Install & Compatibility
Where this runs
tested against v1.43.0 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.910 runs
installs and imports cleanly · install 0.0s · import 0.000s · 68.3MB
glibcpy 3.10–3.910 runs
installs and imports cleanly · install 3.2s · import 0.000s · 19MB
67MB installed
● package 67MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
ChatbotClient
✓ from mypy_boto3_chatbot import ChatbotClient
✗ from mypy_boto3_chatbot import ChatbotClient
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}")
Debug
Known issues
breakingStarting 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.fixUpgrade your Python environment to 3.9 or newer, or pin `mypy-boto3-builder` and associated stub packages to versions older than 8.12.0.
affects: mypy-boto3-builder >=8.12.0
breakingVersion 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`).fixUpdate your code to use the new `TypeDef` names. Refer to the specific service's documentation or your IDE's autocompletion for the correct names.
affects: mypy-boto3-builder >=8.9.0
gotchaWhen 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.fixAlways explicitly type your `boto3.client()` calls, e.g., `client: ChatbotClient = boto3.client("chatbot")`. affects: All versions
gotchaPyCharm 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.fixConsider installing `types-boto3-lite[chatbot]` instead of `types-boto3[chatbot]` or the standalone `mypy-boto3-chatbot`, and explicitly type your client and responses.
affects: All versions
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Version history
1.43.0latest on PyPI · released Apr 29, 2026
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Dependencies
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