mypy-boto3-personalize-runtime type stubs

1.42.3 · active · verified Sat Apr 11

mypy-boto3-personalize-runtime provides high-quality type annotations for the AWS SDK for Python (boto3)'s PersonalizeRuntime service. It enables static type checking with tools like Mypy, Pyright, and enhances IDE features like autocompletion for boto3 clients, responses, and related data structures. The current version, 1.42.3, is generated with mypy-boto3-builder 8.12.0 and is updated frequently to align with boto3 releases and new AWS service features.

Warnings

breaking As of `mypy-boto3-builder` version 8.12.0 (which generated this stub version), support for Python 3.8 has been removed. Users on Python 3.8 should upgrade their Python version to 3.9+ or use an older `mypy-boto3` stub package version.
Fix: Upgrade Python to 3.9 or higher. If unable to upgrade, pin an older `mypy-boto3-personalize-runtime` version that supported Python 3.8.
breaking The `mypy-boto3-builder` (version 8.9.0 and later) introduced changes to `TypeDef` naming conventions. Some generated type definition names may have been shortened or have their `Extra` postfix moved. For example, `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`. While this specific package is for 'personalize-runtime', such a change in the builder could affect similar patterns in type names across services.
Fix: Review your code for `_TypeDef` imports and usage, and update names according to the new conventions as indicated by your type checker or documentation.
gotcha When using standalone `mypy-boto3-personalize-runtime` packages (rather than the umbrella `boto3-stubs` with extras), explicit type annotations for `boto3.client()` calls are required for proper type checking and IDE autocompletion. The type checker will not automatically infer the specific client type without the annotation.
Fix: Always explicitly type hint your boto3 client objects, e.g., `client: PersonalizeRuntimeClient = boto3.client("personalize-runtime")`.
gotcha PyCharm users might experience slow performance or high CPU usage due to how it handles `Literal` overloads within `mypy-boto3` stubs. It is sometimes recommended to use `boto3-stubs-lite` (a more RAM-friendly version) or disable PyCharm's internal type checker and rely on `mypy` or `pyright` instead.
Fix: Consider installing `boto3-stubs-lite[personalize-runtime]` instead of the full package, or configure PyCharm to use an external type checker like `mypy` or `pyright`.
gotcha Pylint might raise `undefined-variable` warnings when using `TYPE_CHECKING` guards to conditionally import `mypy-boto3` types. This is a known issue with Pylint's interaction with the `TYPE_CHECKING` block.
Fix: To resolve Pylint warnings, assign `object` to the type symbols outside the `TYPE_CHECKING` block. For example: `if TYPE_CHECKING: from mypy_boto3_personalize_runtime.client import PersonalizeRuntimeClient else: PersonalizeRuntimeClient = object`.

Install

pip install mypy-boto3-personalize-runtime boto3 Install with pip

Imports

PersonalizeRuntimeClient

from mypy_boto3_personalize_runtime.client import PersonalizeRuntimeClient

GetRecommendationsResponseTypeDef

from mypy_boto3_personalize_runtime.type_defs import GetRecommendationsResponseTypeDef

boto3
```
import boto3
```
mypy-boto3 packages provide type stubs, not runtime modules. Use actual boto3 for client instantiation.

Quickstart

This example demonstrates how to create a type-hinted `PersonalizeRuntimeClient` using `boto3` and explicitly annotate the client object and the response from `get_recommendations`. This allows static type checkers to validate your usage of the client and its response, catching potential errors before runtime. Replace placeholder values with your actual AWS campaign ARN and user ID.

import boto3
from typing import TYPE_CHECKING
import os

if TYPE_CHECKING:
    from mypy_boto3_personalize_runtime.client import PersonalizeRuntimeClient
    from mypy_boto3_personalize_runtime.type_defs import GetRecommendationsResponseTypeDef

def get_personalize_recommendations(
    campaign_arn: str, user_id: str, num_results: int = 10
) -> GetRecommendationsResponseTypeDef:
    """Gets recommendations from AWS Personalize Runtime."""
    client: PersonalizeRuntimeClient = boto3.client(
        "personalize-runtime",
        region_name=os.environ.get('AWS_REGION', 'us-east-1'),
        aws_access_key_id=os.environ.get('AWS_ACCESS_KEY_ID', ''),
        aws_secret_access_key=os.environ.get('AWS_SECRET_ACCESS_KEY', '')
    )
    
    response: GetRecommendationsResponseTypeDef = client.get_recommendations(
        campaignArn=campaign_arn,
        userId=user_id,
        numResults=num_results
    )
    return response

# Example usage (requires AWS credentials and a configured Personalize campaign)
# if __name__ == "__main__":
#     campaign_arn_example = "arn:aws:personalize:us-east-1:123456789012:campaign/your-campaign-name"
#     user_id_example = "test_user_1"
#     try:
#         recommendations = get_personalize_recommendations(campaign_arn_example, user_id_example)
#         print("Recommended Items:")
#         for item in recommendations.get("itemList", []):
#             print(f"  Item ID: {item.get('itemId')}")
#     except Exception as e:
#         print(f"Error getting recommendations: {e}")

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