hank

Hank is an asynchronous job processing and orchestration system.

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Features

• Dispatching of work orders for individual jobs
• Orchestration of work flows of multiple work orders
• Support for managing large batch processes from running jobs

Quick Start

from hank import Dispatcher, LocalMemoryWorkQueue, LocalMemoryResultStore, task


@task
def arithmetic_task(x, y):
    return x + y


dispatcher = Dispatcher()


if __name__ == '__main__':
    result_store = LocalMemoryResultStore()
    dispatcher.add_queue(LocalMemoryWorkQueue())
    dispatcher.add_result_store(result_store)
    dispatcher.add_job(arithmetic_task)
    result = dispatcher.send(arithmetic_task.work_order(2, 3))
    dispatcher.dispatch_until_exhausted()
    print(result.wait())

import sys

from hank import Dispatcher, job, RedisWorkQueue, RedisResultStore


@job
def arithmetic_job(work_order):
    work_order.dispatcher.store_result(sum(work_order.params['args']))


dispatcher = Dispatcher()


if __name__ == '__main__':
    result_store = RedisResultStore('redis://localhost:6379/1')
    dispatcher.add_queue(RedisWorkQueue('redis://localhost:6379/0'))
    dispatcher.add_result_store(result_store)
    dispatcher.add_job(arithmetic_job)

    if sys.argv[1] == 'worker':
        dispatcher.dispatch_forver()
    else:
        result = dispatcher.send(
            arithmetic_job.work_order(
                args=[int(i) for i in sys.argv[1:]]
            )
        )
        print(result.wait())

Installation

Stable Release: pip install hank
Development Head: pip install git+https://github.com/npilon/hank.git

Documentation

For full package documentation please visit npilon.github.io/hank.

Development

See CONTRIBUTING.md for information related to developing the code.

The Four Commands You Need To Know

1. pip install -e .[dev]

   This will install your package in editable mode with all the required development dependencies (i.e. tox).

2. make build

   This will run tox which will run all your tests in both Python 3.7 and Python 3.8 as well as linting your code.

3. make clean

   This will clean up various Python and build generated files so that you can ensure that you are working in a clean environment.

4. make docs

   This will generate and launch a web browser to view the most up-to-date documentation for your Python package.

Apache Software License 2.0