mypy-boto3-amplify Type Stubs for AWS Amplify

1.42.3 · active · verified Sat Apr 11

mypy-boto3-amplify provides static type annotations for the AWS SDK for Python (boto3) specifically for the Amplify service. It helps improve code quality, enables better IDE autocompletion, and catches potential type-related errors before runtime. Currently at version 1.42.3, its releases are closely tied to boto3 updates, ensuring up-to-date type information generated by the mypy-boto3-builder.

Warnings

breaking Python 3.8 support has been removed across all `mypy-boto3-*` packages. Projects using these stubs must target Python 3.9 or higher.
Fix: Upgrade your project's Python interpreter to 3.9 or newer.
breaking TypeDef naming conventions have changed. For packed method arguments, `RequestRequestTypeDef` is shortened to `RequestTypeDef`. Conflicting `Extra` postfixes are moved to the end (e.g., `CreateDistributionExtraRequestTypeDef` to `CreateDistributionRequestExtraTypeDef`).
Fix: Update your type annotations to reflect the new, shorter or reordered TypeDef names. Refer to the specific service's documentation for exact TypeDef names.
deprecated The `sms-voice` service stubs have been removed as the service is no longer supported by AWS. Use `pinpoint-sms-voice` instead.
Fix: Migrate your code to use the `pinpoint-sms-voice` service and install `mypy-boto3-pinpoint-sms-voice` stubs if needed.
gotcha These packages are PEP 561-compliant stub-only packages. They provide type information for `boto3` but do not contain any runtime code themselves. `mypy` and other type checkers automatically discover them if installed.
Fix: Ensure `mypy-boto3-amplify` is installed in the same environment as your project during development. No runtime changes are needed.
gotcha When using `TYPE_CHECKING` guards for conditional imports, `pylint` may complain about undefined variables. To resolve this, conditionally set the imported types to `object` in the non-`TYPE_CHECKING` branch.
Fix: Implement conditional type assignment: `if TYPE_CHECKING: from mypy_boto3_amplify.client import AmplifyClient else: AmplifyClient = object`
gotcha While type checkers can often infer types, explicit type annotations for `boto3.client()`, `session.client()`, `client.get_waiter()`, and `client.get_paginator()` calls are highly recommended for optimal IDE autocompletion and type validation.
Fix: Explicitly add type hints such as `amplify_client: AmplifyClient = boto3.client('amplify')` to improve developer experience.

Install

pip install mypy-boto3-amplify Install service stubs
pip install 'boto3-stubs[amplify]' Install via boto3-stubs (recommended)

Imports

AmplifyClient
```
from mypy_boto3_amplify.client import AmplifyClient
```
Type hint for the boto3 Amplify client.
AmplifyServiceName
```
from mypy_boto3_amplify.literals import AmplifyServiceName
```
Literal type for the 'amplify' service name.
ListAppsOutputTypeDef
```
from mypy_boto3_amplify.type_defs import ListAppsOutputTypeDef
```
Type definition for the output of ListApps API call.
TYPE_CHECKING
```
from typing import TYPE_CHECKING
```
Used for conditional imports to avoid runtime dependency on type stubs.

Quickstart

This example demonstrates how to obtain a type-hinted Amplify client using `boto3` and leverage the `mypy-boto3-amplify` stubs for static analysis. It includes a `TYPE_CHECKING` guard for conditional imports, ensuring the stubs are only used during type checking and not as a runtime dependency. The `get_amplify_apps` function is fully type-hinted, including the client and the return value based on `ListAppsOutputTypeDef`.

import boto3
from typing import TYPE_CHECKING, List
import os

if TYPE_CHECKING:
    from mypy_boto3_amplify.client import AmplifyClient
    from mypy_boto3_amplify.type_defs import AppOutputTypeDef, ListAppsOutputTypeDef

def get_amplify_apps(client: 'AmplifyClient') -> List['AppOutputTypeDef']:
    """Lists Amplify applications with type hints."""
    response: 'ListAppsOutputTypeDef' = client.list_apps()
    return response.get('apps', [])

# Example usage
# Ensure AWS credentials are set up (e.g., via environment variables or ~/.aws/credentials)
# For a runnable example, we'll mock client creation

if os.environ.get('AWS_ACCESS_KEY_ID'): # Check if credentials exist for a real client
    amplify_client: 'AmplifyClient' = boto3.client('amplify')
    apps = get_amplify_apps(amplify_client)
    print(f"Found {len(apps)} Amplify applications.")
    for app in apps:
        print(f"  - App ID: {app['appId']}, Name: {app['name']}")
else:
    print("AWS credentials not found. Skipping live client example. Define AWS_ACCESS_KEY_ID to run.")

# Without type checking (runtime code)
amplify_client_untyped = boto3.client('amplify')
# This client would also work, but without static type validation.

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