types-aiobotocore-machinelearning 2.1.0.post1

Type annotations for aiobotocore.MachineLearning 2.1.0 service generated by mypy-boto3-builder 6.4.2

mypy-boto3-machinelearning

Type annotations for boto3.MachineLearning 1.20.47 service compatible with VSCode, PyCharm, Emacs, Sublime Text, mypy, pyright and other tools.

Generated by mypy-boto3-builder 6.4.2.

More information can be found on boto3-stubs page and in types-aiobotocore-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
    • 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 types-aiobotocore for MachineLearning service.

# install with aiobotocore type annotations
python -m pip install 'types-aiobotocore[machinelearning]'

# Lite version does not provide session.create_client overloads
# it is more RAM-friendly, but requires explicit type annotations
python -m pip install 'types-aiobotocore-lite[machinelearning]'

# standalone installation
python -m pip install types-aiobotocore-machinelearning

Usage

VSCode

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

Both type checking and auto-complete should work for MachineLearning service. No explicit type annotations required, write your aiobotocore code as usual. Auto-complete can be slow on big projects or if you have a lot of installed types-aiobotocore 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 types-aiobotocore[machinelearning] in your environment: python -m pip install 'types-aiobotocore[machinelearning]'
• Run mypy as usual

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

pyright

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

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

Explicit type annotations

Client annotations

MachineLearningClient provides annotations for session.create_client("machinelearning").

from aiobotocore.session import get_session

from types_aiobotocore_machinelearning import MachineLearningClient

session = get_session()
async with session.create_client("machinelearning") as client:
    client: MachineLearningClient
    # now client usage is checked by mypy and IDE should provide code auto-complete

Paginators annotations

types_aiobotocore_machinelearning.paginator module contains type annotations for all paginators.

from aiobotocore.session import get_session

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

session = get_session()
async with session.create_client("machinelearning") as client:
    client: MachineLearningClient

    # 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

`types_aiobotocore_machinelearning.waiter` module contains type annotations for all waiters.

```python
from aiobotocore.session import get_session

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

session = get_session()
async with session.create_client("machinelearning") as client:
    client: MachineLearningClient

    # 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")
    ```





<a id="literals"></a>

### Literals

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

```python
from types_aiobotocore_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

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

from types_aiobotocore_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

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

Documentation

All type annotations can be found in types-aiobotocore-machinelearning docs

Support and contributing

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