%global _empty_manifest_terminate_build 0
Name:		python-mypy-boto3-machinelearning
Version:	1.26.0.post1
Release:	1
Summary:	Type annotations for boto3.MachineLearning 1.26.0 service generated with mypy-boto3-builder 7.11.10
License:	MIT License
URL:		https://github.com/youtype/mypy_boto3_builder
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/cc/76/4666229df73bf733f73c87f4d7f8819c70d026f77bc6f5550855e64a4495/mypy-boto3-machinelearning-1.26.0.post1.tar.gz
BuildArch:	noarch

Requires:	python3-typing-extensions

%description
<a id="mypy-boto3-machinelearning"></a>

# mypy-boto3-machinelearning

[![PyPI - mypy-boto3-machinelearning](https://img.shields.io/pypi/v/mypy-boto3-machinelearning.svg?color=blue)](https://pypi.org/project/mypy-boto3-machinelearning)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mypy-boto3-machinelearning.svg?color=blue)](https://pypi.org/project/mypy-boto3-machinelearning)
[![Docs](https://img.shields.io/readthedocs/mypy-boto3-builder.svg?color=blue)](https://mypy-boto3-builder.readthedocs.io/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/mypy-boto3-machinelearning?color=blue)](https://pypistats.org/packages/mypy-boto3-machinelearning)

![boto3.typed](https://github.com/youtype/mypy_boto3_builder/raw/main/logo.png)

Type annotations for
[boto3.MachineLearning 1.26.0](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/machinelearning.html#MachineLearning)
service compatible with [VSCode](https://code.visualstudio.com/),
[PyCharm](https://www.jetbrains.com/pycharm/),
[Emacs](https://www.gnu.org/software/emacs/),
[Sublime Text](https://www.sublimetext.com/),
[mypy](https://github.com/python/mypy),
[pyright](https://github.com/microsoft/pyright) and other tools.

Generated by
[mypy-boto3-builder 7.11.10](https://github.com/youtype/mypy_boto3_builder).

More information can be found on
[boto3-stubs](https://pypi.org/project/boto3-stubs/) page and in
[mypy-boto3-machinelearning docs](https://youtype.github.io/boto3_stubs_docs/mypy_boto3_machinelearning/).

See how it helps to find and fix potential bugs:

![boto3-stubs demo](https://github.com/youtype/mypy_boto3_builder/raw/main/demo.gif)

- [mypy-boto3-machinelearning](#mypy-boto3-machinelearning)
  - [How to install](#how-to-install)
    - [VSCode extension](#vscode-extension)
    - [From PyPI with pip](#from-pypi-with-pip)
  - [How to uninstall](#how-to-uninstall)
  - [Usage](#usage)
    - [VSCode](#vscode)
    - [PyCharm](#pycharm)
    - [Emacs](#emacs)
    - [Sublime Text](#sublime-text)
    - [Other IDEs](#other-ides)
    - [mypy](#mypy)
    - [pyright](#pyright)
  - [Explicit type annotations](#explicit-type-annotations)
    - [Client annotations](#client-annotations)
    - [Paginators annotations](#paginators-annotations)
    - [Waiters annotations](#waiters-annotations)
    - [Literals](#literals)
    - [Typed dictionaries](#typed-dictionaries)
  - [How it works](#how-it-works)
  - [What's new](#what's-new)
    - [Implemented features](#implemented-features)
    - [Latest changes](#latest-changes)
  - [Versioning](#versioning)
  - [Thank you](#thank-you)
  - [Documentation](#documentation)
  - [Support and contributing](#support-and-contributing)

<a id="how-to-install"></a>

## How to install

<a id="vscode-extension"></a>

### VSCode extension

Add
[AWS Boto3](https://marketplace.visualstudio.com/items?itemName=Boto3typed.boto3-ide)
extension to your VSCode and run `AWS boto3: Quick Start` command.

Click `Modify` and select `boto3 common` and `MachineLearning`.

