mypy-boto3-cognito-sync Type Stubs for boto3 CognitoSync

Warnings

• breaking Python 3.8 support was removed for all `mypy-boto3` packages (including this one) in `mypy-boto3-builder` version 8.12.0. Projects must use Python 3.9 or newer.
  Fix: Upgrade your Python environment to 3.9 or higher.
• breaking All `mypy-boto3` packages migrated to PEP 561, changing how type checkers discover packages. Ensure your `mypy` configuration (if any) is compatible with standard PEP 561 stub discovery.
  Fix: No direct code change required, but verify your `mypy` setup recognizes the stubs correctly. Most modern tooling handles PEP 561 automatically.
• breaking TypedDict argument names for packed methods were shortened (e.g., `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`), and conflicting `Extra` postfixes were reordered in `mypy-boto3-builder 8.9.0`. This can break explicit `TypeDef` imports or usage if not updated.
  Fix: Review and update `TypeDef` imports and usage patterns in your code to match the new, shorter names where applicable.
• gotcha This package provides only type stubs for `boto3-stubs`. You must install the actual `boto3` library separately for your application to run. `mypy-boto3-cognito-sync` is a development dependency, not a runtime dependency.
  Fix: Ensure `pip install boto3` is part of your project's runtime dependencies.
• gotcha When installing `boto3-stubs` with service-specific extras (e.g., `boto3-stubs[cognito-sync]`), the version of the individual `mypy-boto3-*` sub-package might not be strictly locked to the specified `boto3-stubs` version. This can lead to unexpected type-checking errors if the installed sub-package is significantly newer than anticipated.
  Fix: To strictly pin the version, install the specific `mypy-boto3-cognito-sync` package directly with `pip install mypy-boto3-cognito-sync==X.Y.Z` in addition to or instead of the `boto3-stubs` extra.
• gotcha Using `Literal` type overloads can cause slow performance and high CPU usage in PyCharm (issue PY-40997). For PyCharm users, `boto3-stubs-lite` is recommended as an alternative for better IDE responsiveness.
  Fix: Consider installing `boto3-stubs-lite[cognito-sync]` instead, or disable PyCharm's internal type checker and use an external tool like `mypy` or `pyright`.
• gotcha When using `Pylint` with `TYPE_CHECKING` blocks for conditional stub imports, `Pylint` may complain about undefined variables. This requires setting the conditionally imported types to `object` in the non-`TYPE_CHECKING` branch.
  Fix: Implement conditional type assignment, e.g., `if TYPE_CHECKING: from mypy_boto3_cognito_sync import CognitoSyncClient else: CognitoSyncClient = object`.

Install

• pip install mypy-boto3-cognito-sync Install standalone package
• pip install 'boto3-stubs[cognito-sync]' Install as boto3-stubs extra

Imports

• CognitoSyncClient

  from mypy_boto3_cognito_sync import CognitoSyncClient

  Used for explicit type annotation of the boto3 Cognito Sync client.
• BulkPublishStatusType

  from mypy_boto3_cognito_sync.literals import BulkPublishStatusType

  Example of importing a Literal type for stricter type checking of allowed string values.
• BulkPublishRequestTypeDef

  from mypy_boto3_cognito_sync.type_defs import BulkPublishRequestTypeDef

  Example of importing a TypedDict for type-checking input/output shapes.

Quickstart

This quickstart demonstrates how to use the `CognitoSyncClient` type annotation with a boto3 Cognito Sync client. The `TYPE_CHECKING` guard is a best practice to avoid importing the stubs at runtime, making them purely a development dependency. The example shows a typical `list_datasets` operation, which benefits from type hints on client methods and response structures.

from typing import TYPE_CHECKING
import boto3

if TYPE_CHECKING:
    from mypy_boto3_cognito_sync import CognitoSyncClient
    from mypy_boto3_cognito_sync.type_defs import DatasetTypeDef

# Initialize a boto3 session and client
session = boto3.session.Session()
client: "CognitoSyncClient" = session.client("cognito-sync")

# Example: List Identity Pools (Cognito Sync operations often tie to Identity Pools)
# Note: Cognito Sync operations are typically tied to specific identities or datasets.
# This example is illustrative for client type-checking.
try:
    # Placeholder for actual Cognito Sync operation, as ListIdentityPools is CognitoIdentity
    # A more realistic CognitoSync operation would be something like list_records
    # For this example, we'll simulate a call that uses the client.
    # In a real scenario, you'd provide IdentityPoolId, IdentityId, DatasetName, etc.
    # For demonstration, we'll use a dummy call that the client can execute.
    # (Note: CognitoSync doesn't have a simple 'list all' like many services)
    
    # A common operation is to list datasets for an identity.
    identity_pool_id = os.environ.get('COGNITO_IDENTITY_POOL_ID', 'us-east-1:xxxx-xxxx-xxxx') # Dummy ID
    identity_id = os.environ.get('COGNITO_IDENTITY_ID', 'us-east-1:xxxx-xxxx-xxxx') # Dummy ID
    
    response = client.list_datasets(
        IdentityPoolId=identity_pool_id,
        IdentityId=identity_id
    )
    
    print("Datasets:")
    for dataset in response.get("Datasets", []):
        # dataset is type-checked as DatasetTypeDef
        dataset_typed: "DatasetTypeDef" = dataset
        print(f"  Dataset Name: {dataset_typed['DatasetName']}, Num Records: {dataset_typed['NumRecords']}")

except client.exceptions.ResourceNotFoundException:
    print(f"Identity Pool or Identity not found for ID: {identity_pool_id}, {identity_id}")
except Exception as e:
    print(f"An error occurred: {e}")