mypy-boto3-machinelearning 1.14.0.2

Type annotations for boto3.MachineLearning 1.14.0 service, generated by mypy-boto3-buider 2.2.0

mypy-boto3-machinelearning

Type annotations for boto3.MachineLearning 1.14.0 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 expected
• PyCharm also supports function overloads, but consumes a lot of RAM, use carefully if you have many services installed
• VSCode 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")