<a id="from-pypi-with-pip"></a>

### From PyPI with pip

Install `boto3-stubs` for `MachineLearning` service.

```bash
# install with boto3 type annotations
python -m pip install 'boto3-stubs[machinelearning]'


# Lite version does not provide session.client/resource overloads
# it is more RAM-friendly, but requires explicit type annotations
python -m pip install 'boto3-stubs-lite[machinelearning]'


# standalone installation
python -m pip install mypy-boto3-machinelearning
```

<a id="how-to-uninstall"></a>

## How to uninstall

```bash
python -m pip uninstall -y mypy-boto3-machinelearning
```

<a id="usage"></a>

## Usage

<a id="vscode"></a>

### VSCode

- Install
  [Python extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python)
- Install
  [Pylance extension](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance)
- Set `Pylance` as your Python Language Server
- Install `boto3-stubs[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

Both type checking and code completion should now work. No explicit type
annotations required, write your `boto3` code as usual.

<a id="pycharm"></a>

### PyCharm

Install `boto3-stubs-lite[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs-lite[machinelearning]'`
```

Both type checking and code completion should now work. Explicit type
annotations **are required**.

Use `boto3-stubs` package instead for implicit type discovery.

<a id="emacs"></a>

### Emacs

- Install `boto3-stubs` with services you use in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

- Install [use-package](https://github.com/jwiegley/use-package),
  [lsp](https://github.com/emacs-lsp/lsp-mode/),
  [company](https://github.com/company-mode/company-mode) and
  [flycheck](https://github.com/flycheck/flycheck) packages
- Install [lsp-pyright](https://github.com/emacs-lsp/lsp-pyright) package

```elisp
(use-package lsp-pyright
  :ensure t
  :hook (python-mode . (lambda ()
                          (require 'lsp-pyright)
                          (lsp)))  ; or lsp-deferred
  :init (when (executable-find "python3")
          (setq lsp-pyright-python-executable-cmd "python3"))
  )
```

- Make sure emacs uses the environment where you have installed `boto3-stubs`

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="sublime-text"></a>

### Sublime Text

- Install `boto3-stubs[machinelearning]` with services you use in your
  environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

- Install [LSP-pyright](https://github.com/sublimelsp/LSP-pyright) package

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="other-ides"></a>

### Other IDEs

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

<a id="mypy"></a>

### mypy

- Install `mypy`: `python -m pip install mypy`
- Install `boto3-stubs[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'`
```

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="pyright"></a>

### pyright

- Install `pyright`: `npm i -g pyright`
- Install `boto3-stubs[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

Optionally, you can install `boto3-stubs` to `typings` folder.

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="explicit-type-annotations"></a>

## Explicit type annotations

<a id="client-annotations"></a>

### Client annotations

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

```python
from boto3.session import Session

from mypy_boto3_machinelearning import MachineLearningClient

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

# now client usage is checked by mypy and IDE should provide code completion
```

<a id="paginators-annotations"></a>

### Paginators annotations

`mypy_boto3_machinelearning.paginator` module contains type annotations for all
paginators.

```python
from boto3.session import Session

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

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

# Explicit type annotations are optional here
# Types should be correctly discovered by mypy and IDEs
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")
```

<a id="waiters-annotations"></a>

### Waiters annotations

`mypy_boto3_machinelearning.waiter` module contains type annotations for all
waiters.

```python
from boto3.session import Session

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

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

# Explicit type annotations are optional here
# Types should be correctly discovered by mypy and IDEs
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

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

```python
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,
    MachineLearningServiceName,
    ServiceName,
    ResourceServiceName,
    PaginatorName,
    WaiterName,
    RegionName,
)


