types-aiobotocore-emr-containers
Advanced tools
Type annotations for aiobotocore EMRContainers 2.21.1 service generated with mypy-boto3-builder 8.10.0
Type annotations for aiobotocore EMRContainers 2.21.1 compatible with VSCode, PyCharm, Emacs, Sublime Text, mypy, pyright and other tools.
Generated with mypy-boto3-builder 8.10.0.
More information can be found on types-aiobotocore page and in types-aiobotocore-emr-containers docs.
See how it helps you find and fix potential bugs:
You can generate type annotations for aiobotocore package locally with
mypy-boto3-builder. Use
uv for build
isolation.
uvx --with 'aiobotocore==2.21.1' mypy-boto3-builderaiobotocore AWS SDK.EMRContainers service.Install types-aiobotocore for EMRContainers service.
# install with aiobotocore type annotations
python -m pip install 'types-aiobotocore[emr-containers]'
# 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[emr-containers]'
# standalone installation
python -m pip install types-aiobotocore-emr-containers
python -m pip uninstall -y types-aiobotocore-emr-containers
Pylance as your Python Language Servertypes-aiobotocore[emr-containers] in your environment:python -m pip install 'types-aiobotocore[emr-containers]'
Both type checking and code completion should now work. No explicit type
annotations required, write your aiobotocore code as usual.
⚠️ Due to slow PyCharm performance on
Literaloverloads (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
PyCharmtype checker and use mypy or pyright instead.
⚠️ To continue using
PyCharmtype checker, you can try to replacetypes-aiobotocorewith types-aiobotocore-lite:
pip uninstall types-aiobotocore
pip install types-aiobotocore-lite
Install types-aiobotocore[emr-containers] in your environment:
python -m pip install 'types-aiobotocore[emr-containers]'
Both type checking and code completion should now work.
types-aiobotocore with services you use in your environment:python -m pip install 'types-aiobotocore[emr-containers]'
(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"))
)
types-aiobotocoreType checking should now work. No explicit type annotations required, write
your aiobotocore code as usual.
types-aiobotocore[emr-containers] with services you use in your
environment:python -m pip install 'types-aiobotocore[emr-containers]'
Type checking should now work. No explicit type annotations required, write
your aiobotocore code as usual.
Not tested, but as long as your IDE supports mypy or pyright, everything
should work.
mypy: python -m pip install mypytypes-aiobotocore[emr-containers] in your environment:python -m pip install 'types-aiobotocore[emr-containers]'
Type checking should now work. No explicit type annotations required, write
your aiobotocore code as usual.
pyright: npm i -g pyrighttypes-aiobotocore[emr-containers] in your environment:python -m pip install 'types-aiobotocore[emr-containers]'
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.
It is totally safe to use TYPE_CHECKING flag in order to avoid
types-aiobotocore-emr-containers 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
...
EMRContainersClient provides annotations for
session.create_client("emr-containers").
from aiobotocore.session import get_session
from types_aiobotocore_emr_containers import EMRContainersClient
session = get_session()
async with session.create_client("emr-containers") as client:
client: EMRContainersClient
# now client usage is checked by mypy and IDE should provide code completion
types_aiobotocore_emr_containers.paginator module contains type annotations
for all paginators.
from aiobotocore.session import get_session
from types_aiobotocore_emr_containers import EMRContainersClient
from types_aiobotocore_emr_containers.paginator import (
ListJobRunsPaginator,
ListJobTemplatesPaginator,
ListManagedEndpointsPaginator,
ListSecurityConfigurationsPaginator,
ListVirtualClustersPaginator,
)
session = get_session()
async with session.create_client("emr-containers") as client:
client: EMRContainersClient
# Explicit type annotations are optional here
# Types should be correctly discovered by mypy and IDEs
list_job_runs_paginator: ListJobRunsPaginator = client.get_paginator("list_job_runs")
list_job_templates_paginator: ListJobTemplatesPaginator = client.get_paginator(
"list_job_templates"
)
list_managed_endpoints_paginator: ListManagedEndpointsPaginator = client.get_paginator(
"list_managed_endpoints"
)
list_security_configurations_paginator: ListSecurityConfigurationsPaginator = (
client.get_paginator("list_security_configurations")
)
list_virtual_clusters_paginator: ListVirtualClustersPaginator = client.get_paginator(
"list_virtual_clusters"
)
types_aiobotocore_emr_containers.literals module contains literals extracted
from shapes that can be used in user code for type checking.
Full list of EMRContainers Literals can be found in
docs.
from types_aiobotocore_emr_containers.literals import AllowAWSToRetainLogsType
def check_value(value: AllowAWSToRetainLogsType) -> bool: ...
types_aiobotocore_emr_containers.type_defs module contains structures and
shapes assembled to typed dictionaries and unions for additional type checking.
Full list of EMRContainers TypeDefs can be found in
docs.
# TypedDict usage example
from types_aiobotocore_emr_containers.type_defs import CancelJobRunRequestTypeDef
def get_value() -> CancelJobRunRequestTypeDef:
return {
"id": ...,
}
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:
aiobotocore services are covered.aiobotocore service gets valid type
annotations extracted from botocore schemas.boto3, botocore, aiobotocore and aioboto3
librariesmypy, pyright, VSCode, PyCharm, Sublime Text and Emacs
compatibilityClient, ServiceResource, Resource, Waiter Paginator type
annotations for each serviceTypeDefs for each serviceLiterals for each serviceboto3.client and boto3.resource callssession.client and session.resource callsclient.get_waiter and client.get_paginator
callsServiceResource and Resource collectionsaiobotocore.Session.create_client callsBuilder changelog can be found in Releases.
types-aiobotocore-emr-containers version is the same as related aiobotocore
version and follows
Python Packaging version specifiers.
All services type annotations can be found in aiobotocore docs
This package is auto-generated. Please reports any bugs or request new features in mypy-boto3-builder repository.
FAQs
Type annotations for aiobotocore EMRContainers 2.21.1 service generated with mypy-boto3-builder 8.10.0
We found that types-aiobotocore-emr-containers demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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