Lightweight library for AWS SWF.
Garcon deals with easy going clients and kitchens. It takes orders from clients (deciders), and send them to the kitchen (activities). Difficult clients and kitchens can be handled directly by the restaurant manager.
- Python 2.7, 3.4 (tested)
- Boto 2.34.0 (tested)
The goal of this library is to allow the creation of Amazon Simple Workflow without the need to worry about the orchestration of the different activities and building out the different workers. This framework aims to help simple workflows. If you have a more complex case, you might want to use directly boto.
The code sample shows a workflow that has 4 activities. It starts with activity_1, which after being completed schedule activity_2 and activity_3 to be ran in parallel. The workflow ends after the completion of activity_4 which requires activity_2 and activity_3 to be completed.
from __future__ import print_function
import boto.swf.layer2 as swf
from garcon import activity
from garcon import task
domain = 'dev'
create = activity.create(domain)
test_activity_1 = create(
name='activity_1',
tasks=task.SyncTasks(
lambda activity, context: print('activity_1')))
test_activity_2 = create(
name='activity_2',
requires=[test_activity_1],
tasks=task.AsyncTasks(
lambda activity, context: print('activity_2_task_1'),
lambda activity, context: print('activity_2_task_2')))
test_activity_3 = create(
name='activity_3',
requires=[test_activity_1],
tasks=task.SyncTasks(
lambda activity, context: print('activity_3')))
test_activity_4 = create(
name='activity_4',
requires=[test_activity_3, test_activity_2],
tasks=task.SyncTasks(
lambda activity, context: print('activity_4'))).
├── cli.py # Instantiate the workers
├── flows # ALl your application flows.
│ ├── __init__.py
│ └── example.py # Should contain a structure similar to the code sample.
└── tasks
├── __init__.py
└── task_example.py # Your different tasks.
- Michael Ortali (@xethorn)
- Adam Griffiths (@adamlwgriffiths)
- Raphael Antonmattei (@rantonmattei)