kaiju-scheduler¶

Reference

Quickstart¶

kaiju-scheduler is a simple asynchronous tasks scheduler / executor for asyncio functions. It adds a bit of extra such as retries, timeouts, execution policies etc.

Installation¶

With pip and python 3.8+:

pip3 install kaiju-scheduler

How to use¶

See the user guide for more info.

Initialize a scheduler and schedule your procedure for periodic execution. Then start the scheduler.

from kaiju_scheduler import Scheduler

async def call_async_procedure(*args, **kws):
    ...

async def main():
    scheduler = Scheduler()
    scheduler.schedule_task(call_async_procedure, interval_s=10, args=(1, 2), kws={'value': True})
    await scheduler.start()
    ...
    await scheduler.stop()

Alternatively you can use the scheduler contextually.

async def main():
    async with Scheduler() as scheduler:
        scheduler.schedule_task(call_async_procedure, interval_s=10, args=(1, 2), kws={'value': True})

Scheduler.schedule_task returns a task object which you can enable / disable or supress the task execution in your code temporarily using task.suspend context. You can also access the previous call results from task.result attribute.

class Cache:

    def __init__(self, scheduler: Scheduler):
        self._scheduler = scheduler
        self._cache_task = self._scheduler.schedule_task(
            self.cache_all, interval_s=600, policy=scheduler.ExecPolicy.WAIT)

    async def cache_all(self):
        ...

    async def reconfigure_cache(self):
        async with self._cache_task.suspend():
            "Do something while the caching is suspended"

You can specify retries for common types of errors such as IOError or ConnectionError using retries parameter. The scheduler will try to retry the call on such type of error.

scheduler.schedule_task(call_async_procedure, interval_s=300, retries=3, retry_interval_s=1)

There are various policies considering task execution. See the reference for more info on that.

Server¶

There’s also a simple ‘server’ for handling asyncio tasks inside Python. It extends the standard loop functionality with retries, timeouts and impose some rate limit and prevent the loop from growing infinitely.

The server returns an asyncio.Task object which can be awaited independently. The idea is that any error is not raised but instead returned inside of the result. This allows for more convenient handling of errors while using this in streams, queues and server applications.

See the reference for more info on server functions.

from kaiju_scheduler import Server


async def call_something(arg1: int, arg2: int):
    return arg1 + arg2


async def main():
    async with Server() as server:
        task = await server.call(call_something, [1, 2])
        await task

License¶

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.