Python library for dataflow programming with Amazon SWF
Project description
Simple Flow is a Python library that provides abstractions to write programs in the distributed dataflow paradigm. It relies on futures to describe the dependencies between tasks. It coordinates the execution of distributed tasks with Amazon SWF.
A Future object models the asynchronous execution of a computation that may end.
It tries to mimics the interface of the Python concurrent.futures library.
Features
Provides a Future abstraction to define dependencies between tasks.
Define asynchronous tasks from callables.
Handle workflows with Amazon SWF.
Implement replay behavior like the Amazon Flow framework.
Handle retry of tasks that failed.
Automatically register decorated tasks.
Handle the completion of a decision with more than 100 tasks.
Provides a local executor to check a workflow without Amazon SWF (see simpleflow --local command).
Quickstart
Let’s take a simple example that computes the result of (x + 1) * 2.
We need to declare the functions as activities to make them available:
from simpleflow import activity
@activity.with_attributes(task_list='quickstart')
def increment(x):
return x + 1
@activity.with_attributes(task_list='quickstart')
def double(x):
return x * 2
And then define the workflow itself in a example.py file:
from simpleflow import Workflow
class SimpleComputation(Workflow):
def run(self, x):
y = self.submit(increment, x)
z = self.submit(double, y)
return z.result
Now check that the workflow works locally:
$ simpleflow --local -w example.SimpleComputation -i example/input.json
The file example/input.json contains the input passed to the workflow. It should have the format:
{"args": [1],
"kwargs": {}
}
which is equivalent to:
{"kwargs": {"x": 1}}
Documentation
Full documentation is available at https://simpleflow.readthedocs.org/.
Requirements
Python >= 2.6 or >= 3.3
License
MIT licensed. See the bundled LICENSE file for more details.
Changelog
0.1.0 (2014-02-19)
First release.
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