Merged plac 0.8.0 in the trunk

author: Michele Simionato <michele.simionato@gmail.com> 2011-02-16 10:50:26 +0100
committer: Michele Simionato <michele.simionato@gmail.com> 2011-02-16 10:50:26 +0100
commit: ff2c6f7791094f6f4e04393e9e038847a493fbce (patch)
tree: 9cc4c16a722ff2ca908c2723d6f51339e373425d
parent: fdd6d7c4d569c7efaf13d4c256369867c2dd8a5a (diff)
parent: 02d7e73ea41c57e0f1abe47cfda0cedad4a7c720 (diff)
download: micheles-ff2c6f7791094f6f4e04393e9e038847a493fbce.tar.gz
10 files changed, 2131 insertions, 1760 deletions
diff --git a/plac/CHANGES.txt b/plac/CHANGES.txt
index 9ff29f6..25608a7 100644
--- a/plac/CHANGES.txt
+++ b/plac/CHANGES.txt
@@ -1,6 +1,7 @@
 HISTORY
 ----------
 
+0.8.0 Added a monitor framework and a TkMonitor (2011-02-16)
 0.7.6 Fixed the error propagation in ``Interpreter.__exit__``.
       Added a note about commandline and marrow.script in the documentation
       (2011-01-13)
diff --git a/plac/doc/importer_ui.py b/plac/doc/importer_ui.py
index a4592b0..0a5cc9c 100644
--- a/plac/doc/importer_ui.py
+++ b/plac/doc/importer_ui.py
@@ -1,3 +1,4 @@
+from __future__ import with_statement
 from Tkinter import *
 from importer3 import FakeImporter
 
diff --git a/plac/doc/plac.html b/plac/doc/plac.html
index a81cf24..8dc043e 100644
--- a/plac/doc/plac.html
+++ b/plac/doc/plac.html
@@ -474,10 +474,11 @@ h1 tt, h2 tt, h3 tt, h4 tt, h5 tt, h6 tt {
 <li><a class="reference internal" href="#threaded-commands" id="id45">Threaded commands</a></li>
 <li><a class="reference internal" href="#running-commands-as-external-processes" id="id46">Running commands as external processes</a></li>
 <li><a class="reference internal" href="#managing-the-output-of-concurrent-commands" id="id47">Managing the output of concurrent commands</a></li>
-<li><a class="reference internal" href="#parallel-computing-with-plac" id="id48">Parallel computing with plac</a></li>
-<li><a class="reference internal" href="#the-plac-server" id="id49">The plac server</a></li>
-<li><a class="reference internal" href="#summary" id="id50">Summary</a></li>
-<li><a class="reference internal" href="#appendix-custom-annotation-objects" id="id51">Appendix: custom annotation objects</a></li>
+<li><a class="reference internal" href="#monitor-support" id="id48">Monitor support</a></li>
+<li><a class="reference internal" href="#parallel-computing-with-plac" id="id49">Parallel computing with plac</a></li>
+<li><a class="reference internal" href="#the-plac-server" id="id50">The plac server</a></li>
+<li><a class="reference internal" href="#summary" id="id51">Summary</a></li>
+<li><a class="reference internal" href="#appendix-custom-annotation-objects" id="id52">Appendix: custom annotation objects</a></li>
 </ul>
 </li>
 </ul>
@@ -2676,11 +2677,10 @@ task runs and more values are yielded. Accessing the <tt class="docutils literal
 nonblocking and can be done freely.
 Finally there is a <tt class="docutils literal">.result</tt>
 property which waits for the task to finish and returns the last yielded
-value or raises an exception.</p>
-<p>Here is some example code to visualize the output of the FakeImporter
-in Tkinter (I chose Tkinter because it is easy to use and it is
-in the standard library, but you can use any GUI):</p>
+value or raises an exception. The code below provides an example of
+how you could implement a GUI over the importer example:</p>
 <pre class="literal-block">
+from __future__ import with_statement
 from Tkinter import *
 from importer3 import FakeImporter
 
