install

VSCode extension

Add AWS Boto3 extension to your VSCode and run AWS boto3: Quick Start command.

Click Modify and select boto3 common and MachineLearning.

From PyPI with pip

Install boto3-stubs for MachineLearning service.

python -m pip install boto3-stubs[machinelearning]

Usage

VSCode

• Install Python extension
• Install Pylance extension
• Set Pylance as your Python Language Server
• Install boto3-stubs[machinelearning] in your environment: python -m pip install 'boto3-stubs[machinelearning]'

Both type checking and auto-complete should work for MachineLearning service. No explicit type annotations required, write your boto3 code as usual.

PyCharm

• Install boto3-stubs[machinelearning] in your environment: python -m pip install 'boto3-stubs[machinelearning]'

Both type checking and auto-complete should work for MachineLearning service. No explicit type annotations required, write your boto3 code as usual. Auto-complete can be slow on big projects or if you have a lot of installed boto3-stubs submodules.

Other IDEs

Not tested, but as long as your IDE supports mypy or pyright, everything should work.

mypy

• Install mypy: python -m pip install mypy
• Install boto3-stubs[machinelearning] in your environment: python -m pip install 'boto3-stubs[machinelearning]'
• Run mypy as usual

Type checking should work for MachineLearning service. No explicit type annotations required, write your boto3 code as usual.

pyright

• Install pyright: yarn global add pyright
• Install boto3-stubs[machinelearning] in your environment: python -m pip install 'boto3-stubs[machinelearning]'
• Optionally, you can install boto3-stubs to typings folder.

Type checking should work for MachineLearning service. No explicit type annotations required, write your boto3 code as usual.

Explicit type annotations

Client annotations

MachineLearningClient provides annotations for boto3.client("machinelearning").

import boto3

from mypy_boto3_machinelearning import MachineLearningClient

client: MachineLearningClient = boto3.client("machinelearning")

# now client usage is checked by mypy and IDE should provide code auto-complete

# works for session as well
session = boto3.session.Session(region="us-west-1")
session_client: MachineLearningClient = session.client("machinelearning")

Paginators annotations

mypy_boto3_machinelearning.paginator module contains type annotations for all paginators.

from mypy_boto3_machinelearning import MachineLearningClient
from mypy_boto3_machinelearning.paginator import (
    DescribeBatchPredictionsPaginator,
    DescribeDataSourcesPaginator,
    DescribeEvaluationsPaginator,
    DescribeMLModelsPaginator,
)

client: MachineLearningClient = boto3.client("machinelearning")

# Explicit type annotations are optional here
# Type should be correctly discovered by mypy and IDEs
# VSCode requires explicit type annotations
describe_batch_predictions_paginator: DescribeBatchPredictionsPaginator = client.get_paginator("describe_batch_predictions")
describe_data_sources_paginator: DescribeDataSourcesPaginator = client.get_paginator("describe_data_sources")
describe_evaluations_paginator: DescribeEvaluationsPaginator = client.get_paginator("describe_evaluations")
describe_ml_models_paginator: DescribeMLModelsPaginator = client.get_paginator("describe_ml_models")

Waiters annotations

mypy_boto3_machinelearning.waiter module contains type annotations for all waiters.

from mypy_boto3_machinelearning import MachineLearningClient
from mypy_boto3_machinelearning.waiter import (
    BatchPredictionAvailableWaiter,
    DataSourceAvailableWaiter,
    EvaluationAvailableWaiter,
    MLModelAvailableWaiter,
)

client: MachineLearningClient = boto3.client("machinelearning")

# Explicit type annotations are optional here
# Type should be correctly discovered by mypy and IDEs
# VSCode requires explicit type annotations
batch_prediction_available_waiter: BatchPredictionAvailableWaiter = client.get_waiter("batch_prediction_available")
data_source_available_waiter: DataSourceAvailableWaiter = client.get_waiter("data_source_available")
evaluation_available_waiter: EvaluationAvailableWaiter = client.get_waiter("evaluation_available")
ml_model_available_waiter: MLModelAvailableWaiter = client.get_waiter("ml_model_available")

Literals

mypy_boto3_machinelearning.literals module contains literals extracted from shapes that can be used in user code for type checking.

from mypy_boto3_machinelearning.literals import (
    AlgorithmType,
    BatchPredictionAvailableWaiterName,
    BatchPredictionFilterVariableType,
    DataSourceAvailableWaiterName,
    DataSourceFilterVariableType,
    DescribeBatchPredictionsPaginatorName,
    DescribeDataSourcesPaginatorName,
    DescribeEvaluationsPaginatorName,
    DescribeMLModelsPaginatorName,
    DetailsAttributesType,
    EntityStatusType,
    EvaluationAvailableWaiterName,
    EvaluationFilterVariableType,
    MLModelAvailableWaiterName,
    MLModelFilterVariableType,
    MLModelTypeType,
    RealtimeEndpointStatusType,
    SortOrderType,
    TaggableResourceTypeType,
    ServiceName,
    PaginatorName,
    WaiterName,
)

def check_value(value: AlgorithmType) -> bool:
    ...

