1 Introduction
2 ------------
3
4 The pprocess module provides elementary support for parallel programming in
5 Python using a fork-based process creation model in conjunction with a
6 channel-based communications model implemented using socketpair and poll. On
7 systems with multiple CPUs or multicore CPUs, processes should take advantage
8 of as many CPUs or cores as the operating system permits.
9
10 Tutorial
11 --------
12
13 The tutorial provides some information about the examples described below.
14 See the docs/tutorial.html file in the distribution for more details.
15
16 Reference
17 ---------
18
19 A description of the different mechanisms provided by the pprocess module can
20 be found in the reference document. See the docs/reference.html file in the
21 distribution for more details.
22
23 Quick Start
24 -----------
25
26 Try running the simple examples. For example:
27
28 PYTHONPATH=. python examples/simple_create.py
29
30 (These examples show in different ways how limited number of processes can be
31 used to perform a parallel computation. The simple.py, simple1.py, simple2.py
32 and simple_map.py programs are sequential versions of the other programs.)
33
34 The following table summarises the features used in the programs:
35
36 Program (.py) pmap MakeParallel manage start create Map Queue Exchange
37 ------------- ---- ------------ ------ ----- ------ --- ----- --------
38 simple_create_map Yes Yes
39 simple_create_queue Yes Yes
40 simple_create Yes Yes
41 simple_managed_map Yes Yes Yes
42 simple_managed_queue Yes Yes Yes
43 simple_managed Yes Yes Yes
44 simple_pmap Yes
45 simple_pmap_iter Yes
46 simple_start_queue Yes Yes Yes
47 simple_start Yes Yes
48
49 The simplest parallel programs are simple_pmap.py and simple_pmap_iter.py
50 which employ the pmap function resembling the built-in map function in
51 Python.
52
53 Other simple programs are those employing the Queue class, together with those
54 using the manage method which associates functions or callables with Queue or
55 Exchange objects for convenient invocation of those functions and the
56 management of their communications.
57
58 The most technically involved program is simple_start.py which uses the
59 Exchange class together with a calculation function which is aware of the
60 parallel environment and which communicates over the supplied communications
61 channel directly to the creating process.
62
63 It should be noted that with the exception of simple_start.py, those examples
64 employing calculation functions (as opposed to doing a calculation inline in a
65 loop body) all use MakeParallel to make those functions parallel-aware, thus
66 permitting the conversion of "normal" functions to a form usable in the
67 parallel environment.
68
69 Reusable Processes
70 ------------------
71
72 An additional example not listed above, simple_managed_map_reusable.py,
73 employs the MakeReusable class instead of MakeParallel in order to demonstrate
74 reusable processes and channels:
75
76 PYTHONPATH=. python examples/simple_managed_map_reusable.py
77
78 Continuous Process Communications
79 ---------------------------------
80
81 Another example not listed above, simple_continuous_queue.py, employs
82 continuous communications to monitor output from created processes:
83
84 PYTHONPATH=. python examples/simple_continuous_queue.py
85
86 Persistent Processes
87 --------------------
88
89 A number of persistent variants of some of the above examples employ a
90 persistent or background process which can be started by one process and
91 contacted later by another in order to collect the results of a computation.
92 For example:
93
94 PYTHONPATH=. python examples/simple_persistent_managed.py --start
95 PYTHONPATH=. python examples/simple_persistent_managed.py --reconnect
96
97 PYTHONPATH=. python examples/simple_background_queue.py --start
98 PYTHONPATH=. python examples/simple_background_queue.py --reconnect
99
100 PYTHONPATH=. python examples/simple_persistent_queue.py --start
101 PYTHONPATH=. python examples/simple_persistent_queue.py --reconnect
102
103 Parallel Raytracing with PyGmy
104 ------------------------------
105
106 The PyGmy raytracer modified to use pprocess can be run to investigate the
107 potential for speed increases in "real world" programs:
108
109 cd examples/PyGmy
110 PYTHONPATH=../..:. python scene.py
111
112 (This should produce a file called test.tif - a TIFF file containing a
113 raytraced scene image.)
114
115 Examples from the Concurrency SIG
116 ---------------------------------
117
118 PYTHONPATH=. python examples/concurrency-sig/bottles.py
119 PYTHONPATH=. python examples/concurrency-sig/bottles_heartbeat.py
120
121 Test Programs
122 -------------
123
124 There are some elementary tests:
125
126 PYTHONPATH=. python tests/create_loop.py
127 PYTHONPATH=. python tests/start_loop.py
128
129 (Simple loop demonstrations which use two different ways of creating and
130 starting the parallel processes.)
131
132 PYTHONPATH=. python tests/start_indexer.py <directory>
133
134 (A text indexing demonstration, where <directory> should be a directory
135 containing text files to be indexed, although HTML files will also work well
136 enough. After indexing the files, a prompt will appear, words or word
137 fragments can be entered, and matching words and their locations will be
138 shown. Run the program without arguments to see more information.)
139
140 Contact, Copyright and Licence Information
141 ------------------------------------------
142
143 The current Web page for pprocess at the time of release is:
144
145 http://www.boddie.org.uk/python/pprocess.html
146
147 The author can be contacted at the following e-mail address:
148
149 paul@boddie.org.uk
150
151 Copyright and licence information can be found in the docs directory - see
152 docs/COPYING.txt, docs/lgpl-3.0.txt and docs/gpl-3.0.txt for more information.
