Metadata-Version: 1.1
Name: simpleflow
Version: 0.11.8
Summary: Python library for dataflow programming with Amazon SWF
Home-page: https://github.com/botify-labs/simpleflow
Author: Greg Leclercq
Author-email: greg@botify.com
License: Copyright 2014 Greg Leclercq

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Description: ===============================
        simpleflow
        ===============================
        
        .. image:: https://badge.fury.io/py/simpleflow.png
            :target: http://badge.fury.io/py/simpleflow
        
        .. image:: https://travis-ci.org/botify-labs/simpleflow.png?branch=master
                :target: https://travis-ci.org/botify-labs/simpleflow
        
        .. image:: https://pypip.in/d/simpleflow/badge.png
                :target: https://crate.io/packages/simpleflow?version=latest
        
        
        Simple Flow is a Python library that provides abstractions to write programs in
        the `distributed dataflow paradigm
        <https://en.wikipedia.org/wiki/Distributed_data_flow>`_. It relies on futures
        to describe the dependencies between tasks. It coordinates the execution of
        distributed tasks with Amazon `SWF <https://aws.amazon.com/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
        <http://docs.python.org/3/library/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).
        - Provides decider and activity worker process for execution with Amazon SWF.
        - Ships with the `simpleflow` command. `simpleflow --help` for more information
          about the commands it supports.
        
        Quickstart
        ----------
        
        Let's take a simple example that computes the result of ``(x + 1) * 2``. You
        will find this example in ``examples/basic.py``.
        
        We need to declare the functions as activities to make them available:
        
        .. code:: python
        
            from simpleflow import (
                activity,
                Workflow,
                futures,
            )
        
            @activity.with_attributes(task_list='quickstart', version='example')
            def increment(x):
                return x + 1
        
            @activity.with_attributes(task_list='quickstart', version='example')
            def double(x):
                return x * 2
        
            @activity.with_attributes(task_list='quickstart', version='example')
            def delay(t, x):
                time.sleep(t)
                return x
        
        And then define the workflow itself in a ``example.py`` file:
        
        .. code:: python
        
            class BasicWorkflow(Workflow):
                name = 'basic'
                version = 'example'
                task_list = 'example'
        
                def run(self, x, t=30):
                    y = self.submit(increment, x)
                    yy = self.submit(delay, t, y)
                    z = self.submit(double, y)
        
                    print '({x} + 1) * 2 = {result}'.format(
                        x=x,
                        result=z.result)
                    futures.wait(yy, z)
                    return z.result
        
        Now check that the workflow works locally with an integer "x" and a wait value "t": ::
        
            $ simpleflow workflow.start --local examples.basic.BasicWorkflow --input '[1, 5]'
            (1 + 1) * 2 = 4
        
        *input* is encoded in JSON format and can contain the list of *positional*
        arguments such as ``'[1, 1]`` or a *dict* with the ``args`` and ``kwargs`` keys
        such as ``{"args": [1], "kwargs": {}}``, ``{"kwargs": {"x": 1}}``, or
        ``'{"args": [1], "kwargs": {"t": 5}}'```.
        
        Now that you are confident that the workflow should work, you can run it on
        Amazon SWF with the ``standalone`` command : ::
        
           $ simpleflow standalone --domain TestDomain examples.basic.BasicWorkflow --input '[1, 5]'
        
        The *standalone* command sets an unique task list and manage all the processes
        that are needed to execute the workflow: decider, activity worker, and a client
        that starts the workflow. It is very convenient for testing a workflow by
        executing it with SWF during the development steps or integration tests.
        
        Let's take a closer look to the workflow definition.
        
        It is a *class* that inherits from :class:`simpleflow.Workflow`:
        
            .. code:: python
        
            class BasicWorkflow(Workflow):
        
        It defines 3 class attributes:
        
        - *name*, the name of the SWF workflow type.
        - *version*, the version of the SWF workflow type. It is currently provided
          only for labeling a workflow.
        - *task_list*, the default task list (see it as a dynamically created queue)
          where decision tasks for this workflow will be sent. Any *decider* that
          listens on this task list can handle this workflow. This value can be
          overrided by the simpleflow commands and objects.
        
        It also implements the :meth:`run` method that takes two arguments: ``x`` and
        ``t=30`` (i.e. ``t`` is optional and has the default value ``30``). These
        arguments are passed with the ``--input`` option. The :meth:`run` method
        describes the workflow and how its tasks should execute.
        
        Each time a decider takes a decision task, it executes again the :meth:`run`
        from the start. When the workflow execution starts, it evaluates ``y =
        self.submit(increment, x)`` for the first time. *y* holds a future in state
        ``PENDING``. The execution continues with the line ``yy = self.submit(delay, t,
        y)``. *yy* holds another future in state ``PENDING``. This state means the task
        has not been scheduled. Now execution still continue in the :meth:`run` method
        with the line ``z = self.submit(double, y)``. Here it needs the value of the
        *y* future to evaluate the :func:`double` activity. As the execution cannot
        continues, the decider schedules the task :func:`increment`. *yy* is not a
        dependency for any task so it is not scheduled.
        
