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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 0.15.0

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

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Source distribution for capo-scheduler 0.15.0
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Built distribution (wheel)

Table of built distributions (wheels) for capo-scheduler 0.15.0
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capo_scheduler-0.15.0-py3-none-any.whl Python 3 none any Details

Total release size: 247.9 kB

Release files / capo_scheduler-0.15.0.tar.gz

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