laurrentt / stefuna

Write an AWS Step Function Activity Server with a few lines of Python

stefuna

Stefuna is a simple AWS Step Function Activity server framework. It makes it incredibly quick and easy to write workers to process activity tasks in Python.

Install

$ pip install stefuna

Implementation

Stefuna uses a multiprocessing Pool of pre-forked worker processes to run the activity tasks. There is a single instance of a Server class in the main process and a single instance of a Worker class in each worker process. To implement your task, simply create a Worker subclass, override the run_task(self, task_token, input_data) method and start the server.

The run_task method can do whatever work it requires and then return a result as a string or dict (which is automatically JSON stringified). It can be a long-running task but the worker process won't be released until the method returns.

If run_task raises an exception, the task is failed with a Task.Failure error which can be handled in the Step Function state machine. Alternatively, a worker can call self.send_task_failure(error, cause) with a custom error string and return value from run_task will be ignored.

Configurable heartbeats are supported for longer-running tasks.

A healthcheck port can be configured so the server listens for HTTP GET requests on http://localhost:<healthcheck>/

The Server instance in the main class can be customized by setting a custom Server subclass in the config and overriding the init method.

Getting Started

See the examples folder for the files described below.

Create a worker class, which is a subclass of the stefuna.Worker in the file hello_worker.py:

import logging
from stefuna import Worker

logger = logging.getLogger('stefuna.example')


class HelloWorker(Worker):

    def init(self):
        """Initialize the single instance in a worker"""
        pass

    def run_task(self, task_token, input_data):
        self.logger.debug('Worker in run_task')

        # Do some work!

        # Return value can be a string or a dict/array that
        # will be JSON stringified.
        return {"message": "Hello World"}

Create a config file hello_config.py, setting the worker class, server name, and activity ARN:

#
# Stefuna server worker config file
#

# [OPTIONAL] The module path of the server class
server = 'examples.hello_server.HelloServer'

# The module path of the worker class
worker = 'examples.hello_worker.HelloWorker'

# The base name of the server that will be combined with host and pid
# and used when requesting tasks from AWS.
name = 'HelloExample'

# Set the ARN for the activity that this server will work on.
activity_arn = 'arn:aws:states:us-west-2:00000000000000:activity:hello'

# The number of worker processes.
# If None, it will be set to the number of cores.
processes = None

# Number of seconds between heartbeats.
# None or 0 means there is no heartbeat.
heartbeat = 120

# Maximum number of tasks for a worker to run before the worker
# process is automatically killed and a new one created.
# If None, workers will not be killed.
maxtasksperchild = None

# If set to a non-zero integer, an HTTP healthcheck handler listens on
# the port number.
# Healthcheck requests are GET requests to 'http://localhost:<healthcheck>/'
# and return JSON: {"status": "ok"}
healthcheck = 8080

# [OPTIONAL] The server_config is an arbitrary dictionary that is available
# in the server instance as self.config and passed to server init()
# Use it for server-specific configuration.
server_config = {
    'foo': 'bar'
}

# [OPTIONAL] The worker_config is an arbitrary dictionary that is available
# in the worker instance as self.config
# Use it for worker-specific configuration.
worker_config = {
    'foo': 'bar'
}

Run the server:

$ stefuna --config=hello_config

History (Change Log)

See HISTORY.rst

License

MIT License

See LICENSE