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

<a id="typed-dictionaries"></a>

### Typed dictionaries

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

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


def get_structure() -> TagTypeDef:
    return {...}
```

<a id="how-it-works"></a>

## How it works

Fully automated
[mypy-boto3-builder](https://github.com/youtype/mypy_boto3_builder) carefully
generates type annotations for each service, patiently waiting for `boto3`
updates. It delivers a drop-in type annotations for you and makes sure that:

- All available `boto3` services are covered.
- Each public class and method of every `boto3` service gets valid type
  annotations extracted from the documentation (blame `botocore` docs if types
  are incorrect).
- Type annotations include up-to-date documentation.
- Link to documentation is provided for every method.
- Code is processed by [black](https://github.com/psf/black) and
  [isort](https://github.com/PyCQA/isort) for readability.

<a id="what's-new"></a>

## What's new

<a id="implemented-features"></a>

### Implemented features

- Fully type annotated `boto3`, `botocore` and `aiobotocore` libraries
- `mypy`, `pyright`, `VSCode`, `PyCharm`, `Sublime Text` and `Emacs`
  compatibility
- `Client`, `ServiceResource`, `Resource`, `Waiter` `Paginator` type
  annotations for each service
- Generated `TypeDefs` for each service
- Generated `Literals` for each service
- Auto discovery of types for `boto3.client` and `boto3.session` calls
- Auto discovery of types for `session.client` and `session.session` calls
- Auto discovery of types for `client.get_waiter` and `client.get_paginator`
  calls
- Auto discovery of types for `ServiceResource` and `Resource` collections
- Auto discovery of types for `aiobotocore.Session.create_client` calls

<a id="latest-changes"></a>

### Latest changes

Builder changelog can be found in
[Releases](https://github.com/youtype/mypy_boto3_builder/releases).

<a id="versioning"></a>

## Versioning

`mypy-boto3-machinelearning` version is the same as related `boto3` version and
follows [PEP 440](https://www.python.org/dev/peps/pep-0440/) format.

<a id="thank-you"></a>

## Thank you

- [Allie Fitter](https://github.com/alliefitter) for
  [boto3-type-annotations](https://pypi.org/project/boto3-type-annotations/),
  this package is based on top of his work
- [black](https://github.com/psf/black) developers for an awesome formatting
  tool
- [Timothy Edmund Crosley](https://github.com/timothycrosley) for
  [isort](https://github.com/PyCQA/isort) and how flexible it is
- [mypy](https://github.com/python/mypy) developers for doing all dirty work
  for us
- [pyright](https://github.com/microsoft/pyright) team for the new era of typed
  Python

<a id="documentation"></a>

## Documentation

All services type annotations can be found in
[boto3 docs](https://youtype.github.io/boto3_stubs_docs/mypy_boto3_machinelearning/)

<a id="support-and-contributing"></a>

## Support and contributing

This package is auto-generated. Please reports any bugs or request new features
in [mypy-boto3-builder](https://github.com/youtype/mypy_boto3_builder/issues/)
repository.


%package -n python3-mypy-boto3-machinelearning
