Type Annotations for boto3 AWS ManagedGrafana

Warnings

• breaking Starting with `mypy-boto3-builder` version 8.12.0, support for Python 3.8 was removed. Projects using older Python versions must pin to an older `mypy-boto3-grafana` version generated by a builder prior to 8.12.0 or upgrade their Python version.
  Fix: Upgrade to Python 3.9+ or pin `mypy-boto3-grafana` to a version compatible with Python 3.8 (e.g., versions generated by `mypy-boto3-builder < 8.12.0`).
• breaking Version 8.9.0 of `mypy-boto3-builder` introduced breaking changes in TypeDef naming conventions, potentially causing import errors or type mismatches if you were explicitly referencing generated TypedDicts with the old naming scheme.
  Fix: Review your code for explicit TypeDef imports and update names according to the new conventions (e.g., `CreateDistributionRequestRequestTypeDef` -> `CreateDistributionRequestTypeDef`, `CreateDistributionExtraRequestTypeDef` -> `CreateDistributionRequestExtraTypeDef`).
• gotcha While some IDEs (like PyCharm) and `mypy` can infer types for `boto3.client` calls, explicit type annotations (e.g., `client: ManagedGrafanaClient = boto3.client("grafana")`) are often recommended for optimal autocompletion and comprehensive type checking, especially when using VSCode or the `boto3-stubs-lite` packages.
  Fix: Add explicit type annotations for boto3 client, resource, waiter, and paginator objects, as shown in the quickstart example.
• gotcha Pylint may complain about undefined variables when using `typing.TYPE_CHECKING` guards. This is a known issue with Pylint's static analysis when types are only defined conditionally.
  Fix: As a workaround, you can assign `object` to the type-hinted variables outside the `TYPE_CHECKING` block: `if TYPE_CHECKING: from mypy_boto3_grafana.client import ManagedGrafanaClient else: ManagedGrafanaClient = object`.
• gotcha PyCharm users might experience slow performance or high CPU usage due to how it handles `Literal` overloads. This can be particularly noticeable with comprehensive stub packages like `mypy-boto3-grafana`.
  Fix: It is recommended to use `boto3-stubs-lite` (e.g., `mypy-boto3-grafana-lite` if available, or `boto3-stubs-lite[grafana]`) or disable PyCharm's internal type checker and rely solely on `mypy` or `pyright` instead.

Install

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

Imports

• ManagedGrafanaClient

  from mypy_boto3_grafana.client import ManagedGrafanaClient

  Import the client type directly for explicit type hinting.
• ListWorkspacesResponseTypeDef

  from mypy_boto3_grafana.type_defs import ListWorkspacesResponseTypeDef

  Import specific TypedDicts for response or request structures.

Quickstart

This quickstart demonstrates how to use the `mypy-boto3-grafana` type annotations with a boto3 client. It explicitly types the client and a response object, allowing `mypy` to catch potential type mismatches.

import boto3
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from mypy_boto3_grafana.client import ManagedGrafanaClient
    from mypy_boto3_grafana.type_defs import ListWorkspacesResponseTypeDef

def get_grafana_workspaces():
    # In a real application, consider using environment variables or other secure methods for credentials
    client: ManagedGrafanaClient = boto3.client("grafana")

    # Example: List AWS Grafana workspaces
    response: ListWorkspacesResponseTypeDef = client.list_workspaces()
    for workspace in response.get("workspaces", []):
        print(f"Workspace Name: {workspace.get('workspaceName')}, Status: {workspace.get('workspaceStatus')}")

if __name__ == "__main__":
    get_grafana_workspaces()

# To type-check this file: mypy your_script_name.py