tgext.asyncjob 0.3.1
Asynchronous jobs worker for TurboGears2
License: MIT
Keywords: turbogears2.extension pylons

About AsyncJob
-------------------------

.. image:: https://drone.io/bitbucket.org/axant/tgext.asyncjob/status.png
    :target: https://drone.io/bitbucket.org/axant/tgext.asyncjob

AsyncJob is a TurboGears2 extension made to handle background/synchronous jobs.
Permits to quickly return responses to the user while the system performs more work on
background, it can be useful for video transcoding, thumbnails generation or other
tasks where the user cannot expect the require time before getting an answer.

To perform a task in background simply perform::

    from tgext.asyncjob import asyncjob_perform
    asyncjob_perform(callable, arg1, arg2, kwarg=value)

Installing
-------------------------------

tgext.asyncjob can be installed both from pypi or from bitbucket::

    easy_install tgext.asyncjob

should just work for most of the users

Enabling AsyncJob
----------------------------------

In your application *config/app_cfg.py* append the following lines::

    import tgext.asyncjob
    tgext.asyncjob.plugme(base_config)

Or use the pluggable application interface if tgext.pluggable is available::

    from tgext.pluggable import plug
    plug(base_config, 'tgext.asyncjob')

You can pass the **Globals** object itself to the *plug* function::

    plug(base_config, 'tgext.asyncjob', app_globals=app_globals)

which will be used to store the tasks queue, otherwise asyncjob will autodetect
the Globals object from the call stack frame getting the object inside where
it has been called.

Performing background tasks
----------------------------

To perform a background task you can simply use **tgext.asyncjob.asyncjob_perform**
it called from any context where there is a valid request it will perform the callable
passed as first argument in background with the parameters provided::

    from tgext.asyncjob import asyncjob_perform

    def background_task(number):
        print number*2

    asyncjob_perform(background_task, 5)

Tracking Tasks Progress
----------------------------

asyncjob traces tasks status and permits to update it to implement progress bars or other kind
of user reporting of long running operations. Each time you call **asyncjob_perform** it will
return an unique id for the action you just scheduled that can be used to retrieve
the task status anytime.

You can update progress status anytime from inside the background task itself by calling
**asyncjob_set_progress(value, data)** the *value* argument is expected to be an int value
while the second optional *data* argument can be anything that you might want to get back later.

To retrieve the progress status you can call **asyncjob_get_progress** passing it the
id of the task for which you want to fetch status. Returned value is a 2 items tuple
with the first entry being a the numeric value and the second one being the data you passed
to **asyncjob_set_progress**. 
If the task has completed it will return *None*, if it has not yet started you will get *(-1, None)*

Progress tracking example::

    from tgext.asyncjob import asyncjob_perform, asyncjob_get_progress, asyncjob_set_progress

    @expose()
    def controller_method(self):
        def async_action():
            for i in range(5):
                asyncjob_set_progress(i)
                time.sleep(1)

        taskid = asyncjob_perform(async_action)
        return redirect(url('/state', uid=taskid))

    @expose()
    def state(self, uid):
        state = asyncjob_get_progress(uid)
        if not state:
            return 'Job Completed'
        elif state[0] < 0:
            return 'Not yet started'
        else:
            return str(state[0])

Progress Tracking with Multiple Processes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

When using multiple processes to serve your web application, the default task tracking
system won't be able to track the process state between different processes.

To solve this issue you must rely on an alternative progress tracker that stores the
state in a shared storage. By default the ``tgext.asyncjob.tracker.redisdb.RedisProgressTracker``
is provided, which stores state in a Redis database.

Using it is as simple as::

    from tgext.asyncjob import start_async_worker
    tgext.asyncjob.tracker.redisdb import RedisProgressTracker

    class Globals(object):
        def __init__(self):
            start_async_worker(progress_tacker=RedisProgressTracker(host='localhost'))

The ``RedisProgressTracker`` class accepts ``host``, ``port``, ``db`` and ``timeout`` arguments
which set the database connection options and the timeout of progress tracking keys (to avoid
leaving stray keys behind). By default db **15** with a timeout of **1 hour** is used.

Custom Progress Trackers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Writing a custom progress tracker is as simple as providing a class with following methods::

    class MyProgressTracker(object):
        def track(self, entryid): pass
        def remove(self, entryid): pass
        def set_progress(self, entryid, value, message): pass
        def get_progress(self, entryid): pass

Your custom progress tracker can then be passed as argument to ``start_async_worker`` to store
status on SQL database, MongoDB or any other system.

Refer to ``tgext.asyncjob.tracker.redisdb.RedisProgressTracker`` or
``tgext.asyncjob.tracker.memory.MemoryProgressTracker`` for implementation examples.

Accessing the database
------------------------

By default asyncjob manages SQLAlchemy sessions and transactions by itself. Each background task
is encapsulated in a transaction which is reverted in case of any exception.

AsyncJob uses its own SQLAlchemy session, so never pass an object already bound to another session.
Query them again.

The only issue that developers might have to keep in mind is that when looking for objects
that they just created before starting the background task, they might not yet be available inside
the DB. To avoid this issue asyncjob provides **asyncjob_timed_query** which will perform a query
looking for a result until the result itself is found or a timeout is reached (by default 60 seconds).

This can be used to fetch back objects created before starting the background task waiting for
them to appear on the database::

    from tgext.asyncjob import asyncjob_perform, asyncjob_timed_query

    @expose()
    def controller_method(self):
        def async_query_action(group_id):
            group = asyncjob_timed_query(DBSession.query(Group).filter_by(group_id=group_id)).first()
            group.display_name = 'Prova'

        g = Group(group_name='test_group')
        DBSession.add(g)
        DBSession.flush()
        asyncjob_perform(async_query_action, g.group_id)
        return 'OK'

To change the timeout you can simply pass different *retries* and *interval* parameters to
asyncjob_timed_query::

    asyncjob_timed_query(DBSession.query(Group).filter_by(group_id=group_id),
                         retries=10, interval=6).first()