        Once the decider has scheduled the task for *y*, it sleeps and waits for an
        event to be waken up. This happens when the :func:`increment` task completes.
        SWF schedules a decision task. A decider takes it and executes the
        :meth:`BasicWorkflow.run` method again from the start. It evalues the line ``y
        = self.submit(increment, x)``. The task associated with the *y* future has
        completed. Hence *y* is in state ``FINISHED`` and contains the value ``2`` in
        ``y.result``. The execution continues until it blocks. It goes by ``yy =
        self.submit(delay, t, y)`` that stays the same. Then it reaches ``z =
        self.submit(double, y)``. It gets the value of ``y.result`` and *z* now holds a
        future in state ``PENDING``. Execution reaches the line with the ``print``. It
        blocks here because ``z.result`` is not available. The decider schedules the
        task backs by the *z* future: ``double(y)``. The workflow execution continues
        so forth by evaluating the :meth:`BasicWorkflow.run` again from the start until
        it finishes.
        
        Commands
        --------
        
        Overview
        ~~~~~~~~
        
        Please read and even run the `demo` script to have a quick glance of
        `simpleflow` commands. To run the `demo` you will need to start decider and
        activity worker processes.
        
        Start a decider with: ::
        
            $ simpleflow decider.start --domain TestDomain --task-list test examples.basic.BasicWorkflow
        
        Start an activity worker with: ::
        
            $ simpleflow worker.start --domain TestDomain --task-list quickstart examples.basic.BasicWorkflow
        
        Then execute ``./demo``.
        
        Controlling SWF region and domain
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        The SWF region is controlled by the environment variable ``AWS_DEFAULT_REGION``. This variable
        comes from the legacy "simple-workflow" project. The option might be exposed through a
        ``--region`` option in the future (if you want that, please open an issue).
        
        The SWF domain is controlled by the ``--domain`` on most simpleflow commands. It can also
        be set via the ``SWF_DOMAIN`` environment variable. In case both are supplied, the
        command-line value takes precedence over the environment variable.
        
        Note that some simpleflow commands expect the domain to be passed as a positionnal argument.
        In that case the environment variable has no effect for now.
        
        List Workflow Executions
        ~~~~~~~~~~~~~~~~~~~~~~~~
        
            $ simpleflow workflow.list TestDomain
            basic-example-1438722273  basic  OPEN
        
        Workflow Execution Status
        ~~~~~~~~~~~~~~~~~~~~~~~~~
        
            $ simpleflow --header workflow.info TestDomain basic-example-1438722273
            domain      workflow_type.name    workflow_type.version      task_list  workflow_id               run_id                                          tag_list      execution_time  input
            TestDomain  basic                 example                               basic-example-1438722273  22QFVi362TnCh6BdoFgkQFlocunh24zEOemo1L12Yl5Go=                          1.70  {u'args': [1], u'kwargs': {}}
        
        Tasks Status
        ~~~~~~~~~~~~
        
        You can check the status of the workflow execution with: ::
        
            $ simpleflow --header workflow.tasks DOMAIN WORKFLOW_ID [RUN_ID] --nb-tasks 3
            $ simpleflow --header workflow.tasks TestDomain basic-example-1438722273
            Tasks                     Last State    Last State Time             Scheduled Time
            examples.basic.increment  scheduled     2015-08-04 23:04:34.510000  2015-08-04 23:04:34.510000
            $ simpleflow --header workflow.tasks TestDomain basic-example-1438722273
            Tasks                     Last State    Last State Time             Scheduled Time
            examples.basic.double     completed     2015-08-04 23:06:19.200000  2015-08-04 23:06:17.738000
            examples.basic.delay      completed     2015-08-04 23:08:18.402000  2015-08-04 23:06:17.738000
            examples.basic.increment  completed     2015-08-04 23:06:17.503000  2015-08-04 23:04:34.510000
        
        Profiling
        ~~~~~~~~~~~~
        
        You can profile the execution of the workflow with: ::
        
            $ simpleflow --header workflow.profile TestDomain basic-example-1438722273
            Task                                 Last State    Scheduled           Time Scheduled  Start               Time Running  End                 Percentage of total time
            activity-examples.basic.double-1     completed     2015-08-04 23:06              0.07  2015-08-04 23:06            1.39  2015-08-04 23:06                        1.15
            activity-examples.basic.increment-1  completed     2015-08-04 23:04            102.20  2015-08-04 23:06            0.79  2015-08-04 23:06                        0.65
        
        
        Controlling log verbosity
        ~~~~~~~~~~~~~~~~~~~~~~~~~
        
        You can control log verbosity via the `LOG_LEVEL` environment variable. Default is `INFO`. For instance,
        the following command will start a decider with `DEBUG` logs:
        
            $ LOG_LEVEL=DEBUG simpleflow decider.start --domain TestDomain --task-list test examples.basic.BasicWorkflow
        
        
        Documentation
        -------------
        
        Full documentation (work-in-progress) is available at
        https://simpleflow.readthedocs.org/.
        
