Examples#
Index > MachineLearning > Examples
Auto-generated documentation for MachineLearning type annotations stubs module mypy-boto3-machinelearning.
Client#
Implicit type annotations#
Can be used with boto3-stubs[machinelearning]
package installed.
Write your MachineLearning
code as usual,
type checking and code completion should work out of the box.
Client method usage example#
# MachineLearningClient usage example
from boto3.session import Session
session = Session()
client = session.client("machinelearning") # (1)
result = client.add_tags() # (2)
- client: MachineLearningClient
- result: AddTagsOutputTypeDef
Paginator usage example#
# DescribeBatchPredictionsPaginator usage example
from boto3.session import Session
session = Session()
client = session.client("machinelearning") # (1)
paginator = client.get_paginator("describe_batch_predictions") # (2)
for item in paginator.paginate(...):
print(item) # (3)
- client: MachineLearningClient
- paginator: DescribeBatchPredictionsPaginator
- item: DescribeBatchPredictionsOutputTypeDef
Waiter usage example#
# BatchPredictionAvailableWaiter usage example
from boto3.session import Session
session = Session()
client = session.client("machinelearning") # (1)
waiter = client.get_waiter("batch_prediction_available") # (2)
waiter.wait(...)
- client: MachineLearningClient
- waiter: BatchPredictionAvailableWaiter
Explicit type annotations#
With boto3-stubs-lite[machinelearning]
or a standalone mypy_boto3_machinelearning
package, you have to explicitly specify client: MachineLearningClient
type annotation.
All other type annotations are optional, as types should be discovered automatically. However, these type annotations can be helpful in your functions and methods.
Client method usage example#
# MachineLearningClient usage example with type annotations
from boto3.session import Session
from mypy_boto3_machinelearning.client import MachineLearningClient
from mypy_boto3_machinelearning.type_defs import AddTagsOutputTypeDef
from mypy_boto3_machinelearning.type_defs import AddTagsInputTypeDef
session = Session()
client: MachineLearningClient = session.client("machinelearning")
kwargs: AddTagsInputTypeDef = {...}
result: AddTagsOutputTypeDef = client.add_tags(**kwargs)
Paginator usage example#
# DescribeBatchPredictionsPaginator usage example with type annotations
from boto3.session import Session
from mypy_boto3_machinelearning.client import MachineLearningClient
from mypy_boto3_machinelearning.paginator import DescribeBatchPredictionsPaginator
from mypy_boto3_machinelearning.type_defs import DescribeBatchPredictionsOutputTypeDef
session = Session()
client: MachineLearningClient = session.client("machinelearning")
paginator: DescribeBatchPredictionsPaginator = client.get_paginator("describe_batch_predictions")
for item in paginator.paginate(...):
item: DescribeBatchPredictionsOutputTypeDef
print(item)
Waiter usage example#
# BatchPredictionAvailableWaiter usage example with type annotations
from boto3.session import Session
from mypy_boto3_machinelearning.client import MachineLearningClient
from mypy_boto3_machinelearning.waiter import BatchPredictionAvailableWaiter
session = Session()
client: MachineLearningClient = session.client("machinelearning")
waiter: BatchPredictionAvailableWaiter = client.get_waiter("batch_prediction_available")
waiter.wait(...)