skip to navigation
skip to content

arbiter 0.2.1

A concurrent task-runner that resolves dependency issues

Latest Version: 0.3.0

Arbiter is a 2.7, 3.3+ compatible concurrent task runner that automatically handles resolving dependency between tasks:

from arbiter import create_task, run_tasks

results = run_tasks(
        create_task('foo', foo_function, args=('bar', 'baz')),
        create_task('lorem', lorem_function, dependencies=['foo']),
        create_task('ipsum', ipsum_function, dependencies=['foo']),


Arbiter is not yet on PyPI, so it has to be installed manually.


The task-runner is implemented using concurrent.futures. If running on Python 2, the backport from python 3 will need to be installed:

$ pip install futures

Manual Installation

To install manually:

$ git clone
$ cd Arbiter
$ python install



Tasks can be created using the create_task function:

from arbiter import create_task

task = create_task('name', function)

Create takes a name (which must be unique among tasks) and a function representing the task. The function will be considered successful if it runs without raising an exception. Arguments can be passed to the function using the args and kwargs arguments:

create_task('name', function, args=('foo', 'bar'), kwargs={'baz': 'qux'})

Any tasks that need to run to completion prior to your task, specify them using the dependencies argument:

create_task('bar', function, dependencies=['foo'])

Any number of dependencies may be supplied.

It’s quite possible that your task might require multiple tries to succeed. To automatically force a task to retry using the retries and delay arguments:

create_task('failable', sketchy_function, replies=3, delay=timedelta(seconds=5))

If delay isn’t given, the function will retry immediately.

Running Tasks

The run_tasks function will run a list of tasks, handling their dependencies:

from arbiter import run_tasks

results = run_tasks(task_list)

By default, run_tasks will run the tasks with one worker thread. workers can be increased using the max_workers argument, and processes=True will run the tasks using working processes instead of threads (NOTE: some tasks may only run using threads).

run_tasks returns a dict of Result objects. result.success is a boolean value signifying whether the task completed. If successful, result.value will contain the task’s return value. If the task failed, result.value will contain the exception that was thrown that caused the task to fail.

Two custom exceptions exist to signify errors that prevented the task from running at all. arbiter.exceptions.FailedDependencyError represents a task that had a dependency that failed. arbiter.exceptions.UnsatisfiedDependencyError represents a task that had a dependency that doesn’t exist, or can’t be run because of a circular dependency.

Arbiter is guaranteed to eventually complete (as long as the tasks you give it are guaranteed to eventually complete or fail), but if you have some stricter time constraints you can use the timeout flag:

results = run_tasks(task_list, timeout=timedelta(minutes=1))

NOTE: If a timeout occurs, queued tasks will be cancelled and run_tasks will return, but any running tasks will continue to run (python will not exit until these tasks complete). This is a property of the Future class, so it cannot easily be worked around. Where possible, it may be preferrable to directly add timeout code to your task.

For tasks that are already running, arbiter.exceptions.UncancelledTaskError is returned as a result. UncancelledTaskError subclasses TimeoutError, so you can just treat it as a TimeoutError, but also includes a future attribute so that you can deal with it directly.


Results from a task can be passed as named arguments by passing chain=true to create_task:

results = run_tasks(
        create_task('response', requests.get, args=('',)),
        create_task('temperature', lambda response:'temp="(\d*)"', response.text).group(1), dependencies=['response'], chain=True)
        create_task('text', "The current temperature is: {temperature}.".format, dependencies=['temperature'], chain=True)
print(results['text'].value)  # "The current temperature is 17."


Arbiter is provided under an MIT License.

File Type Py Version Uploaded on Size
arbiter-0.2.1-py2.py3-none-any.whl (md5) Python Wheel 2.7 2014-08-26 9KB
arbiter-0.2.1.tar.gz (md5) Source 2014-08-26 7KB