mypy-boto3-pipes Type Annotations

Warnings

• breaking Support for Python 3.8 was removed in `mypy-boto3-builder` version 8.12.0, which generates these stubs. Ensure your environment uses Python 3.9 or higher.
  Fix: Upgrade Python to 3.9 or newer.
• breaking TypeDef names were shortened in `mypy-boto3-builder` 8.9.0 (e.g., `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`). If you manually import TypeDefs, their names might have changed.
  Fix: Review your explicit `from mypy_boto3_pipes.type_defs import ...` statements and adjust to the new, shorter names if applicable.
• gotcha This library provides only type stubs. You must install `boto3` (the actual AWS SDK) separately for your code to run. `mypy-boto3-pipes` provides no runtime functionality.
  Fix: Ensure `pip install boto3` is part of your project's dependencies.
• gotcha The version of `mypy-boto3-pipes` should ideally match the major and minor version of your installed `boto3` library for full compatibility and accurate type hints.
  Fix: Periodically update `mypy-boto3-pipes` along with `boto3` to maintain type accuracy. Check the `mypy-boto3` documentation for versioning guidance.
• gotcha For production environments, it is recommended to wrap imports of `mypy-boto3` stubs within `if TYPE_CHECKING:` blocks to prevent them from becoming runtime dependencies.
  Fix: Use `from typing import TYPE_CHECKING` and conditionally import stubs: `if TYPE_CHECKING: from mypy_boto3_pipes.client import PipesClient`.
• gotcha Users of PyCharm may experience slow performance or high CPU usage due to `Literal` overloads. Consider using `mypy-boto3-pipes-lite` or an external type checker like Mypy/Pyright.
  Fix: Install `mypy-boto3-pipes-lite` instead, or disable PyCharm's internal type checker and use Mypy/Pyright.

Install

• pip install mypy-boto3-pipes boto3 mypy Install library, runtime, and type checker

Imports

• PipesClient

  from mypy_boto3_pipes.client import PipesClient

  Use this for explicit type hinting of the boto3 EventBridgePipes client.
• EventBridgePipesServiceName

  from mypy_boto3_pipes.literals import EventBridgePipesServiceName

  Provides a literal type for the service name 'pipes' for stricter type checking.
• PipeStateTypeDef

  from mypy_boto3_pipes.type_defs import PipeStateTypeDef

  Provides type definitions for service-specific structures (e.g., input/output dictionaries).

Quickstart

This quickstart demonstrates how to initialize a `boto3` client for EventBridge Pipes with type hints from `mypy-boto3-pipes` and perform a simple `list_pipes` operation. The `TYPE_CHECKING` block ensures that `mypy-boto3-pipes` is only a development dependency.

import boto3
import os
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from mypy_boto3_pipes.client import PipesClient
    from mypy_boto3_pipes.type_defs import ListPipesResponseTypeDef

# Ensure boto3 is configured, e.g., via AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION
# For this example, we'll just create a client.
# In a real application, ensure credentials are set up (e.g., via environment variables or ~/.aws/credentials)

def get_pipes_client() -> 'PipesClient':
    # The explicit type annotation here (PipesClient) enables type checking and autocompletion
    client: PipesClient = boto3.client(
        "pipes",
        aws_access_key_id=os.environ.get('AWS_ACCESS_KEY_ID', 'DUMMY_KEY'),
        aws_secret_access_key=os.environ.get('AWS_SECRET_ACCESS_KEY', 'DUMMY_SECRET'),
        region_name=os.environ.get('AWS_REGION', 'us-east-1')
    )
    return client

def list_eventbridge_pipes():
    pipes_client = get_pipes_client()
    try:
        response: ListPipesResponseTypeDef = pipes_client.list_pipes(
            MaxResults=5
        )
        print("Successfully listed pipes:")
        for pipe in response.get('Pipes', []):
            print(f"  Pipe Name: {pipe.get('Name')}, State: {pipe.get('State')}")
    except Exception as e:
        print(f"Error listing pipes: {e}")

if __name__ == "__main__":
    list_eventbridge_pipes()