Type annotations for boto3.MachineLearning 1.12.3 service, generated by mypy-boto3-buider 1.0.1
Project description
mypy-boto3-machinelearning
Type annotations for boto3.MachineLearning 1.12.3 service compatible with mypy, VSCode, PyCharm and other tools.
Generated by mypy-boto3-buider 1.0.1.
More information can be found on boto3-stubs page.
How to use
Type checking
Make sure you have mypy installed and activated in your IDE.
Install boto3-stubs
for MachineLearning
service.
python -m pip install boto3-stubs[mypy-boto3-machinelearning]
Use boto3
with mypy_boto3
in your project and enjoy type checking and auto-complete.
import boto3
from mypy_boto3 import machinelearning
# alternative import if you do not want to install mypy_boto3 package
# import mypy_boto3_machinelearning as machinelearning
# Use this client as usual, now mypy can check if your code is valid.
# Check if your IDE supports function overloads,
# you probably do not need explicit type annotations
# client = boto3.client("machinelearning")
client: machinelearning.MachineLearningClient = boto3.client("machinelearning")
# works for session as well
session = boto3.session.Session(region="us-west-1")
session_client: machinelearning.MachineLearningClient = session.client("machinelearning")
# Waiters need type annotation on creation
batch_prediction_available_waiter: machinelearning.BatchPredictionAvailableWaiter = client.get_waiter("batch_prediction_available")
data_source_available_waiter: machinelearning.DataSourceAvailableWaiter = client.get_waiter("data_source_available")
evaluation_available_waiter: machinelearning.EvaluationAvailableWaiter = client.get_waiter("evaluation_available")
ml_model_available_waiter: machinelearning.MLModelAvailableWaiter = client.get_waiter("ml_model_available")
# Paginators need type annotation on creation
describe_batch_predictions_paginator: machinelearning.DescribeBatchPredictionsPaginator = client.get_paginator("describe_batch_predictions")
describe_data_sources_paginator: machinelearning.DescribeDataSourcesPaginator = client.get_paginator("describe_data_sources")
describe_evaluations_paginator: machinelearning.DescribeEvaluationsPaginator = client.get_paginator("describe_evaluations")
describe_ml_models_paginator: machinelearning.DescribeMLModelsPaginator = client.get_paginator("describe_ml_models")
How it works
Fully automated 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 (blamebotocore
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 for readability.
Project details
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