Metadata-Version: 2.1
Name: pycos
Version: 4.12.2
Summary: Concurrent, Asynchronous, Distributed, Communicating Tasks with Python
Home-page: https://pycos.org
Author: Giridhar Pemmasani
Author-email: pgiri@yahoo.com
License: Apache 2.0
Keywords: concurrency,asynchronous,network programming,distributed,tasks,message passing
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.1
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries
License-File: LICENSE

pycos
######

    .. note:: Full documentation for pycos is now available at `pycos.org
              <https://pycos.org>`_.

pycos is a Python framework for concurrent, asynchronous, network/distributed programming
and distributed / cloud computing, using *very* light weight
computational units called *tasks*. pycos tasks are created with generator functions similar to
the way threads are created with functions using Python's `threading module
<https://docs.python.org/2.7/library/threading.html>`_. Programs developed with pycos have **same
logic and structure** as programs with threads, except for a few syntactic changes - mostly using
*yield* with asynchronous completions that give control to pycos's scheduler, which interleaves
executions of generators, similar to the way an operating system executes multiple processes.

Unlike threads, creating tasks with pycos is very efficient (see below). Moreover, with pycos task
context switch occurs only when tasks use *yield* (typically with an asynchronous call), so there
is no need for locking and there is no overhead of unnecessary context switches.

Unlike with other asynchronous frameworks, programming with pycos is rather
straight forward: There are just 4 simple steps to convert programming
with threads to programming with pycos.

Features
--------

pycos features include:

* No callbacks or event loops! No need to lock critical sections either,

* Efficient polling mechanisms epoll, kqueue, /dev/poll, Windows
  I/O Completion Ports (IOCP) for high performance and
  scalability,

* Asynchronous (non-blocking) sockets and pipes, for concurrent
  processing of I/O,

* SSL for security,

* Asynchronous locking primitives similar to Python threading module,

* Asynchronous timers and timeouts,

* `Message passing <http://en.wikipedia.org/wiki/Message_passing>`_
  for (local and remote) tasks to exchange messages one-to-one
  with `Message Queue Pattern
  <http://en.wikipedia.org/wiki/Message_queue>`_ or through
  broadcasting channels with `Publish-Subscribe Pattern
  <http://en.wikipedia.org/wiki/Publish/subscribe>`_,

* `Location transparency
  <http://en.wikipedia.org/wiki/Location_transparency>`_ with naming
  and locating (local and remote) resources,

* Remote Pico Service (RPS) for defining services that remote clients can run as tasks
  (with possibly message passing to communicate).

* Distributing computation components (code and data) for execution of
  distributed communicating processes, for wide range of use cases, covering
  `SIMD, MISD, MIMD <https://en.wikipedia.org/wiki/Flynn%27s_taxonomy>`_ system
  architectures at the process level; `in-memory processing
  <https://en.wikipedia.org/wiki/In-memory_processing>`_, data streaming,
  real-time (live) analytics and cloud computing are supported as well,

* `Web interface <https://pycos.org/dispycos.html#client-browser-interface>`_ to monitor
  cluster/application status/performance,

* Monitoring and restarting of (local or remote) tasks, for fault detection
  and fault-tolerance,

* Hot-swapping of task functions, for dynamic system reconfiguration.

* Thread pools with asynchronous task completions, for executing (external)
  synchronous tasks, such as reading standard input.

pycos works with Python 2.7+ and Python 3.1+ and tested on Linux, Mac OS X and Windows; it may
work on other platforms (e.g., FreeBSD and other BSD variants) too. pycos works with `PyPy
<https://pypy.org>`_ as well.

Dependencies
------------

pycos is implemented with standard modules in Python.

If `psutil <https://pypi.python.org/pypi/psutil>`_ is available on nodes, node
availability status (CPU, memory and disk) is sent in status messages, and shown
in web browser so node/application performance can be monitored.

Under Windows efficient polling notifier I/O Completion Ports (IOCP) is
supported only if `pywin32 <https://github.com/mhammond/pywin32>`_ is available;
otherwise, inefficient *select* notifier is used.

Installation
------------
To install pycos, run::

   python -m pip install pycos

Authors
-------
* Giridhar Pemmasani

Links
-----
* Documentation is at `pycos.org`_.
* `GitHub (Code Repository) <https://github.com/pgiri/pycos>`_.


