Type annotations for boto3.MachineLearning 1.14.22 service, generated by mypy-boto3-buider 2.2.0
Project description
mypy-boto3-machinelearning
Type annotations for boto3.MachineLearning 1.14.22 service compatible with mypy, VSCode, PyCharm and other tools.
Generated by mypy-boto3-buider 2.2.0.
More information can be found on boto3-stubs page.
How to install
Make sure you have mypy installed and activated in your IDE.
Install boto3-stubs
for MachineLearning
service.
python -m pip install boto3-stubs[machinelearning]
How to use
Client annotations
MachineLearningClient
provides annotations for boto3.client("machinelearning")
.
import boto3
from mypy_boto3_machinelearning import MachineLearningClient
from mypy_boto3_machinelearning.paginator import (
DescribeBatchPredictionsPaginator,
DescribeDataSourcesPaginator,
DescribeEvaluationsPaginator,
DescribeMLModelsPaginator,
)
from mypy_boto3_machinelearning.type_defs import BatchPredictionTypeDef, ...
from mypy_boto3_machinelearning.waiter import (
BatchPredictionAvailableWaiter,
DataSourceAvailableWaiter,
EvaluationAvailableWaiter,
MLModelAvailableWaiter,
)
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.
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.
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")
Typed dictionations
mypy_boto3_machinelearning.type_defs
module contains structures and shapes assembled
to typed dictionaries for additional type checking.
def get_structure() -> BatchPredictionTypeDef:
return {
...
}
Dynamic type annotations
mypy_boto3
command generates boto3.client/resource
type annotations for
mypy_boto3_machinelearning
and other installed services.
# Run this command after you add or remove service packages
python -m mypy_boto3
Generated type annotations provide overloads for boto3.client
and boto3.resource
,
boto3.Session.client
and boto3.Session.resource
functions,
so explicit type annotations are not needed.
mypy
supports function overloads as expectedPyCharm
also supports function overloads, but consumes a lot of RAM, use carefully if you have many services installedVSCode
does not currently support function overloads, use explicit type annotations
# Type is discovered correctly by mypy and PyCharm
# VSCode still needs explicit type annotations
client = boto3.client("machinelearning")
session_client = boto3.Session().client("machinelearning")
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