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 0.12.0

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 0.12.0
File Size Uploaded Provenance
capo_scheduler-0.12.0.tar.gz 90.7 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for capo-scheduler 0.12.0
File Interpreter ABI Platform
capo_scheduler-0.12.0-py3-none-any.whl Python 3 none any Details

Total release size: 246.9 kB

Release files / capo_scheduler-0.12.0.tar.gz

Download URL capo_scheduler-0.12.0.tar.gz
Size 90.7 kB
Tags Source
SHA-256 checksum
How to use checksums
b2bf37da9a2b94e8ef53103ab1b6fb4fa3281f9a6e90269e91a2c6f86de0c063
BLAKE2b-256 checksum
How to use checksums
2d0890c11d7213f4bf096d579b5f11c27c2ffadceac7c01952550d130a039f4d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.12.18 {"installer":{"name":"uv","version":"0.12.18","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-0.12.0-py3-none-any.whl

Download URL capo_scheduler-0.12.0-py3-none-any.whl
Size 156.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
80e47b94b7ae870d160f9302dc1c42d9a15b829d147283205558da9b7495b79c
BLAKE2b-256 checksum
How to use checksums
be04ea2b846ceeb48205896f9d98615e87ee32e5194a3901d92650a06f5f6b6e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.12.18 {"installer":{"name":"uv","version":"0.12.18","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 0.12.0

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