Summary:	Type annotations for boto3.MachineLearning 1.26.0 service generated with mypy-boto3-builder 7.11.10
Provides:	python-mypy-boto3-machinelearning
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-mypy-boto3-machinelearning
<a id="mypy-boto3-machinelearning"></a>

# mypy-boto3-machinelearning

[![PyPI - mypy-boto3-machinelearning](https://img.shields.io/pypi/v/mypy-boto3-machinelearning.svg?color=blue)](https://pypi.org/project/mypy-boto3-machinelearning)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mypy-boto3-machinelearning.svg?color=blue)](https://pypi.org/project/mypy-boto3-machinelearning)
[![Docs](https://img.shields.io/readthedocs/mypy-boto3-builder.svg?color=blue)](https://mypy-boto3-builder.readthedocs.io/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/mypy-boto3-machinelearning?color=blue)](https://pypistats.org/packages/mypy-boto3-machinelearning)

![boto3.typed](https://github.com/youtype/mypy_boto3_builder/raw/main/logo.png)

Type annotations for
[boto3.MachineLearning 1.26.0](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/machinelearning.html#MachineLearning)
service compatible with [VSCode](https://code.visualstudio.com/),
[PyCharm](https://www.jetbrains.com/pycharm/),
[Emacs](https://www.gnu.org/software/emacs/),
[Sublime Text](https://www.sublimetext.com/),
[mypy](https://github.com/python/mypy),
[pyright](https://github.com/microsoft/pyright) and other tools.

Generated by
[mypy-boto3-builder 7.11.10](https://github.com/youtype/mypy_boto3_builder).

More information can be found on
[boto3-stubs](https://pypi.org/project/boto3-stubs/) page and in
[mypy-boto3-machinelearning docs](https://youtype.github.io/boto3_stubs_docs/mypy_boto3_machinelearning/).

See how it helps to find and fix potential bugs:

![boto3-stubs demo](https://github.com/youtype/mypy_boto3_builder/raw/main/demo.gif)

- [mypy-boto3-machinelearning](#mypy-boto3-machinelearning)
  - [How to install](#how-to-install)
    - [VSCode extension](#vscode-extension)
    - [From PyPI with pip](#from-pypi-with-pip)
  - [How to uninstall](#how-to-uninstall)
  - [Usage](#usage)
    - [VSCode](#vscode)
    - [PyCharm](#pycharm)
    - [Emacs](#emacs)
    - [Sublime Text](#sublime-text)
    - [Other IDEs](#other-ides)
    - [mypy](#mypy)
    - [pyright](#pyright)
  - [Explicit type annotations](#explicit-type-annotations)
    - [Client annotations](#client-annotations)
    - [Paginators annotations](#paginators-annotations)
    - [Waiters annotations](#waiters-annotations)
    - [Literals](#literals)
    - [Typed dictionaries](#typed-dictionaries)
  - [How it works](#how-it-works)
  - [What's new](#what's-new)
    - [Implemented features](#implemented-features)
    - [Latest changes](#latest-changes)
  - [Versioning](#versioning)
  - [Thank you](#thank-you)
  - [Documentation](#documentation)
  - [Support and contributing](#support-and-contributing)

<a id="how-to-install"></a>

## How to install

<a id="vscode-extension"></a>

### VSCode extension

Add
[AWS Boto3](https://marketplace.visualstudio.com/items?itemName=Boto3typed.boto3-ide)
extension to your VSCode and run `AWS boto3: Quick Start` command.

Click `Modify` and select `boto3 common` and `MachineLearning`.

<a id="from-pypi-with-pip"></a>

### From PyPI with pip

Install `boto3-stubs` for `MachineLearning` service.

