mypy-boto3-databrew Type Stubs

Warnings

• breaking Support for Python 3.8 has been removed in `mypy-boto3-builder` version 8.12.0 and subsequently in generated packages. Ensure your project uses Python 3.9 or newer.
  Fix: Upgrade your Python environment to 3.9 or a later version.
• breaking TypeDef names for packed method arguments were shortened (e.g., `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`). Conflicting `Extra` postfixes were moved to the end (`CreateDistributionExtraRequestTypeDef` to `CreateDistributionRequestExtraTypeDef`). This may require updates to explicit `TypedDict` imports in your code.
  Fix: Review and update explicit `TypedDict` imports and usage to reflect the new naming conventions.
• gotcha For optimal performance and correct type resolution in PyCharm, especially with Literal overloads, it is recommended to use `boto3-stubs-lite` instead of the full stubs. Alternatively, disable PyCharm's internal type checker and rely on external tools like `mypy` or `pyright`.
  Fix: Consider `pip install 'boto3-stubs-lite[databrew]'` or configure your IDE to use an external type checker.
• gotcha While `mypy-boto3-databrew` provides type information, `boto3` and `mypy` (or another type checker) must be installed separately for the stubs to be effective. The stubs do not include the runtime library itself.
  Fix: Ensure `boto3` and `mypy` are included in your project's dependencies (`pip install boto3 mypy`).
• gotcha Explicit type annotations for `boto3.client()` calls are often recommended or necessary for the best type-checking and auto-completion experience, especially with IDEs like VSCode and PyCharm, as automatic type discovery may not always be fully reliable or performant.
  Fix: Always explicitly annotate your client creation, e.g., `client: GlueDataBrewClient = boto3.client('databrew')`.

Install

• pip install mypy-boto3-databrew boto3 mypy Install standalone stubs with boto3 and mypy
• pip install 'boto3-stubs[databrew]' boto3 mypy Install as part of boto3-stubs collection

Imports

• GlueDataBrewClient

  from mypy_boto3_databrew.client import GlueDataBrewClient

  Import the specific client type for GlueDataBrew.
• BatchPutDataBrewJobResponseTypeDef

  from mypy_boto3_databrew.type_defs import BatchPutDataBrewJobResponseTypeDef

  Import specific TypedDicts for request/response bodies.

Quickstart

This quickstart demonstrates how to use `mypy-boto3-databrew` to add type hints to your boto3 GlueDataBrew client. It explicitly imports the `GlueDataBrewClient` type and a sample response `TypedDict` for improved type checking and auto-completion. The example initializes a DataBrew client and lists recipes, showcasing how type annotations benefit method calls and return values.

import boto3
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from mypy_boto3_databrew.client import GlueDataBrewClient
    from mypy_boto3_databrew.type_defs import ListRecipesResponseTypeDef

def get_databrew_recipes() -> ListRecipesResponseTypeDef:
    # Initialize the DataBrew client with type annotation
    client: GlueDataBrewClient = boto3.client("databrew")
    
    # Use the client with type-hinted methods and expected return types
    response: ListRecipesResponseTypeDef = client.list_recipes(MaxResults=5)
    print(f"Found {len(response['Recipes'])} DataBrew recipes.")
    for recipe in response.get('Recipes', []):
        print(f"- {recipe['Name']} (ARN: {recipe['Arn']})")
    return response

if __name__ == "__main__":
    # Ensure AWS credentials are configured (e.g., via AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION)
    # For a runnable example without actual AWS calls, you might mock boto3 or use a dummy client.
    # This example assumes valid AWS credentials are set up.
    print("Listing DataBrew recipes...")
    try:
        get_databrew_recipes()
    except Exception as e:
        print(f"Error fetching DataBrew recipes: {e}")
        print("Please ensure AWS credentials and region are configured correctly.")