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AWS Step Function Activity server framework

Project description


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.


$ pip install stefuna


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.

The Python multiprocessing start method for worker processes can be set in the config. By default ‘spawn’ is used to ensure a clean, safe worker process. Although potentially slower than ‘forkserver’ (or ‘fork’ which is not recommended), since new workers are typically rarely created, this should not be an issue.

Getting Started

See the examples folder for the files described below.

Step Function

Create an AWS Step Function Activity, for example hello.

Then create a Step Function State Machine, using the ARN of the activity you just created. For example a single state Hello World State Machine:

   "Comment": "A Hello World example with a single activity",
   "StartAt": "HelloWorld",
   "States": {
      "HelloWorld": {
        "Type": "Task",
        "Resource": "arn:aws:states:us-east-1:00000000000000:activity:hello",
        "End": true

Worker Code

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

import logging
from stefuna import Worker

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

class HelloWorker(Worker):

    def init(self):
        """Initialize the single instance in a worker"""
        # self.config is the worker config
        self.logger.debug('Init worker instance')

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

        # Do some work!
        # self.config is the worker config

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

Create a config file, 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-east-1:00000000000000:activity:hello'

# [OPTIONAL] The number of worker processes.
# If None, it will be set to the number of cores.
# Default is None.
processes = None

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

# [OPTIONAL] 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.
# Default is None.
maxtasksperchild = None

# [OPTIONAL] The multiprocessing start method for worker processes.
# See for more info
# The default is 'spawn' which starts a fresh python interpreter process.
# It is rather slow compared to using fork or forkserver, but we typically
# create workers and leave them running so the impact should be minimal.
# Possible values are:
# spawn - Recommended (Unix and Windows)
# fork - Not recommended due to thread-safety issues
# forkserver - On Unix platforms which support passing fds over Unix pipes
# '' - Uses the python defaults. Not recommended.
start_method = 'spawn'

# [OPTIONAL] 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"}
# Default is 8080
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
$ stefuna --help
usage: stefuna [-h] [--config CONFIG] [--worker WORKER]
               [--activity-arn ACTIVITY_ARN] [--processes PROCESSES]
               [--loglevel LOGLEVEL]

Run a Step Function Activity server.

optional arguments:
  -h, --help            show this help message and exit
  --config CONFIG       Module or dict of config to override defaults
  --worker WORKER       Module and class of worker in dot notation. Overrides
                        config setting.
  --activity-arn ACTIVITY_ARN
                        Step Function Activity ARN, Overrides config setting.
  --processes PROCESSES
                        Number of worker processes. Overrides config setting.
                        If 0, cpu_count is used.
  --loglevel LOGLEVEL   Loglevel (debug, info, warning, error or critical).
                        Overrides config setting.

History (Change Log)



MIT License



1.0.1 [2019-06-02] * Restrict to python >=3.4 * Add activity-arn arg to stefuna

1.0.0 [2019-03-20] * Added docs

0.9.9 [2019-03-20] * Fixed spawn configuration for workers on Unix.

0.9.8 [2019-03-07] * Check server class was located * Add start_method as config setting and default to spawn. * BREAKING: Changed default config values. Heartbeat is disabled by default.

0.9.7 [2018-10-18] * Truncate the failure cause if over the result size limit * Removed Python 3.4 from Travis test envs due to a dateutils / urllib3 install conflict.

0.9.6 [2017-11-06] * Fix missing attribute bug if no healthcheck configured * Improved timing of heartbeats

0.9.5 [2017-10-30] * Keep pypi happy

0.9.4 [2017-10-30] [not available through pypi] * Shutdown healthcheck server immediately when stopping server * Added info logs

0.9.3 [2017-10-27] * Add customizable Server subclass with init method.

0.9.2 [2017-10-25] * Change default loglevel to info. * Improve log format. * Handle client error when doing heartbeat and don’t retry for failed tokens.

0.9.1 [2017-10-20] * Suppress boto dropped connection info log messages.

0.9.0 [2017-09-26] * Add HTTP healthcheck

0.8.4 [2017-09-18] * Add loglevel arg

0.8.3 [2017-09-18] * Add processes arg to stefuna * Add timestamp to log format

0.8.2 [2017-08-16] * Set the region based on region in activity ARN.

0.8.1 [2017-08-15] * First public release

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