Getting Started

Installation

pip install capo-dax

Usage

from capo_dax import AsyncDAXClient


async def main():
    async with AsyncDAXClient() as dax:
        # Example: call the create_cluster operation
        response = await dax.create_cluster()
        print(response["cluster"])

Error Handling

The SDK raises exceptions for errors returned by the API. Catch them to handle failures gracefully.

from capo_dax import AsyncDAXClient
from capo_dax.error import ClusterAlreadyExistsFault


async def main():
    async with AsyncDAXClient() as dax:
        try:
            await dax.create_cluster()
        except ClusterAlreadyExistsFault as e:
            print(f"Error: {e}")
            print(e.data)  # additional error data

Retrying

The SDK retries failed operations automatically. Retry behaviour follows the Smithy specification: errors are retried based on their is_retryable and is_throttling_error attributes. Throttling errors use a longer base delay. Network-level failures (connection errors and timeouts) are also retried. Non-retryable errors, such as client errors without the @retryable trait, are raised immediately without further attempts.

The number of attempts defaults to 3 and can be changed at the client level via retry_max_attempts, or per call via config_overrides.

from capo_dax import AsyncDAXClient


async def main():
    async with AsyncDAXClient() as dax:
        # Default: 3 attempts for every operation
        response = await dax.create_cluster()

        # Override per operation
        response = await dax.create_cluster(config_overrides={"retry_max_attempts": 5})

        # Disable retries for this call
        response = await dax.create_cluster(config_overrides={"retry_max_attempts": 1})