        Requirements
        ------------
        
        - Python 2.6.x or 2.7.x
        - Python 3.x compatibility is NOT guaranteed for now: https://github.com/botify-labs/simpleflow/issues/87
        
        
        Release
        -------
        
        In order to release a new version, you'll need credentials on pypi.python.org for this
        software, as long as write access to this repository. Ask via an issue if needed.
        Rough process:
        
            git checkout master
            git pull --rebase
            v=0.10.0
            vi simpleflow/__init__.py
            git add . && git commit -m "Bump version to $v"
            git tag $v
            git push --tags
            python setup.py sdist upload -r pypi
        
        
        License
        -------
        
        MIT licensed. See the bundled `LICENSE <https://github.com/botify-labs/simpleflow/blob/master/LICENSE>`_ file for more details.
        
        
        ======================
        Python Simple Workflow
        ======================
        
        .. image:: https://travis-ci.org/botify-labs/python-simple-workflow.png?branch=develop
        
        python-simple-workflow is a wrapper for `Amazon Simple Workflow <http://aws.amazon.com/en/swf/>`_ service.
        It aims to provide some abstractions over the webservice concepts through `Boto <https://boto.readthedocs.org/en/latest/ref/swf.html>`_ library Swf api implementation.
        
        It aims to provide:
        
        * **Modelisation**: Swf entities and concepts are to be manipulated through `Models <http://test.com>`_ and `QuerySets <http://test.com>`_ (any ressemblance with the `Django <http://test.com>`_ api would not be a coincidence).
        * **High-level Events, History**: A higher level of abstractions over Swf *events* and *history*. Events are implemented as stateful objects aware of their own state and possible transitions. History enhance the events flow description, and can be compiled to check it's integrity and the activities statuses transitions.
        * **Decisions**: Stateful abstractions above the Swf decision making system.
        * **Actors**: Swf actors base implementation such as a `Decider <http://test.com>`_ or an activity task processor `Worker <http://test.com>`_ from which the user can easily inherit to implement it's own decision/processing model.
        
        It provides querysets and model objects over commonly used concepts: domains, workflow types, activity types, and so on.
        
        It is under MIT license, and any ideas, features requests, patches, pull requests to improve it are of course welcome.
        
        Installation
        ============
        
        .. code-block:: shell
        
            pip install simple-workflow
        
        
        Usage and all the rest
        ======================
        
        Please, refer to `Documentation <http://python-simple-workflow.readthedocs.org>`_
        
        
        What's left?
        ============
        
        Amazon interface models implementation:
         ✔ Domain @done (13-04-02 10:01)
         ✔ Workflow Type @done (13-04-02 10:01)
         ✔ Workflow Execution @done (13-04-05 10:13)
         ☐ Activity Type
         ☐ Decider
        
        Amazon interface querysets implementation:
         ✔ DomainQuery @done (13-04-02 10:02)
         ✔ WorkflowTypeQuery @done (13-04-02 10:03)
         ✔ Workflow Execution @done (13-04-05 10:13)
         ☐ Activity Type
         ☐ Decider
        
        General:
         ☐ Add sphinx doc
         ☐ Document real world example
         ☐ TESTS TESTS TESTS!
        
        
        Changelog
        ---------
        
        0.11.8
        ~~~~~~
        
        - Retry boto.swf connection to avoid frequent errors when using IAM roles (#99)
        
        0.11.7
        ~~~~~~
        
        Same as 0.11.6 but the 0.11.6 on pypi is broken (pushed something similar to 0.11.5 by mistake)
        
        0.11.6
        ~~~~~~
        
        - Add issubclass_ method (#96)
        - Avoid duplicate logs if root logger has an handler (#97)
        - Allow passing SWF domain via the SWF_DOMAIN environment variable (#98)
        
        0.11.5
        ~~~~~~
        
        - Don't mask activity cancel exception (#84)
        - Propagate all decision response attributes up to Executor.replay() (#76, #94)
        
        0.11.4
        ~~~~~~
        
        - ISO dates in workflow history #91
        - Fix potential infinite retry loop #90
        
        0.11.3
        ~~~~~~
        
        - Fix replay hooks introduced in 0.11.2 (#86)
        - Remove python3 compatibility from README (which was not working for a long time)
        
        0.11.2
        ~~~~~~
        
        - Add new workflow hooks (#79)
        
        0.11.1
        ~~~~~~
        
        - Fix logging when an exception occurs
        
        0.11.0
        ~~~~~~
        
        - Merge ``swf`` package into simplefow for easier maintenance.
        
        
        0.10.4 and below
        ~~~~~~~~~~~~~~~~
        
        Sorry changes were not documented for simpleflow <= 0.10.x.
        
Keywords: simpleflow amazon swf simple workflow
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
