Skip to main content

Getting Started

Installation

pip install capo-cleanroomsml

Usage

from capo_cleanroomsml import AsyncCleanRoomsMLClient


async def main():
    async with AsyncCleanRoomsMLClient() as clean_rooms_ml:
        # Example: call the list_collaboration_configured_model_algorithm_associations operation
        response = await clean_rooms_ml.list_collaboration_configured_model_algorithm_associations()
        print(response["next_token"])

Pagination

Some operations in this SDK support pagination. If the operation supports pagination it will have an iter_ prefixed method that returns an async iterator.

from capo_cleanroomsml import AsyncCleanRoomsMLClient


async def main():
    async with AsyncCleanRoomsMLClient() as clean_rooms_ml:
        # Example: paginate over list_collaboration_configured_model_algorithm_associations
        async for item in clean_rooms_ml.iter_list_collaboration_configured_model_algorithm_associations():
            print(item)

Error Handling

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

from capo_cleanroomsml import AsyncCleanRoomsMLClient
from capo_cleanroomsml.error import AccessDeniedException


async def main():
    async with AsyncCleanRoomsMLClient() as clean_rooms_ml:
        try:
            await clean_rooms_ml.list_collaboration_configured_model_algorithm_associations()
        except AccessDeniedException 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_cleanroomsml import AsyncCleanRoomsMLClient


async def main():
    async with AsyncCleanRoomsMLClient() as clean_rooms_ml:
        # Default: 3 attempts for every operation
        response = await clean_rooms_ml.list_collaboration_configured_model_algorithm_associations()

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

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

Metadata

Release files for capo-cleanroomsml 0.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for capo-cleanroomsml 0.6.0
File Size Uploaded
capo_cleanroomsml-0.6.0.tar.gz 191.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for capo-cleanroomsml 0.6.0
File Interpreter ABI Platform
capo_cleanroomsml-0.6.0-py3-none-any.whl Python 3 none any Details

Total release size: 675.5 kB

Release files / capo_cleanroomsml-0.6.0.tar.gz

Download URL capo_cleanroomsml-0.6.0.tar.gz
Size 191.9 kB
Tags Source
SHA-256 checksum
How to use checksums
582a94e01fd9e709c1917bb9f805e800fa3cd48096777bc78cac94ae7a239f09
BLAKE2b-256 checksum
How to use checksums
1ab61e36d8513b47ebcafc76595332f11bc44c7be2798d174c05f01015b516f7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.12.22 {"installer":{"name":"uv","version":"0.12.22","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release files / capo_cleanroomsml-0.6.0-py3-none-any.whl

Download URL capo_cleanroomsml-0.6.0-py3-none-any.whl
Size 483.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
d9582b73f397e78a8c4809264a9f36fa2b08e3a10484edbd9136c358dbc36df3
BLAKE2b-256 checksum
How to use checksums
e35d9e990df86f1e51d2dd7afee702a52408f711ef214cffdcd9a4efa612cd4c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.12.22 {"installer":{"name":"uv","version":"0.12.22","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release history Release notifications | RSS feed

0.12.0

2 release files

0.11.0

2 release files

0.10.0

2 release files

0.9.0

2 release files

0.8.0

2 release files

0.7.0

2 release files

This release

0.6.0 This release

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.0

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page