Typed dictionaries

mypy_boto3_machinelearning.type_defs module contains structures and shapes assembled to typed dictionaries for additional type checking.

from mypy_boto3_machinelearning.type_defs import (
    AddTagsInputRequestTypeDef,
    AddTagsOutputTypeDef,
    BatchPredictionTypeDef,
    CreateBatchPredictionInputRequestTypeDef,
    CreateBatchPredictionOutputTypeDef,
    CreateDataSourceFromRDSInputRequestTypeDef,
    CreateDataSourceFromRDSOutputTypeDef,
    CreateDataSourceFromRedshiftInputRequestTypeDef,
    CreateDataSourceFromRedshiftOutputTypeDef,
    CreateDataSourceFromS3InputRequestTypeDef,
    CreateDataSourceFromS3OutputTypeDef,
    CreateEvaluationInputRequestTypeDef,
    CreateEvaluationOutputTypeDef,
    CreateMLModelInputRequestTypeDef,
    CreateMLModelOutputTypeDef,
    CreateRealtimeEndpointInputRequestTypeDef,
    CreateRealtimeEndpointOutputTypeDef,
    DataSourceTypeDef,
    DeleteBatchPredictionInputRequestTypeDef,
    DeleteBatchPredictionOutputTypeDef,
    DeleteDataSourceInputRequestTypeDef,
    DeleteDataSourceOutputTypeDef,
    DeleteEvaluationInputRequestTypeDef,
    DeleteEvaluationOutputTypeDef,
    DeleteMLModelInputRequestTypeDef,
    DeleteMLModelOutputTypeDef,
    DeleteRealtimeEndpointInputRequestTypeDef,
    DeleteRealtimeEndpointOutputTypeDef,
    DeleteTagsInputRequestTypeDef,
    DeleteTagsOutputTypeDef,
    DescribeBatchPredictionsInputRequestTypeDef,
    DescribeBatchPredictionsOutputTypeDef,
    DescribeDataSourcesInputRequestTypeDef,
    DescribeDataSourcesOutputTypeDef,
    DescribeEvaluationsInputRequestTypeDef,
    DescribeEvaluationsOutputTypeDef,
    DescribeMLModelsInputRequestTypeDef,
    DescribeMLModelsOutputTypeDef,
    DescribeTagsInputRequestTypeDef,
    DescribeTagsOutputTypeDef,
    EvaluationTypeDef,
    GetBatchPredictionInputRequestTypeDef,
    GetBatchPredictionOutputTypeDef,
    GetDataSourceInputRequestTypeDef,
    GetDataSourceOutputTypeDef,
    GetEvaluationInputRequestTypeDef,
    GetEvaluationOutputTypeDef,
    GetMLModelInputRequestTypeDef,
    GetMLModelOutputTypeDef,
    MLModelTypeDef,
    PaginatorConfigTypeDef,
    PerformanceMetricsTypeDef,
    PredictInputRequestTypeDef,
    PredictOutputTypeDef,
    PredictionTypeDef,
    RDSDataSpecTypeDef,
    RDSDatabaseCredentialsTypeDef,
    RDSDatabaseTypeDef,
    RDSMetadataTypeDef,
    RealtimeEndpointInfoTypeDef,
    RedshiftDataSpecTypeDef,
    RedshiftDatabaseCredentialsTypeDef,
    RedshiftDatabaseTypeDef,
    RedshiftMetadataTypeDef,
    ResponseMetadataTypeDef,
    S3DataSpecTypeDef,
    TagTypeDef,
    UpdateBatchPredictionInputRequestTypeDef,
    UpdateBatchPredictionOutputTypeDef,
    UpdateDataSourceInputRequestTypeDef,
    UpdateDataSourceOutputTypeDef,
    UpdateEvaluationInputRequestTypeDef,
    UpdateEvaluationOutputTypeDef,
    UpdateMLModelInputRequestTypeDef,
    UpdateMLModelOutputTypeDef,
    WaiterConfigTypeDef,
)

def get_structure() -> AddTagsInputRequestTypeDef:
    return {
      ...
    }

Versioning

mypy-boto3-machinelearning version is the same as related boto3 version and follows PEP 440 format.

Documentation

All type annotations can be found in mypy-boto3-machinelearning docs

Support and contributing

This package is auto-generated. Please reports any bugs or request new features in mypy-boto3-builder repository.