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 3.5, 3.6, 3.7, 3.8 (tested)
• Boto3 (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 where a user enters a coffee shop, orders a coffee and a chocolate chip cookie. All ordered items are prepared and completed, the user pays the order, receives the ordered items, then leave the shop.

The code below represents the workflow decider. For the full code sample, see the example.

enter = schedule('enter', self.create_enter_coffee_activity)
enter.wait()

total = 0
for item in ['coffee', 'chocolate_chip_cookie']:
    activity_name = 'order_{item}'.format(item=item)
    activity = schedule(activity_name,
        self.create_order_activity,
        input={'item': item})
    total += activity.result.get('price')

pay_activity = schedule(
    'pay', self.create_payment_activity,
    input={'total': total})

get_order = schedule('get_order', self.create_get_order_activity)

# Waiting for paying and getting the order to complete before
# we let the user leave the coffee shop.
pay_activity.wait(), get_order.wait()
schedule('leave_coffee_shop', self.create_leave_coffee_shop)

.
├── cli.py # Instantiate the workers
├── flows # All your application flows.
│   ├── __init__.py
│   └── example.py # Should contain a structure similar to the code sample.
├── tasks # All your tasks
│   ├── __init__.py
│   └── s3.py # Task that focuses on s3 files.
└── task_example.py # Your different tasks.

• Michael Ortali (Author)
• Adam Griffiths
• Raphael Antonmattei
• John Penner