mypy-boto3-dataexchange

Warnings

• breaking Support for Python 3.8 has been removed in `mypy-boto3-builder` version 8.12.0. Projects using `mypy-boto3-dataexchange` (and other `mypy-boto3` packages) must use Python 3.9 or newer.
  Fix: Upgrade your Python environment to 3.9 or a later version.
• breaking Version 8.9.0 of `mypy-boto3-builder` introduced breaking changes in TypeDef naming conventions. Specifically, TypeDefs for packed method arguments use shorter names (e.g., `CreateDistributionRequestRequestTypeDef` -> `CreateDistributionRequestTypeDef`), and conflicting `Extra` postfixes were moved (e.g., `CreateDistributionExtraRequestTypeDef` -> `CreateDistributionRequestExtraTypeDef`). This impacts explicit type annotations.
  Fix: Review and update explicit TypeDef imports and usages in your codebase according to the new naming conventions. Refer to the specific service documentation for updated TypeDef names.
• gotcha PyCharm users might experience slow performance or high CPU usage due to literal overloads. It is recommended to use `boto3-stubs-lite` packages or disable PyCharm's internal type checker and rely on `mypy` or `pyright` instead.
  Fix: Consider installing the `*-lite` version of the stubs (e.g., `boto3-stubs-lite[dataexchange]`) or configure your IDE to use external type checkers like `mypy` or `pyright`.
• gotcha When using `TYPE_CHECKING` for conditional imports with `pylint`, it may complain about undefined variables in the runtime block. To avoid this, set types to `object` in the `else` branch of the `TYPE_CHECKING` block.
  Fix: Implement a pattern like `if TYPE_CHECKING: from mypy_boto3_dataexchange.client import DataExchangeClient else: DataExchangeClient = object`.

Install

• pip install mypy-boto3-dataexchange boto3 Install with boto3

Imports

• DataExchangeClient

  from mypy_boto3_dataexchange.client import DataExchangeClient

  This imports the typed client for DataExchange, enabling type-checking and auto-completion for boto3.client('dataexchange').

Quickstart

This quickstart demonstrates how to obtain a type-hinted DataExchange client using `mypy-boto3-dataexchange` and perform a basic operation like listing data sets. The `TYPE_CHECKING` block ensures that the type stub is only imported during type-checking, avoiding runtime dependencies. Remember to configure your AWS credentials.

import boto3
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from mypy_boto3_dataexchange.client import DataExchangeClient

# Ensure AWS credentials are set up (e.g., via environment variables, ~/.aws/credentials)
# For example, export AWS_ACCESS_KEY_ID='YOUR_ACCESS_KEY_ID'
# export AWS_SECRET_ACCESS_KEY='YOUR_SECRET_ACCESS_KEY'
# export AWS_DEFAULT_REGION='us-east-1'

def get_dataexchange_client() -> DataExchangeClient:
    """Returns a type-hinted DataExchange client."""
    client: DataExchangeClient = boto3.client("dataexchange")
    return client

if __name__ == "__main__":
    dataexchange_client = get_dataexchange_client()
    print(f"Client type: {type(dataexchange_client)}")
    try:
        # Example: List your Data Exchange data sets
        response = dataexchange_client.list_data_sets()
        print(f"Successfully listed {len(response.get('DataSets', []))} data sets.")
        # Accessing typed attributes will be auto-completed and type-checked
        for dataset in response.get('DataSets', []):
            print(f"  - DataSetId: {dataset.get('DataSetId')}, Name: {dataset.get('Name')}")
    except Exception as e:
        print(f"Error listing data sets: {e}")