153
154 For the PyGmy raytracer example, different copyright and licence information
155 is provided in the docs directory - see docs/COPYING-PyGmy.txt and
156 docs/LICENCE-PyGmy.txt for more information.
157
158 Dependencies
159 ------------
160
161 This software depends on standard library features which are stated as being
162 available only on "UNIX"; it has only been tested repeatedly on a GNU/Linux
163 system, and occasionally on systems running OpenSolaris.
164
165 New in pprocess 0.4.1 (Changes since pprocess 0.4)
166 --------------------------------------------------
167
168 * Fixed the get_number_of_cores function to work with /proc/cpuinfo where
169 the "physical id" field is missing.
170 * Changed the Map class to permit incremental access to received results
171 from completed parts of the sequence of inputs, also adding an iteration
172 interface.
173 * Added an example, simple_pmap_iter.py, to demonstrate iteration over maps.
174 * Added proper support in the Exchange class for continuous communications
175 between processes.
176
177 New in pprocess 0.4 (Changes since pprocess 0.3.1)
178 --------------------------------------------------
179
180 * Added support for persistent/background processes.
181 * Added a utility function to detect and return the number of processor
182 cores available.
183 * Added missing documentation stylesheet.
184 * Added support for Solaris using pipes instead of socket pairs, since
185 the latter do not apparently work properly with poll on Solaris.
186
187 New in pprocess 0.3.1 (Changes since pprocess 0.3)
188 --------------------------------------------------
189
190 * Moved the reference material out of the module docstring and into a
191 separate document, converting it to XHTML in the process.
192 * Fixed the project name in the setup script.
193
194 New in pprocess 0.3 (Changes since parallel 0.2.5)
195 --------------------------------------------------
196
197 * Added managed callables: wrappers around callables which cause them to be
198 automatically managed by the exchange from which they were acquired.
199 * Added MakeParallel: a wrapper instantiated around a normal function which
200 sends the result of that function over the supplied channel when invoked.
201 * Added MakeReusable: a wrapper like MakeParallel which can be used in
202 conjunction with the newly-added reuse capability of the Exchange class in
203 order to reuse processes and channels.
204 * Added a Map class which attempts to emulate the built-in map function,
205 along with a pmap function using this class.
206 * Added a Queue class which provides a simpler iterator-style interface to
207 data produced by created processes.
208 * Added a create method to the Exchange class and an exit convenience
209 function to the module.
210 * Changed the Exchange implementation to not block when attempting to start
211 new processes beyond the process limit: such requests are queued and
212 performed as running processes are completed. This permits programs using
213 the start method to proceed to consumption of results more quickly.
214 * Extended and updated the examples. Added a tutorial.
215 * Added Ubuntu Feisty (7.04) package support.
216
217 New in parallel 0.2.5 (Changes since parallel 0.2.4)
218 ----------------------------------------------------
219
220 * Added a start method to the Exchange class for more convenient creation of
221 processes.
222 * Relicensed under the LGPL (version 3 or later) - this also fixes the
223 contradictory situation where the GPL was stated in the pprocess module
224 (which was not, in fact, the intention) and the LGPL was stated in the
225 documentation.
226
227 New in parallel 0.2.4 (Changes since parallel 0.2.3)
228 ----------------------------------------------------
229
230 * Set buffer sizes to zero for the file object wrappers around sockets: this
231 may prevent deadlock issues.
232
233 New in parallel 0.2.3 (Changes since parallel 0.2.2)
234 ----------------------------------------------------
235
236 * Added convenient message exchanges, offering methods handling common
237 situations at the cost of having to define a subclass of Exchange.
238 * Added a simple example of performing a parallel computation.
239 * Improved the PyGmy raytracer example to use the newly added functionality.
240
241 New in parallel 0.2.2 (Changes since parallel 0.2.1)
242 ----------------------------------------------------
243
244 * Changed the status testing in the Exchange class, potentially fixing the
245 premature closure of channels before all data was read.
246 * Fixed the PyGmy raytracer example's process accounting by relying on the
247 possibly more reliable Exchange behaviour, whilst also preventing
248 erroneous creation of "out of bounds" processes.
249 * Added a removed attribute on the Exchange to record which channels were
250 removed in the last call to the ready method.
251
252 New in parallel 0.2.1 (Changes since parallel 0.2)
253 --------------------------------------------------
254
255 * Added a PyGmy raytracer example.
256 * Updated copyright and licensing details (FSF address, additional works).
257
258 New in parallel 0.2 (Changes since parallel 0.1)
259 ------------------------------------------------
260
261 * Changed the name of the included module from parallel to pprocess in order
262 to avoid naming conflicts with PyParallel.
263
264 Release Procedures
265 ------------------
266
267 Update the pprocess __version__ attribute and the setup.py file version field.
268 Change the version number and package filename/directory in the documentation.
269 Update the release notes (see above).
270 Check the release information in the PKG-INFO file.
271 Tag, export.
272 Archive, upload.
273 Update PyPI.
274
275 Making Packages
276 ---------------
277
278 To make Debian-based packages:
279
280 1. Create new package directories under packages if necessary.
281 2. Make a symbolic link in the distribution's root directory to keep the
282 Debian tools happy:
283
284 ln -s packages/ubuntu-hoary/python2.4-parallel-pprocess/debian/
285
286 Or:
287
288 ln -s packages/ubuntu-feisty/python-pprocess/debian/
289
290 3. Run the package builder:
291
292 dpkg-buildpackage -rfakeroot
293
294 4. Locate and tidy up the packages in the parent directory of the
295 distribution's root directory.