mypy-boto3-rds-data Type Annotations

Warnings

• breaking Support for Python 3.8 has been removed. All `mypy-boto3-*` packages generated with `mypy-boto3-builder` version 8.12.0 or newer (including `mypy-boto3-rds-data 1.42.3`) require Python 3.9 or higher.
  Fix: Upgrade your Python environment to 3.9 or newer.
• breaking Type definition (TypeDef) names for packed method arguments have been shortened (e.g., `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`). Conflicting `Extra` postfixes were also moved to the end (e.g., `CreateDistributionExtraRequestTypeDef` to `CreateDistributionRequestExtraTypeDef`). While not specific to `rds-data`, this is a general breaking change from the underlying builder that might affect type hints for other services if specific TypeDefs are used directly.
  Fix: Review your code for direct usage of specific TypeDef names and update them according to the new naming conventions, or rely on IDE autocompletion for the correct names.
• gotcha PyCharm users may experience slow performance or high CPU usage due to `Literal` overloads. It is recommended to use `boto3-stubs-lite` (if available for your service) or disable PyCharm's internal type checker and use `mypy` or `pyright` externally.
  Fix: Consider `pip install boto3-stubs-lite[rds-data]` if `lite` version exists and meets needs, or configure PyCharm to use an external type checker.
• gotcha For optimal autocompletion and type checking in IDEs like VSCode and PyCharm, explicit type annotations for `boto3.client` and `boto3.session.client` calls are highly recommended, as function overload support is not always fully robust.
  Fix: Always add explicit type hints like `client: RDSDataServiceClient = boto3.client("rds-data")`.
• gotcha When using the `TYPE_CHECKING` flag to prevent production dependencies, Pylint might report 'undefined variable' errors. To fix this, set all types to `object` in the non-`TYPE_CHECKING` branch.
  Fix: Implement a pattern like `if TYPE_CHECKING: from mypy_boto3_rds_data.client import RDSDataServiceClient else: RDSDataServiceClient = object`.

Install

• pip install mypy-boto3-rds-data boto3 mypy Install library, boto3, and mypy

Imports

• RDSDataServiceClient

  from mypy_boto3_rds_data.client import RDSDataServiceClient

• ArrayValueOutputTypeDef

  from mypy_boto3_rds_data.type_defs import ArrayValueOutputTypeDef

  Type definitions for method input/output parameters.
• DecimalReturnTypeType

  from mypy_boto3_rds_data.literals import DecimalReturnTypeType

  Literals for specific enumerated types.

Quickstart

This quickstart demonstrates how to obtain a type-hinted RDS Data Service client and use it to execute an SQL statement. The `TYPE_CHECKING` block ensures type hints are only active during static analysis, avoiding runtime dependency on mypy-boto3-rds-data for production code.

import boto3
from typing import TYPE_CHECKING
from mypy_boto3_rds_data.client import RDSDataServiceClient


# Ensure boto3 is installed: pip install boto3 mypy-boto3-rds-data

def get_rds_data_client() -> RDSDataServiceClient:
    if TYPE_CHECKING:
        client: RDSDataServiceClient = boto3.client("rds-data")
    else:
        client = boto3.client("rds-data")
    return client


def execute_statement(sql: str, database: str, resource_arn: str, secret_arn: str) -> None:
    client = get_rds_data_client()
    
    # Example: Execute SQL statement
    response = client.execute_statement(
        sql=sql,
        database=database,
        resourceArn=resource_arn,
        secretArn=secret_arn,
        includeResultMetadata=True
    )
    print("Statement executed.")
    print(response)

# To run this, replace placeholders with actual AWS details:
# sql_query = "SELECT 1"
# db_name = "your_database_name"
# rds_resource_arn = "arn:aws:rds:region:account-id:cluster:cluster-name"
# rds_secret_arn = "arn:aws:secretsmanager:region:account-id:secret:secret-name"
# execute_statement(sql_query, db_name, rds_resource_arn, rds_secret_arn)