Introduction

------------

The pprocess module provides elementary support for parallel programming in

Python using a fork-based process creation model in conjunction with a

channel-based communications model implemented using socketpair and poll. On

systems with multiple CPUs or multicore CPUs, processes should take advantage

of as many CPUs or cores as the operating system permits.

Tutorial

--------

The tutorial provides some information about the examples described below.

See the docs/tutorial.html file in the distribution for more details.

Reference

---------

A description of the different mechanisms provided by the pprocess module can

be found in the reference document. See the docs/reference.html file in the

distribution for more details.

Quick Start

-----------

Try running the simple examples. For example:

PYTHONPATH=. python examples/simple_create.py

(These examples show in different ways how limited number of processes can be

used to perform a parallel computation. The simple.py, simple1.py, simple2.py

and simple_map.py programs are sequential versions of the other programs.)

The following table summarises the features used in the programs:

Program (.py)         pmap  MakeParallel manage start create Map Queue Exchange

-------------         ----  ------------ ------ ----- ------ --- ----- --------

simple_create_map                                     Yes    Yes

simple_create_queue                                   Yes        Yes

simple_create                                         Yes              Yes

simple_managed_map          Yes          Yes                 Yes

simple_managed_queue        Yes          Yes                     Yes

simple_managed              Yes          Yes                           Yes

simple_pmap           Yes

simple_start_queue          Yes                 Yes              Yes

simple_start                                    Yes                    Yes

The simplest parallel program is simple_pmap.py which employs the pmap

function resembling the built-in map function in Python.

Other simple programs are those employing the Queue class, together with those

using the manage method which associates functions or callables with Queue or

Exchange objects for convenient invocation of those functions and the

management of their communications.

The most technically involved program is simple_start.py which uses the

Exchange class together with a calculation function which is aware of the

parallel environment and which communicates over the supplied communications

channel directly to the creating process.

It should be noted that with the exception of simple_start.py, those examples

employing calculation functions (as opposed to doing a calculation inline in a

loop body) all use MakeParallel to make those functions parallel-aware, thus

permitting the conversion of "normal" functions to a form usable in the

parallel environment.

Reusable Processes

------------------

An additional example not listed above, simple_managed_map_reusable.py,

employs the MakeReusable class instead of MakeParallel in order to demonstrate

reusable processes and channels:

PYTHONPATH=. python examples/simple_managed_map_reusable.py

Persistent Processes

--------------------

A number of persistent variants of some of the above examples employ a

persistent or background process which can be started by one process and

contacted later by another in order to collect the results of a computation.

For example:

PYTHONPATH=. python examples/simple_persistent_managed.py --start

PYTHONPATH=. python examples/simple_persistent_managed.py --reconnect

PYTHONPATH=. python examples/simple_background_queue.py --start

PYTHONPATH=. python examples/simple_background_queue.py --reconnect

PYTHONPATH=. python examples/simple_persistent_queue.py --start

PYTHONPATH=. python examples/simple_persistent_queue.py --reconnect

Parallel Raytracing with PyGmy

------------------------------

The PyGmy raytracer modified to use pprocess can be run to investigate the

potential for speed increases in "real world" programs:

cd examples/PyGmy

PYTHONPATH=../..:. python scene.py

(This should produce a file called test.tif - a TIFF file containing a

raytraced scene image.)

Test Programs

-------------

There are some elementary tests:

PYTHONPATH=. python tests/create_loop.py

PYTHONPATH=. python tests/start_loop.py

(Simple loop demonstrations which use two different ways of creating and

starting the parallel processes.)

PYTHONPATH=. python tests/start_indexer.py <directory>

(A text indexing demonstration, where <directory> should be a directory

containing text files to be indexed, although HTML files will also work well

enough. After indexing the files, a prompt will appear, words or word

fragments can be entered, and matching words and their locations will be

shown. Run the program without arguments to see more information.)

Contact, Copyright and Licence Information

------------------------------------------

The current Web page for pprocess at the time of release is:

http://www.boddie.org.uk/python/pprocess.html

The author can be contacted at the following e-mail address:

paul@boddie.org.uk

Copyright and licence information can be found in the docs directory - see

docs/COPYING.txt, docs/lgpl-3.0.txt and docs/gpl-3.0.txt for more information.

