types-aiobotocore-textract

import asyncio from aiobotocore.session import get_session from types_aiobotocore_textract.client import TextractClient async def analyze_document_typed(s3_bucket: str, s3_key: str): session = get_session() async with session.create_client("textract") as client: # type: TextractClient print(f"Client type: {type(client)}") try: response = await client.analyze_document( Document={ 'S3Object': { 'Bucket': s3_bucket, 'Name': s3_key } }, FeatureTypes=['FORMS', 'TABLES'] ) print("Document analysis successful.") # Example of accessing a typed response document_metadata = response.get('DocumentMetadata') if document_metadata: print(f"Pages: {document_metadata.get('Pages')}") except client.ValidationException as e: print(f"Validation error: {e}") except Exception as e: print(f"An unexpected error occurred: {e}") if __name__ == "__main__": # Replace with your S3 bucket and key for a document (e.g., PDF, PNG, JPG) # This example requires an actual S3 object for Textract to process. # For local testing without a real S3 object, Textract might raise an InvalidS3ObjectException or similar. dummy_s3_bucket = "your-s3-bucket" dummy_s3_key = "path/to/your/document.pdf" # You can use a dummy value if you only want to test type checking without actual execution # or ensure a real, accessible S3 object is configured for Textract. asyncio.run(analyze_document_typed(dummy_s3_bucket, dummy_s3_key))