```bash
# install with boto3 type annotations
python -m pip install 'boto3-stubs[machinelearning]'


# Lite version does not provide session.client/resource overloads
# it is more RAM-friendly, but requires explicit type annotations
python -m pip install 'boto3-stubs-lite[machinelearning]'


# standalone installation
python -m pip install mypy-boto3-machinelearning
```

<a id="how-to-uninstall"></a>

## How to uninstall

```bash
python -m pip uninstall -y mypy-boto3-machinelearning
```

<a id="usage"></a>

## Usage

<a id="vscode"></a>

### VSCode

- Install
  [Python extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python)
- Install
  [Pylance extension](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance)
- Set `Pylance` as your Python Language Server
- Install `boto3-stubs[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

Both type checking and code completion should now work. No explicit type
annotations required, write your `boto3` code as usual.

<a id="pycharm"></a>

### PyCharm

Install `boto3-stubs-lite[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs-lite[machinelearning]'`
```

Both type checking and code completion should now work. Explicit type
annotations **are required**.

Use `boto3-stubs` package instead for implicit type discovery.

<a id="emacs"></a>

### Emacs

- Install `boto3-stubs` with services you use in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

- Install [use-package](https://github.com/jwiegley/use-package),
  [lsp](https://github.com/emacs-lsp/lsp-mode/),
  [company](https://github.com/company-mode/company-mode) and
  [flycheck](https://github.com/flycheck/flycheck) packages
- Install [lsp-pyright](https://github.com/emacs-lsp/lsp-pyright) package

```elisp
(use-package lsp-pyright
  :ensure t
  :hook (python-mode . (lambda ()
                          (require 'lsp-pyright)
                          (lsp)))  ; or lsp-deferred
  :init (when (executable-find "python3")
          (setq lsp-pyright-python-executable-cmd "python3"))
  )
```

- Make sure emacs uses the environment where you have installed `boto3-stubs`

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="sublime-text"></a>

### Sublime Text

- Install `boto3-stubs[machinelearning]` with services you use in your
  environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

- Install [LSP-pyright](https://github.com/sublimelsp/LSP-pyright) package

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="other-ides"></a>

### Other IDEs

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

<a id="mypy"></a>

### mypy

- Install `mypy`: `python -m pip install mypy`
- Install `boto3-stubs[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'`
```

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="pyright"></a>

### pyright

- Install `pyright`: `npm i -g pyright`
- Install `boto3-stubs[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

Optionally, you can install `boto3-stubs` to `typings` folder.

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="explicit-type-annotations"></a>

## Explicit type annotations

<a id="client-annotations"></a>

### Client annotations

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

```python
from boto3.session import Session

from mypy_boto3_machinelearning import MachineLearningClient

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

# now client usage is checked by mypy and IDE should provide code completion
```

<a id="paginators-annotations"></a>

### Paginators annotations

`mypy_boto3_machinelearning.paginator` module contains type annotations for all
paginators.

```python
from boto3.session import Session

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

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

# Explicit type annotations are optional here
# Types should be correctly discovered by mypy and IDEs
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")
```

<a id="waiters-annotations"></a>

### Waiters annotations

`mypy_boto3_machinelearning.waiter` module contains type annotations for all
waiters.

```python
from boto3.session import Session

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

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

# Explicit type annotations are optional here
# Types should be correctly discovered by mypy and IDEs
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

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

```python
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,
    MachineLearningServiceName,
    ServiceName,
    ResourceServiceName,
    PaginatorName,
    WaiterName,
    RegionName,
)


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

<a id="typed-dictionaries"></a>

### Typed dictionaries

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

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


def get_structure() -> TagTypeDef:
    return {...}
```

<a id="how-it-works"></a>

## How it works

Fully automated
[mypy-boto3-builder](https://github.com/youtype/mypy_boto3_builder) carefully
generates type annotations for each service, patiently waiting for `boto3`
updates. It delivers a drop-in type annotations for you and makes sure that:

- All available `boto3` services are covered.
- Each public class and method of every `boto3` service gets valid type
  annotations extracted from the documentation (blame `botocore` docs if types
  are incorrect).
- Type annotations include up-to-date documentation.
- Link to documentation is provided for every method.
- Code is processed by [black](https://github.com/psf/black) and
  [isort](https://github.com/PyCQA/isort) for readability.

<a id="what's-new"></a>

## What's new

<a id="implemented-features"></a>

### Implemented features

- Fully type annotated `boto3`, `botocore` and `aiobotocore` libraries
- `mypy`, `pyright`, `VSCode`, `PyCharm`, `Sublime Text` and `Emacs`
  compatibility
- `Client`, `ServiceResource`, `Resource`, `Waiter` `Paginator` type
  annotations for each service
- Generated `TypeDefs` for each service
- Generated `Literals` for each service
- Auto discovery of types for `boto3.client` and `boto3.session` calls
- Auto discovery of types for `session.client` and `session.session` calls
- Auto discovery of types for `client.get_waiter` and `client.get_paginator`
  calls
- Auto discovery of types for `ServiceResource` and `Resource` collections
- Auto discovery of types for `aiobotocore.Session.create_client` calls

<a id="latest-changes"></a>

### Latest changes

Builder changelog can be found in
[Releases](https://github.com/youtype/mypy_boto3_builder/releases).