For the PyGmy raytracer example, different copyright and licence information

is provided in the docs directory - see docs/COPYING-PyGmy.txt and

docs/LICENCE-PyGmy.txt for more information.

Dependencies

------------

This software depends on standard library features which are stated as being

available only on "UNIX"; it has only been tested on a GNU/Linux system.

New in pprocess 0.4 (Changes since pprocess 0.3.1)

--------------------------------------------------

  * Added support for persistent/background processes.

  * Added a utility function to detect and return the number of processor

    cores available.

  * Added missing documentation stylesheet.

New in pprocess 0.3.1 (Changes since pprocess 0.3)

--------------------------------------------------

  * Moved the reference material out of the module docstring and into a

    separate document, converting it to XHTML in the process.

  * Fixed the project name in the setup script.

New in pprocess 0.3 (Changes since parallel 0.2.5)

--------------------------------------------------

  * Added managed callables: wrappers around callables which cause them to be

    automatically managed by the exchange from which they were acquired.

  * Added MakeParallel: a wrapper instantiated around a normal function which

    sends the result of that function over the supplied channel when invoked.

  * Added MakeReusable: a wrapper like MakeParallel which can be used in

    conjunction with the newly-added reuse capability of the Exchange class in

    order to reuse processes and channels.

  * Added a Map class which attempts to emulate the built-in map function,

    along with a pmap function using this class.

  * Added a Queue class which provides a simpler iterator-style interface to

    data produced by created processes.

  * Added a create method to the Exchange class and an exit convenience

    function to the module.

  * Changed the Exchange implementation to not block when attempting to start

    new processes beyond the process limit: such requests are queued and

    performed as running processes are completed. This permits programs using

    the start method to proceed to consumption of results more quickly.

  * Extended and updated the examples. Added a tutorial.

  * Added Ubuntu Feisty (7.04) package support.

New in parallel 0.2.5 (Changes since parallel 0.2.4)

----------------------------------------------------

  * Added a start method to the Exchange class for more convenient creation of

    processes.

  * Relicensed under the LGPL (version 3 or later) - this also fixes the

    contradictory situation where the GPL was stated in the pprocess module

    (which was not, in fact, the intention) and the LGPL was stated in the

    documentation.

New in parallel 0.2.4 (Changes since parallel 0.2.3)

----------------------------------------------------

  * Set buffer sizes to zero for the file object wrappers around sockets: this

    may prevent deadlock issues.

New in parallel 0.2.3 (Changes since parallel 0.2.2)

----------------------------------------------------

  * Added convenient message exchanges, offering methods handling common

    situations at the cost of having to define a subclass of Exchange.

  * Added a simple example of performing a parallel computation.

  * Improved the PyGmy raytracer example to use the newly added functionality.

New in parallel 0.2.2 (Changes since parallel 0.2.1)

----------------------------------------------------

  * Changed the status testing in the Exchange class, potentially fixing the

    premature closure of channels before all data was read.

  * Fixed the PyGmy raytracer example's process accounting by relying on the

    possibly more reliable Exchange behaviour, whilst also preventing

    erroneous creation of "out of bounds" processes.

  * Added a removed attribute on the Exchange to record which channels were

    removed in the last call to the ready method.

New in parallel 0.2.1 (Changes since parallel 0.2)

--------------------------------------------------

  * Added a PyGmy raytracer example.

  * Updated copyright and licensing details (FSF address, additional works).

New in parallel 0.2 (Changes since parallel 0.1)

------------------------------------------------

  * Changed the name of the included module from parallel to pprocess in order

    to avoid naming conflicts with PyParallel.

Release Procedures

------------------

Update the pprocess __version__ attribute.

Change the version number and package filename/directory in the documentation.

Update the release notes (see above).

Check the release information in the PKG-INFO file.

Tag, export.

Archive, upload.

Update PyPI.

Making Packages

---------------

To make Debian-based packages:

  1. Create new package directories under packages if necessary.

  2. Make a symbolic link in the distribution's root directory to keep the

     Debian tools happy:

     ln -s packages/ubuntu-hoary/python2.4-parallel-pprocess/debian/

     Or:

     ln -s packages/ubuntu-feisty/python-pprocess/debian/

  3. Run the package builder:

     dpkg-buildpackage -rfakeroot

  4. Locate and tidy up the packages in the parent directory of the

     distribution's root directory.