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Type annotations for aiobotocore CleanRoomsML 3.3.0 service generated with mypy-boto3-builder 8.12.0

Project description

types-aiobotocore-cleanroomsml

PyPI - types-aiobotocore-cleanroomsml PyPI - Python Version Docs PyPI - Downloads

boto3.typed

Type annotations for aiobotocore CleanRoomsML 3.3.0 compatible with VSCode, PyCharm, Emacs, Sublime Text, mypy, pyright and other tools.

Generated with mypy-boto3-builder 8.12.0.

More information can be found on types-aiobotocore page and in types-aiobotocore-cleanroomsml docs.

See how it helps you find and fix potential bugs:

types-boto3 demo

How to install

Generate locally (recommended)

You can generate type annotations for aiobotocore package locally with mypy-boto3-builder. Use uv for build isolation.

  1. Run mypy-boto3-builder in your package root directory: uvx --with 'aiobotocore==3.3.0' mypy-boto3-builder
  2. Select aiobotocore AWS SDK.
  3. Add CleanRoomsML service.
  4. Use provided commands to install generated packages.

From PyPI with pip

Install types-aiobotocore for CleanRoomsML service.

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

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

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

How to uninstall

python -m pip uninstall -y types-aiobotocore-cleanroomsml

Usage

VSCode

python -m pip install 'types-aiobotocore[cleanroomsml]'

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

PyCharm

⚠️ Due to slow PyCharm performance on Literal overloads (issue PY-40997), it is recommended to use types-aiobotocore-lite until the issue is resolved.

⚠️ If you experience slow performance and high CPU usage, try to disable PyCharm type checker and use mypy or pyright instead.

⚠️ To continue using PyCharm type checker, you can try to replace types-aiobotocore with types-aiobotocore-lite:

pip uninstall types-aiobotocore
pip install types-aiobotocore-lite

Install types-aiobotocore[cleanroomsml] in your environment:

python -m pip install 'types-aiobotocore[cleanroomsml]'

Both type checking and code completion should now work.

Emacs

  • Install types-aiobotocore with services you use in your environment:
python -m pip install 'types-aiobotocore[cleanroomsml]'
(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 types-aiobotocore

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

Sublime Text

  • Install types-aiobotocore[cleanroomsml] with services you use in your environment:
python -m pip install 'types-aiobotocore[cleanroomsml]'

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

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[cleanroomsml] in your environment:
python -m pip install 'types-aiobotocore[cleanroomsml]'

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

pyright

  • Install pyright: npm i -g pyright
  • Install types-aiobotocore[cleanroomsml] in your environment:
python -m pip install 'types-aiobotocore[cleanroomsml]'

Optionally, you can install types-aiobotocore to typings directory.

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

Pylint compatibility

It is totally safe to use TYPE_CHECKING flag in order to avoid types-aiobotocore-cleanroomsml dependency in production. However, there is an issue in pylint that it complains about undefined variables. To fix it, set all types to object in non-TYPE_CHECKING mode.

from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from types_aiobotocore_ec2 import EC2Client, EC2ServiceResource
    from types_aiobotocore_ec2.waiters import BundleTaskCompleteWaiter
    from types_aiobotocore_ec2.paginators import DescribeVolumesPaginator
else:
    EC2Client = object
    EC2ServiceResource = object
    BundleTaskCompleteWaiter = object
    DescribeVolumesPaginator = object

...

Explicit type annotations

Client annotations

CleanRoomsMLClient provides annotations for session.create_client("cleanroomsml").

from aiobotocore.session import get_session

from types_aiobotocore_cleanroomsml import CleanRoomsMLClient

session = get_session()
async with session.create_client("cleanroomsml") as client:
    client: CleanRoomsMLClient
    # now client usage is checked by mypy and IDE should provide code completion

Paginators annotations

types_aiobotocore_cleanroomsml.paginator module contains type annotations for all paginators.

from aiobotocore.session import get_session

from types_aiobotocore_cleanroomsml import CleanRoomsMLClient
from types_aiobotocore_cleanroomsml.paginator import (
    ListAudienceExportJobsPaginator,
    ListAudienceGenerationJobsPaginator,
    ListAudienceModelsPaginator,
    ListCollaborationConfiguredModelAlgorithmAssociationsPaginator,
    ListCollaborationMLInputChannelsPaginator,
    ListCollaborationTrainedModelExportJobsPaginator,
    ListCollaborationTrainedModelInferenceJobsPaginator,
    ListCollaborationTrainedModelsPaginator,
    ListConfiguredAudienceModelsPaginator,
    ListConfiguredModelAlgorithmAssociationsPaginator,
    ListConfiguredModelAlgorithmsPaginator,
    ListMLInputChannelsPaginator,
    ListTrainedModelInferenceJobsPaginator,
    ListTrainedModelVersionsPaginator,
    ListTrainedModelsPaginator,
    ListTrainingDatasetsPaginator,
)

session = get_session()
async with session.create_client("cleanroomsml") as client:
    client: CleanRoomsMLClient

