Metadata-Version: 2.1
Name: psycopg2-mq
Version: 0.4
Summary: A message queue written around PostgreSQL.
Home-page: https://github.com/mmerickel/psycopg2_mq
Author: Michael Merickel
Author-email: oss@m.merickel.org
License: UNKNOWN
Keywords: psycopg2,postgres,postgresql
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: >=3.6
Requires-Dist: SQLAlchemy
Requires-Dist: transaction
Requires-Dist: zope.sqlalchemy
Provides-Extra: testing
Requires-Dist: pytest ; extra == 'testing'
Requires-Dist: pytest-cov ; extra == 'testing'

===========
psycopg2_mq
===========

.. image:: https://img.shields.io/pypi/v/psycopg2_mq.svg
    :target: https://pypi.org/pypi/psycopg2_mq

.. image:: https://img.shields.io/travis/mmerickel/psycopg2_mq/master.svg
    :target: https://travis-ci.org/mmerickel/psycopg2_mq

``psycopg2_mq`` is a message queue implemented on top of
`PostgreSQL <https://www.postgresql.org/>`__,
`SQLAlchemy <https://www.sqlalchemy.org/>`__, and
`psycopg2 <http://initd.org/psycopg/>`__.

Currently the library provides only the low-level constructs that can be used
to build a multithreaded worker system. It is broken into two components:

- ``psycopg2_mq.MQWorker`` - a reusable worker object that manages a
  single-threaded worker that can accept jobs and execute them. An application
  should create worker per thread. It supports an API for thread-safe graceful
  shutdown.

- ``psycopg2_mq.MQSource`` - a source object providing a client-side API for
  invoking and querying job states.

Data Model
==========

Queues
------

Workers run jobs defined in queues. Currently each queue will run jobs
concurrently, while a future version may support serial execution on a
per-queue basis. Each registered queue should contain an ``execute_job(job)``
method.

Jobs
----

The ``execute_job`` method of a queue is passed a ``Job`` object containing
the following attributes:

- ``id``
- ``queue``
- ``method``
- ``args``
- ``cursor``

As a convenience, there is an ``extend(**kw)`` method which can be used to
add extra attributes to the object. This is useful in individual queues to
define a contract between a queue and its methods.

Cursors
-------

A ``Job`` can be scheduled with a ``cursor_key``. There can only be one
pending job and one running job for any cursor. New jobs scheduled while
another one is pending will be ignored and the pending job is returned.

A ``job.cursor`` dict is provided to the workers containing the cursor data,
and is saved back to the database when the job is completed. This effectively
gives jobs some persistent, shared state, and serializes all jobs over a given
cursor.

Scheduled Jobs
--------------

A ``Job`` can be scheduled in the future by providing a ``datetime`` object
to the ``when`` argument. This, along with a cursor key, can provide a nice
throttle on how frequently a job runs. For example, schedule jobs to run in
30 seconds with a ``cursor_key`` and any jobs that are scheduled in the
meantime will be dropped. The assumption here is that the arguments are
constant and data to continue execute is in the cursor or another table.

Example Worker
==============

.. code-block:: python

    from psycopg2_mq import (
        MQWorker,
        make_default_model,
    )
    from sqlalchemy import (
        MetaData,
        create_engine,
    )
    import sys

    class EchoQueue:
        def execute_job(self, job):
            return f'hello, {job.args["name"]} from method="{job.method}"'

    if __name__ == '__main__':
        engine = create_engine(sys.argv[1])
        metadata = MetaData()
        model = make_default_model(metadata)
        worker = MQWorker(
            engine=engine,
            queues={
                'echo': EchoQueue(),
            },
            model=model,
        )
        worker.run()

Example Source
==============

.. code-block:: python

    engine = create_engine()
    metadata = MetaData()
    model = make_default_model(metadata)
    session_factory = sessionmaker()
    session_factory.configure(bind=engine)

    dbsession = session_factory()
    with dbsession.begin():
      mq = MQSource(
          dbsession=dbsession,
          model=model,
      )
      job = mq.call('echo', 'hello', {'name': 'Andy'})
      print(f'queued job={job.id}')


0.4 (2019-10-28)
================

- Add a ``worker`` column to the ``Job`` model to track what worker
  is handling a job.

- Add an optional ``name`` argument to ``MQWorker`` to name the worker -
  the value will be recorded in each job.

- Add a ``threads`` argument (default=``1``) to ``MQWorker`` to support
  handling multiple jobs from the same worker instance instead of making a
  worker per thread.

- Add ``capture_signals`` argument (default=``True``) to ``MQWorker`` which
  will capture ``SIGTERM``, ``SIGINT`` and ``SIGUSR1``. The first two will
  trigger graceful shutdown - they will make the process stop handling new
  jobs while finishing active jobs. The latter will dump to ``stderr`` a
  JSON dump of the current status of the worker.

0.3.3 (2019-10-23)
==================

- Only save a cursor update if the job is completed successfully.

0.3.2 (2019-10-22)
==================

- Mark lost jobs during timeouts instead of just when a worker starts in order
  to catch them earlier.

0.3.1 (2019-10-17)
==================

- When attempting to schedule a job with a cursor and a ``scheduled_time``
  earlier than a pending job on the same cursor, the job will be updated to
  run at the earlier time.

- When attempting to schedule a job with a cursor and a pending job already
  exists on the same cursor, a ``conflict_resolver`` function may be
  supplied to ``MQSource.call`` to update the job properties, merging the
  arguments however the user wishes.

0.3 (2019-10-15)
================

- Add a new column ``cursor_snapshot`` to the ``Job`` model which will
  contain the value of the cursor when the job begins.

0.2 (2019-10-09)
================

- Add cursor support for jobs. This requires a schema migration to add
  a ``cursor_key`` column, a new ``JobCursor`` model, and some new indices.

0.1.6 (2019-10-07)
==================

- Support passing custom kwargs to the job in ``psycopg2_mq.MQSource.call``
  to allow custom columns on the job table.

0.1.5 (2019-05-17)
==================

- Fix a regression when serializing errors with strings or cycles.

0.1.4 (2019-05-09)
==================

- More safely serialize exception objects when jobs fail.

0.1.3 (2018-09-04)
==================

- Rename the thread to contain the job id while it's handling a job.

0.1.2 (2018-09-04)
==================

- Rename ``Job.params`` to ``Job.args``.

0.1.1 (2018-09-04)
==================

- Make ``psycopg2`` an optional dependency in order to allow apps to depend
  on ``psycopg2-binary`` if they wish.

0.1 (2018-09-04)
================

- Initial release.


