mypy-boto3-chatbot Type Annotations

Warnings

• breaking Starting with `mypy-boto3-builder` version 8.12.0, support for Python 3.8 has been removed for all generated stub packages, including `mypy-boto3-chatbot`. The library now requires Python >=3.9.
  Fix: Upgrade your Python environment to 3.9 or newer, or pin `mypy-boto3-builder` and associated stub packages to versions older than 8.12.0.
• breaking Version 8.9.0 of `mypy-boto3-builder` introduced breaking changes to `TypeDef` naming conventions. Some TypeDefs (e.g., method argument types) now use shorter names (e.g., `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`).
  Fix: Update your code to use the new `TypeDef` names. Refer to the specific service's documentation or your IDE's autocompletion for the correct names.
• gotcha When using `mypy-boto3-chatbot` as a standalone package or the `types-boto3-lite` variants, explicit type annotations are necessary for `boto3.client()` and `session.client()` calls to leverage full static analysis and IDE autocompletion. The full `types-boto3` package provides function overloads for automatic type inference.
  Fix: Always explicitly type your `boto3.client()` calls, e.g., `client: ChatbotClient = boto3.client("chatbot")`.
• gotcha PyCharm users might experience performance slowdowns when working with `Literal` overloads in `mypy-boto3` packages. As a workaround, the `types-boto3-lite` versions are often recommended, which typically necessitate explicit type annotations.
  Fix: Consider installing `types-boto3-lite[chatbot]` instead of `types-boto3[chatbot]` or the standalone `mypy-boto3-chatbot`, and explicitly type your client and responses.

Install

• pip install mypy-boto3-chatbot Standalone package
• pip install 'types-boto3[chatbot]' Recommended (integrates with types-boto3)

Imports

• ChatbotClient

  from mypy_boto3_chatbot.client import ChatbotClient

• AccountPreferencesTypeDef

  from mypy_boto3_chatbot.type_defs import AccountPreferencesTypeDef

• CustomActionAttachmentCriteriaOperatorType

  from mypy_boto3_chatbot.literals import CustomActionAttachmentCriteriaOperatorType

• ListMicrosoftTeamsChannelConfigurationsPaginator

  from mypy_boto3_chatbot.paginator import ListMicrosoftTeamsChannelConfigurationsPaginator

  Paginator types are in the `paginator` submodule, not directly in `client`.

Quickstart

This example demonstrates how to use `mypy-boto3-chatbot` to add type hints to your `boto3` Chatbot client. By explicitly annotating the client and its response, you gain static analysis benefits like autocompletion and type validation.

import boto3
from typing import TYPE_CHECKING, Dict, Any

# Ensure boto3 is installed for runtime functionality
# pip install boto3

if TYPE_CHECKING:
    from mypy_boto3_chatbot.client import ChatbotClient
    from mypy_boto3_chatbot.type_defs import DescribeChatbotSourcesResponseTypeDef

def get_chatbot_sources(aws_region: str = "us-east-1") -> Dict[str, Any]:
    """
    Retrieves and type-checks AWS Chatbot sources using mypy-boto3-chatbot stubs.
    """
    # boto3.client returns an untyped client by default
    client: ChatbotClient = boto3.client("chatbot", region_name=aws_region)
    
    # The response is now type-checked, providing autocompletion and validation
    response: DescribeChatbotSourcesResponseTypeDef = client.describe_chatbot_sources()
    
    print(f"Chatbot sources response: {response}")
    return response

if __name__ == "__main__":
    # This assumes AWS credentials are configured (e.g., via environment variables or ~/.aws/credentials)
    try:
        sources = get_chatbot_sources()
        print(f"Successfully retrieved chatbot sources with HTTP status: {sources['ResponseMetadata']['HTTPStatusCode']}")
    except Exception as e:
        print(f"An error occurred while fetching chatbot sources: {e}")