<a id="versioning"></a>

## Versioning

`mypy-boto3-machinelearning` version is the same as related `boto3` version and
follows [PEP 440](https://www.python.org/dev/peps/pep-0440/) format.

<a id="thank-you"></a>

## Thank you

- [Allie Fitter](https://github.com/alliefitter) for
  [boto3-type-annotations](https://pypi.org/project/boto3-type-annotations/),
  this package is based on top of his work
- [black](https://github.com/psf/black) developers for an awesome formatting
  tool
- [Timothy Edmund Crosley](https://github.com/timothycrosley) for
  [isort](https://github.com/PyCQA/isort) and how flexible it is
- [mypy](https://github.com/python/mypy) developers for doing all dirty work
  for us
- [pyright](https://github.com/microsoft/pyright) team for the new era of typed
  Python

<a id="documentation"></a>

## Documentation

All services type annotations can be found in
[boto3 docs](https://youtype.github.io/boto3_stubs_docs/mypy_boto3_machinelearning/)

<a id="support-and-contributing"></a>

## Support and contributing

This package is auto-generated. Please reports any bugs or request new features
in [mypy-boto3-builder](https://github.com/youtype/mypy_boto3_builder/issues/)
repository.


%package help
Summary:	Development documents and examples for mypy-boto3-machinelearning
Provides:	python3-mypy-boto3-machinelearning-doc
%description help
<a id="mypy-boto3-machinelearning"></a>

# mypy-boto3-machinelearning

[![PyPI - mypy-boto3-machinelearning](https://img.shields.io/pypi/v/mypy-boto3-machinelearning.svg?color=blue)](https://pypi.org/project/mypy-boto3-machinelearning)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mypy-boto3-machinelearning.svg?color=blue)](https://pypi.org/project/mypy-boto3-machinelearning)
[![Docs](https://img.shields.io/readthedocs/mypy-boto3-builder.svg?color=blue)](https://mypy-boto3-builder.readthedocs.io/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/mypy-boto3-machinelearning?color=blue)](https://pypistats.org/packages/mypy-boto3-machinelearning)

![boto3.typed](https://github.com/youtype/mypy_boto3_builder/raw/main/logo.png)

Type annotations for
[boto3.MachineLearning 1.26.0](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/machinelearning.html#MachineLearning)
service compatible with [VSCode](https://code.visualstudio.com/),
[PyCharm](https://www.jetbrains.com/pycharm/),
[Emacs](https://www.gnu.org/software/emacs/),
[Sublime Text](https://www.sublimetext.com/),
[mypy](https://github.com/python/mypy),
[pyright](https://github.com/microsoft/pyright) and other tools.

Generated by
[mypy-boto3-builder 7.11.10](https://github.com/youtype/mypy_boto3_builder).

More information can be found on
[boto3-stubs](https://pypi.org/project/boto3-stubs/) page and in
[mypy-boto3-machinelearning docs](https://youtype.github.io/boto3_stubs_docs/mypy_boto3_machinelearning/).

See how it helps to find and fix potential bugs:

![boto3-stubs demo](https://github.com/youtype/mypy_boto3_builder/raw/main/demo.gif)

- [mypy-boto3-machinelearning](#mypy-boto3-machinelearning)
  - [How to install](#how-to-install)
    - [VSCode extension](#vscode-extension)
    - [From PyPI with pip](#from-pypi-with-pip)
  - [How to uninstall](#how-to-uninstall)
  - [Usage](#usage)
    - [VSCode](#vscode)
    - [PyCharm](#pycharm)
    - [Emacs](#emacs)
    - [Sublime Text](#sublime-text)
    - [Other IDEs](#other-ides)
    - [mypy](#mypy)
    - [pyright](#pyright)
  - [Explicit type annotations](#explicit-type-annotations)
    - [Client annotations](#client-annotations)
    - [Paginators annotations](#paginators-annotations)
    - [Waiters annotations](#waiters-annotations)
    - [Literals](#literals)
    - [Typed dictionaries](#typed-dictionaries)
  - [How it works](#how-it-works)
  - [What's new](#what's-new)
    - [Implemented features](#implemented-features)
    - [Latest changes](#latest-changes)
  - [Versioning](#versioning)
  - [Thank you](#thank-you)
  - [Documentation](#documentation)
  - [Support and contributing](#support-and-contributing)

