mypy-boto3-snowball

1.42.3 · active · verified Sat Apr 11

Type annotations for boto3 Snowball 1.42.3 service generated with mypy-boto3-builder 8.12.0. This library provides static type checking for `boto3` clients and resources, enhancing development with autocompletion and early error detection for AWS Snowball operations. It follows `boto3`'s release cadence, with frequent updates to align with new AWS service versions.

Warnings

breaking Python 3.8 support has been removed since mypy-boto3-builder version 8.12.0. Ensure your project uses Python 3.9 or newer to utilize the latest `mypy-boto3-snowball` versions.
Fix: Upgrade your Python environment to 3.9 or higher. If unable to upgrade Python, use an older `mypy-boto3-snowball` version compatible with Python 3.8.
breaking mypy-boto3-builder version 8.9.0 introduced breaking changes in TypeDef naming conventions, potentially affecting existing type-hinted code. For example, `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`.
Fix: Review and update `TypedDict` imports and usage in your codebase to match the new naming conventions as defined in the latest stub package documentation.
gotcha Legacy `mypy-boto3` (the monolithic package) has been moved to a separate product by the builder in version 8.9.0. Users should explicitly install service-specific packages (e.g., `mypy-boto3-snowball`) or `boto3-stubs` with extras.
Fix: Always install the specific `mypy-boto3-SERVICE_NAME` package for the service you need or use `boto3-stubs[SERVICE_NAME]` to ensure you're getting the latest and correctly generated stubs.
gotcha PyCharm may experience slow performance or high CPU usage due to `Literal` overloads in `mypy-boto3` stubs. This is a known issue (PY-40997).
Fix: Consider using `boto3-stubs-lite[snowball]` which offers a more RAM-friendly experience without `session.client`/`resource` overloads (requiring explicit type annotations). Alternatively, disable PyCharm's internal type checker and rely on external tools like `mypy` or `pyright`.
gotcha While `mypy-boto3` often provides implicit type discovery, explicit type annotations for clients, paginators, and waiters can improve clarity and sometimes be necessary, especially when using `lite` versions of the stubs.
Fix: It's good practice to explicitly type-hint your `boto3` client (e.g., `client: SnowballClient = boto3.client("snowball")`) for maximum type-checking benefit and IDE assistance.

Install

pip install mypy-boto3-snowball Standalone package
pip install 'boto3-stubs[snowball]' As part of boto3-stubs

Imports

SnowballClient
```
from mypy_boto3_snowball.client import SnowballClient
```
Type hint for the boto3 Snowball client.
AddressTypeDef
```
from mypy_boto3_snowball.type_defs import AddressTypeDef
```
Type definition for Snowball service data structures.
AddressTypeType
```
from mypy_boto3_snowball.literals import AddressTypeType
```
Literal types for string-based enumerations in Snowball operations.
Session
```
from boto3.session import Session
```
Required for creating a boto3 session and client.

Quickstart

This quickstart demonstrates how to initialize a `boto3` Snowball client and use it with `mypy-boto3-snowball` type annotations. The `TYPE_CHECKING` guard ensures the stub package is only used during static analysis, preventing a runtime dependency. The example lists up to 10 Snowball jobs.

import boto3
from typing import TYPE_CHECKING
from mypy_boto3_snowball.client import SnowballClient

def get_snowball_jobs():
    # Use TYPE_CHECKING guard to avoid runtime dependency on mypy-boto3-snowball
    if TYPE_CHECKING:
        client: SnowballClient = boto3.client("snowball")
    else:
        client = boto3.client("snowball")

    try:
        response = client.list_jobs(
            MaxResults=10,
            # NextToken='string' # Uncomment if you have a next token
        )
        print(f"Snowball Jobs: {response.get('JobListEntries')}")
        return response.get('JobListEntries', [])
    except client.exceptions.InvalidResourceException as e:
        print(f"Error: {e}")
        return []

if __name__ == "__main__":
    # Ensure AWS credentials are configured (e.g., via ~/.aws/credentials or environment variables)
    # For local testing, you might need a mock boto3 or actual AWS setup.
    print("Attempting to list Snowball jobs...")
    jobs = get_snowball_jobs()

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