    # Explicit type annotations are optional here
    # Types should be correctly discovered by mypy and IDEs
    list_audience_export_jobs_paginator: ListAudienceExportJobsPaginator = client.get_paginator(
        "list_audience_export_jobs"
    )
    list_audience_generation_jobs_paginator: ListAudienceGenerationJobsPaginator = (
        client.get_paginator("list_audience_generation_jobs")
    )
    list_audience_models_paginator: ListAudienceModelsPaginator = client.get_paginator(
        "list_audience_models"
    )
    list_collaboration_configured_model_algorithm_associations_paginator: ListCollaborationConfiguredModelAlgorithmAssociationsPaginator = client.get_paginator(
        "list_collaboration_configured_model_algorithm_associations"
    )
    list_collaboration_ml_input_channels_paginator: ListCollaborationMLInputChannelsPaginator = (
        client.get_paginator("list_collaboration_ml_input_channels")
    )
    list_collaboration_trained_model_export_jobs_paginator: ListCollaborationTrainedModelExportJobsPaginator = client.get_paginator(
        "list_collaboration_trained_model_export_jobs"
    )
    list_collaboration_trained_model_inference_jobs_paginator: ListCollaborationTrainedModelInferenceJobsPaginator = client.get_paginator(
        "list_collaboration_trained_model_inference_jobs"
    )
    list_collaboration_trained_models_paginator: ListCollaborationTrainedModelsPaginator = (
        client.get_paginator("list_collaboration_trained_models")
    )
    list_configured_audience_models_paginator: ListConfiguredAudienceModelsPaginator = (
        client.get_paginator("list_configured_audience_models")
    )
    list_configured_model_algorithm_associations_paginator: ListConfiguredModelAlgorithmAssociationsPaginator = client.get_paginator(
        "list_configured_model_algorithm_associations"
    )
    list_configured_model_algorithms_paginator: ListConfiguredModelAlgorithmsPaginator = (
        client.get_paginator("list_configured_model_algorithms")
    )
    list_ml_input_channels_paginator: ListMLInputChannelsPaginator = client.get_paginator(
        "list_ml_input_channels"
    )
    list_trained_model_inference_jobs_paginator: ListTrainedModelInferenceJobsPaginator = (
        client.get_paginator("list_trained_model_inference_jobs")
    )
    list_trained_model_versions_paginator: ListTrainedModelVersionsPaginator = client.get_paginator(
        "list_trained_model_versions"
    )
    list_trained_models_paginator: ListTrainedModelsPaginator = client.get_paginator(
        "list_trained_models"
    )
    list_training_datasets_paginator: ListTrainingDatasetsPaginator = client.get_paginator(
        "list_training_datasets"
    )

Literals

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

Full list of CleanRoomsML Literals can be found in docs.

from types_aiobotocore_cleanroomsml.literals import AccessBudgetTypeType


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

Type definitions

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

Full list of CleanRoomsML TypeDefs can be found in docs.

# TypedDict usage example
from types_aiobotocore_cleanroomsml.type_defs import AccessBudgetDetailsTypeDef


def get_value() -> AccessBudgetDetailsTypeDef:
    return {
        "startTime": ...,
    }

How it works

Fully automated mypy-boto3-builder carefully generates type annotations for each service, patiently waiting for aiobotocore updates. It delivers drop-in type annotations for you and makes sure that:

  • All available aiobotocore services are covered.
  • Each public class and method of every aiobotocore service gets valid type annotations extracted from botocore schemas.
  • Type annotations include up-to-date documentation.
  • Link to documentation is provided for every method.
  • Code is processed by ruff for readability.

What's new

Implemented features

  • Fully type annotated boto3, botocore, aiobotocore and aioboto3 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.resource calls
  • Auto discovery of types for session.client and session.resource 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

Latest changes

Builder changelog can be found in Releases.

Versioning

types-aiobotocore-cleanroomsml version is the same as related aiobotocore version and follows Python Packaging version specifiers.

Thank you

Documentation

All services type annotations can be found in aiobotocore docs

Support and contributing

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

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