<a id="how-to-install"></a>

## How to install

<a id="vscode-extension"></a>

### VSCode extension

Add
[AWS Boto3](https://marketplace.visualstudio.com/items?itemName=Boto3typed.boto3-ide)
extension to your VSCode and run `AWS boto3: Quick Start` command.

Click `Modify` and select `boto3 common` and `MachineLearning`.

<a id="from-pypi-with-pip"></a>

### From PyPI with pip

Install `boto3-stubs` for `MachineLearning` service.

```bash
# install with boto3 type annotations
python -m pip install 'boto3-stubs[machinelearning]'


# Lite version does not provide session.client/resource overloads
# it is more RAM-friendly, but requires explicit type annotations
python -m pip install 'boto3-stubs-lite[machinelearning]'


# standalone installation
python -m pip install mypy-boto3-machinelearning
```

<a id="how-to-uninstall"></a>

## How to uninstall

```bash
python -m pip uninstall -y mypy-boto3-machinelearning
```

<a id="usage"></a>

## Usage

<a id="vscode"></a>

### VSCode

- Install
  [Python extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python)
- Install
  [Pylance extension](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance)
- Set `Pylance` as your Python Language Server
- Install `boto3-stubs[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

Both type checking and code completion should now work. No explicit type
annotations required, write your `boto3` code as usual.

<a id="pycharm"></a>

### PyCharm

Install `boto3-stubs-lite[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs-lite[machinelearning]'`
```

Both type checking and code completion should now work. Explicit type
annotations **are required**.

Use `boto3-stubs` package instead for implicit type discovery.

<a id="emacs"></a>

### Emacs

- Install `boto3-stubs` with services you use in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

- Install [use-package](https://github.com/jwiegley/use-package),
  [lsp](https://github.com/emacs-lsp/lsp-mode/),
  [company](https://github.com/company-mode/company-mode) and
  [flycheck](https://github.com/flycheck/flycheck) packages
- Install [lsp-pyright](https://github.com/emacs-lsp/lsp-pyright) package

```elisp
(use-package lsp-pyright
  :ensure t
  :hook (python-mode . (lambda ()
                          (require 'lsp-pyright)
                          (lsp)))  ; or lsp-deferred
  :init (when (executable-find "python3")
          (setq lsp-pyright-python-executable-cmd "python3"))
  )
```

- Make sure emacs uses the environment where you have installed `boto3-stubs`

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="sublime-text"></a>

### Sublime Text

- Install `boto3-stubs[machinelearning]` with services you use in your
  environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

- Install [LSP-pyright](https://github.com/sublimelsp/LSP-pyright) package

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="other-ides"></a>

### Other IDEs

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

<a id="mypy"></a>

### mypy

- Install `mypy`: `python -m pip install mypy`
- Install `boto3-stubs[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'`
```

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="pyright"></a>

### pyright

- Install `pyright`: `npm i -g pyright`
- Install `boto3-stubs[machinelearning]` in your environment:

```bash
python -m pip install 'boto3-stubs[machinelearning]'
```

Optionally, you can install `boto3-stubs` to `typings` folder.

Type checking should now work. No explicit type annotations required, write
your `boto3` code as usual.

