mypy-boto3-schemas

1.42.3 · active · verified Fri Apr 10

mypy-boto3-schemas provides type annotations for the AWS Schemas service within the boto3 library, enhancing static type checking for Python applications. It is part of the `mypy-boto3` family of projects, generated by `mypy-boto3-builder`. The current version is 1.42.3 and new versions are released frequently to keep pace with boto3 updates and new AWS service features.

Warnings

breaking Starting with `mypy-boto3-builder` version 8.12.0 (which generates this package), support for Python 3.8 has been removed. Projects using `mypy-boto3-schemas` must use Python 3.9 or newer.
Fix: Upgrade your project's Python interpreter to 3.9 or newer.
breaking In `mypy-boto3-builder` version 8.9.0, there were breaking changes to TypeDef naming conventions. Conflicting TypeDef names had `Extra` moved to the end (e.g., `CreateDistributionExtraRequestTypeDef` -> `CreateDistributionRequestExtraTypeDef`), and packed method arguments use shorter names (`CreateDistributionRequestRequestTypeDef` -> `CreateDistributionRequestTypeDef`).
Fix: Review and update TypeDef names in your codebase according to the new conventions. Refer to the specific service documentation for exact changes.
deprecated The `sms-voice` service was removed in `mypy-boto3-builder` version 8.11.0. If your project uses type hints for `sms-voice`, you should migrate to `pinpoint-sms-voice`.
Fix: Replace imports and usage of `mypy_boto3_sms_voice` with `mypy_boto3_pinpoint_sms_voice` and update your `boto3` client calls accordingly.
gotcha This package (`mypy-boto3-schemas`) is a stub-only library for static type checking. It does not contain any runtime code. You must have `boto3` (or `aioboto3` for async variants) installed in your environment for your application to run.
Fix: Ensure `boto3` is installed via `pip install boto3`. It is recommended to install `mypy` as well if you intend to perform static type checks.
gotcha When using `mypy-boto3` stubs with `pylint`, `pylint` might complain about undefined variables if types are used directly without a `TYPE_CHECKING` guard. This is because `pylint` may not fully understand the stub-only nature of the imports.
Fix: Wrap stub-only imports within a `if TYPE_CHECKING:` block and set runtime types to `object` outside of it to prevent `pylint` errors. This ensures type hints are only active during static analysis.

Install

pip install mypy-boto3-schemas Install core package

Imports

SchemaSummaryTypeDef
```
from mypy_boto3_schemas.type_defs import SchemaSummaryTypeDef
```
Type definitions (TypeDefs) are found within the `type_defs` submodule of the service-specific `mypy-boto3` package, not directly from `boto3`.
SchemasClient
```
from mypy_boto3_schemas.client import SchemasClient
```
Client type annotations are found within the `client` submodule of the service-specific `mypy-boto3` package.

Quickstart

Demonstrates how to import and use a TypeDef for the AWS Schemas service. It includes a `TYPE_CHECKING` block to guard against runtime dependencies on the stub package for production environments, which is a common pattern for `mypy-boto3` users. It shows how to define a schema input using the `CreateSchemaInputRequestTypeDef`.

from typing import TYPE_CHECKING
from mypy_boto3_schemas.type_defs import CreateSchemaInputRequestTypeDef

if TYPE_CHECKING:
    import boto3
    from mypy_boto3_schemas.client import SchemasClient

def create_example_schema(client: "SchemasClient") -> None:
    # Example of a TypeDef for schema creation input
    schema_input: CreateSchemaInputRequestTypeDef = {
        "RegistryName": "my-registry",
        "SchemaName": "my-schema",
        "Content": "{\"type\": \"object\", \"properties\": {\"foo\": {\"type\": \"string\"}}}",
        "Type": "OpenApi3", # Or 'JSONSchema', 'WSDL', 'XSD'
    }
    
    print(f"Attempting to create schema: {schema_input['SchemaName']}")
    # In a real application, you would call a boto3 client method here, e.g.:
    # client.create_schema(**schema_input)

# Example usage (requires boto3 to be installed and configured)
if __name__ == "__main__":
    # This part would typically interact with a real boto3 client
    # For demonstration, we'll use a mock if boto3 is not present
    try:
        import boto3
        schemas_client: "SchemasClient" = boto3.client("schemas")
        create_example_schema(schemas_client)
    except ImportError:
        print("boto3 not installed. Skipping live client example, but type hints are still valid.")

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