Skip to main content

Getting Started

Installation

pip install capo-scheduler

Usage

from capo_scheduler import AsyncSchedulerClient


async def main():
    async with AsyncSchedulerClient() as scheduler:
        # Example: call the list_tags_for_resource operation
        response = await scheduler.list_tags_for_resource()
        print(response["tags"])

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_scheduler import AsyncSchedulerClient


async def main():
    async with AsyncSchedulerClient() as scheduler:
        # Example: paginate over list_schedules
        async for item in scheduler.iter_list_schedules():
            print(item)

Error Handling

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

from capo_scheduler import AsyncSchedulerClient
from capo_scheduler.error import InternalServerException


async def main():
    async with AsyncSchedulerClient() as scheduler:
        try:
            await scheduler.list_tags_for_resource()
        except InternalServerException 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_scheduler import AsyncSchedulerClient


async def main():
    async with AsyncSchedulerClient() as scheduler:
        # Default: 3 attempts for every operation
        response = await scheduler.list_tags_for_resource()

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

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

Metadata

Release files for capo-scheduler 0.11.0

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-scheduler 0.11.0
File Size Uploaded Provenance
capo_scheduler-0.11.0.tar.gz 87.2 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for capo-scheduler 0.11.0
File Interpreter ABI Platform
capo_scheduler-0.11.0-py3-none-any.whl Python 3 none any Details

Total release size: 241.3 kB

Release files / capo_scheduler-0.11.0.tar.gz

Download URL capo_scheduler-0.11.0.tar.gz
Size 87.2 kB
Tags Source
SHA-256 checksum
How to use checksums
f442bea05d49062517582913ef7405b2d3e7f1b61ea68df01137da358218d046
BLAKE2b-256 checksum
How to use checksums
75ffc2593ce5fa30fec053b7f23e71f36e047b27020fe7873e4042b40dd45b0b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.12.17 {"installer":{"name":"uv","version":"0.12.17","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_scheduler-0.11.0-py3-none-any.whl

Download URL capo_scheduler-0.11.0-py3-none-any.whl
Size 154.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
160e40862110f2af1d9e40b96d385bfb6900f4f318fbe63a20c562d32be1809e
BLAKE2b-256 checksum
How to use checksums
44be83c333b12d9facf469437b953812becdff648bbc7d535e0efdb44156bb68
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.12.17 {"installer":{"name":"uv","version":"0.12.17","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}

Security for capo-scheduler 0.11.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

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