<a id="explicit-type-annotations"></a>

## Explicit type annotations

<a id="client-annotations"></a>

### Client annotations

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

```python
from boto3.session import Session

from mypy_boto3_machinelearning import MachineLearningClient

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

# now client usage is checked by mypy and IDE should provide code completion
```

<a id="paginators-annotations"></a>

### Paginators annotations

`mypy_boto3_machinelearning.paginator` module contains type annotations for all
paginators.

```python
from boto3.session import Session

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

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

# Explicit type annotations are optional here
# Types should be correctly discovered by mypy and IDEs
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")
```

<a id="waiters-annotations"></a>

### Waiters annotations

`mypy_boto3_machinelearning.waiter` module contains type annotations for all
waiters.

```python
from boto3.session import Session

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

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

# Explicit type annotations are optional here
# Types should be correctly discovered by mypy and IDEs
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

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

```python
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,
    MachineLearningServiceName,
    ServiceName,
    ResourceServiceName,
    PaginatorName,
    WaiterName,
    RegionName,
)


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

<a id="typed-dictionaries"></a>

### Typed dictionaries

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

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


def get_structure() -> TagTypeDef:
    return {...}
```

<a id="how-it-works"></a>

## How it works

Fully automated
[mypy-boto3-builder](https://github.com/youtype/mypy_boto3_builder) carefully
generates type annotations for each service, patiently waiting for `boto3`
updates. It delivers a drop-in type annotations for you and makes sure that:

- All available `boto3` services are covered.
- Each public class and method of every `boto3` service gets valid type
  annotations extracted from the documentation (blame `botocore` docs if types
  are incorrect).
- Type annotations include up-to-date documentation.
- Link to documentation is provided for every method.
- Code is processed by [black](https://github.com/psf/black) and
  [isort](https://github.com/PyCQA/isort) for readability.

<a id="what's-new"></a>

## What's new

<a id="implemented-features"></a>

### Implemented features

- Fully type annotated `boto3`, `botocore` and `aiobotocore` libraries
- `mypy`, `pyright`, `VSCode`, `PyCharm`, `Sublime Text` and `Emacs`
  compatibility
- `Client`, `ServiceResource`, `Resource`, `Waiter` `Paginator` type
  annotations for each service
- Generated `TypeDefs` for each service
- Generated `Literals` for each service
- Auto discovery of types for `boto3.client` and `boto3.session` calls
- Auto discovery of types for `session.client` and `session.session` calls
- Auto discovery of types for `client.get_waiter` and `client.get_paginator`
  calls
- Auto discovery of types for `ServiceResource` and `Resource` collections
- Auto discovery of types for `aiobotocore.Session.create_client` calls

<a id="latest-changes"></a>

### Latest changes

Builder changelog can be found in
[Releases](https://github.com/youtype/mypy_boto3_builder/releases).

<a id="versioning"></a>

## Versioning

`mypy-boto3-machinelearning` version is the same as related `boto3` version and
follows [PEP 440](https://www.python.org/dev/peps/pep-0440/) format.

<a id="thank-you"></a>

## Thank you

- [Allie Fitter](https://github.com/alliefitter) for
  [boto3-type-annotations](https://pypi.org/project/boto3-type-annotations/),
  this package is based on top of his work
- [black](https://github.com/psf/black) developers for an awesome formatting
  tool
- [Timothy Edmund Crosley](https://github.com/timothycrosley) for
  [isort](https://github.com/PyCQA/isort) and how flexible it is
- [mypy](https://github.com/python/mypy) developers for doing all dirty work
  for us
- [pyright](https://github.com/microsoft/pyright) team for the new era of typed
  Python

<a id="documentation"></a>

## Documentation

All services type annotations can be found in
[boto3 docs](https://youtype.github.io/boto3_stubs_docs/mypy_boto3_machinelearning/)

<a id="support-and-contributing"></a>

## Support and contributing

This package is auto-generated. Please reports any bugs or request new features
in [mypy-boto3-builder](https://github.com/youtype/mypy_boto3_builder/issues/)
repository.


%prep
%autosetup -n mypy-boto3-machinelearning-1.26.0.post1

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-mypy-boto3-machinelearning -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Sun Apr 23 2023 Python_Bot <Python_Bot@openeuler.org> - 1.26.0.post1-1
- Package Spec generated