mypy-boto3-marketplace-deployment Type Stubs

1.42.3 · active · verified Sat Apr 11

mypy-boto3-marketplace-deployment provides machine-generated type annotations (type stubs) for the `boto3` AWS SDK's MarketplaceDeploymentService. These stubs enhance static analysis, autocompletion, and error checking in IDEs and type checkers like MyPy, ensuring more robust and maintainable AWS automation scripts. The library is currently at version 1.42.3, mirroring the `boto3` version it types, and is actively maintained with updates generated by `mypy-boto3-builder`.

Warnings

breaking As of `mypy-boto3-builder` version 8.12.0, Python 3.8 support has been removed. All `mypy-boto3` packages, including this one, now require Python >=3.9.
Fix: Upgrade your Python environment to 3.9 or newer.
breaking The `mypy-boto3-builder` (version 8.9.0) introduced changes to how TypeDef names are generated, potentially shortening them (e.g., `CreateDistributionRequestRequestTypeDef` to `CreateDistributionRequestTypeDef`) or adjusting postfixes for conflicting names. While specific to the builder, this impacts all generated service stubs if such naming conflicts existed.
Fix: Review your code for any explicit imports of `TypeDef` names and adjust according to the new naming conventions if they were affected.
gotcha This package provides type stubs *only* for the `MarketplaceDeploymentService`. For comprehensive `boto3` type annotations covering all services, you should install the `boto3-stubs` metapackage (e.g., `pip install boto3-stubs[full]`) or specific service stubs for each service you use (e.g., `pip install boto3-stubs[s3,ec2]`). Installing only this package will not provide types for other boto3 services.
Fix: Install `boto3-stubs` with the appropriate extras (`[full]`, `[all]`, or specific service names) to get type annotations for other AWS services.
gotcha It is highly recommended to wrap `mypy-boto3` type imports within `if TYPE_CHECKING:` blocks. This prevents the stub packages from becoming runtime dependencies, keeping your production environment lighter and cleaner. Tools like Pylint might complain about undefined variables without this pattern or by assigning `object` in the `else` branch.
Fix: Encapsulate type imports: `from typing import TYPE_CHECKING\nif TYPE_CHECKING:\n from mypy_boto3_marketplace_deployment import MarketplaceDeploymentServiceClient`

Install

pip install mypy-boto3-marketplace-deployment Install specific service stubs
pip install boto3-stubs[marketplace-deployment] Install via boto3-stubs metapackage

Imports

MarketplaceDeploymentServiceClient
```
from mypy_boto3_marketplace_deployment import MarketplaceDeploymentServiceClient
```
Primary client type for Marketplace Deployment Service.
DeploymentParameterInputTypeDef
```
from mypy_boto3_marketplace_deployment.type_defs import DeploymentParameterInputTypeDef
```
Example of importing a type definition for request/response payloads.

MarketplaceDeploymentServiceServiceName

from mypy_boto3_marketplace_deployment.literals import MarketplaceDeploymentServiceServiceName

Importing a literal type for service name.

Quickstart

This quickstart demonstrates how to import and use the type-hinted `MarketplaceDeploymentServiceClient` with `boto3`. It includes the recommended `if TYPE_CHECKING` block to ensure type imports are only active during static analysis, avoiding runtime dependencies on the stub package.

import boto3
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from mypy_boto3_marketplace_deployment import MarketplaceDeploymentServiceClient
    from mypy_boto3_marketplace_deployment.type_defs import DeploymentParameterInputTypeDef


def get_marketplace_deployment_client() -> 'MarketplaceDeploymentServiceClient':
    """Returns a type-hinted MarketplaceDeploymentService client."""
    # boto3.client is dynamically typed, mypy-boto3 provides the static types
    return boto3.client("marketplace-deployment") # type: ignore[return-value]

def process_deployment_parameters(client: 'MarketplaceDeploymentServiceClient') -> None:
    """Example of using the client with typed input."""
    # Example of a typed dictionary for input (replace with actual data)
    deployment_param: DeploymentParameterInputTypeDef = {
        "name": "ExampleParam",
        "value": "ExampleValue"
    }
    # In a real scenario, you'd call a client method here, e.g., client.SomeOperation(**deployment_param)
    print(f"Processing deployment parameter: {deployment_param['name']}")

if __name__ == "__main__":
    client = get_marketplace_deployment_client()
    process_deployment_parameters(client)

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