@@ -2713,8 +2713,47 @@ if __name__ == '__main__':
 
 </pre>
 </div>
+<div class="section" id="monitor-support">
+<h2><a class="toc-backref" href="#id48">Monitor support</a></h2>
+<p>Starting from release 0.8 <a class="reference external" href="http://pypi.python.org/pypi/plac">plac</a> provides builtin support for monitoring the
+output of concurrent commands, at least for platforms where multiprocessing
+is fully supported. You can define your own monitor
+class, simply by inheriting from <tt class="docutils literal">plac.Monitor</tt> and by
+overriding the methods <tt class="docutils literal">add_listener(self, no)</tt>,
+<tt class="docutils literal">del_listener(self, taskno)</tt>, <tt class="docutils literal">notify_listener(self, taskno, msg)</tt>,
+<tt class="docutils literal">schedule(self, seconds, func, arg)</tt> and <tt class="docutils literal">run(self)</tt>.
+Then, you can a monitor object to any <tt class="docutils literal">plac.Interpreter</tt> object
+by simply calling the <tt class="docutils literal">add_monitor</tt> method.
+For convenience,
+<tt class="docutils literal">plac</tt> comes with a very simple <tt class="docutils literal">TkMonitor</tt> based on Tkinter
+(I chose Tkinter because it is easy to use and it is
+in the standard library, but you can use any GUI): you can just
+look at how the <tt class="docutils literal">TkMonitor</tt> is implemented in <tt class="docutils literal">plac_tk.py</tt>
+and adapt it. Here is an example of usage of the <tt class="docutils literal">TkMonitor</tt>:</p>
+<pre class="literal-block">
+from __future__ import with_statement
+import plac
+
+class Hello(object):
+    mpcommands = ['hello']
+    def hello(self):
+        yield 'hello'
+
+if __name__ == '__main__':
+    i = plac.Interpreter(Hello())
+    i.add_monitor(plac.TkMonitor('tkmon'))
+    with i:
+        i.interact()
+        
+
+</pre>
+<p>Try to give the <tt class="docutils literal">hello</tt> command from the interactive interpreter:
+each time a new text widget will be added displaying the output
+of the command. Notice that if <tt class="docutils literal">Tkinter</tt> is not installed correctly
+on your system the <tt class="docutils literal">TkMonitor</tt> class will not be available.</p>
+</div>
 <div class="section" id="parallel-computing-with-plac">
-<h2><a class="toc-backref" href="#id48">Parallel computing with plac</a></h2>
+<h2><a class="toc-backref" href="#id49">Parallel computing with plac</a></h2>
 <p><a class="reference external" href="http://pypi.python.org/pypi/plac">plac</a> is certainly not intended as a tool for parallel computing, but
 still you can use it to launch a set of commands and to collect the
 results, similarly to the MapReduce pattern popularized by
@@ -2836,7 +2875,7 @@ $ python picalculator.py -mS 10000000 # sequential
 mode is some 20% slower than the sequential mode.</p>
 <p>Since the pattern submit a bunch of tasks, starts them and collect the
 results is so common, <a class="reference external" href="http://pypi.python.org/pypi/plac">plac</a> provides an utility function
-<tt class="docutils literal">runp(genseq, <span class="pre">mode='p',</span> start=True)</tt> to start
+<tt class="docutils literal">runp(genseq, <span class="pre">mode='p',</span> <span class="pre">monitors=(),</span> start=True)</tt> to start
 a bunch a generators and return a list of task objects. By default
 <tt class="docutils literal">runp</tt> use processes, but you can use threads by passing <tt class="docutils literal"><span class="pre">mode='t'</span></tt>.
 If you do not wont to start the tasks, you can say so (<tt class="docutils literal">start=False</tt>).
@@ -2844,9 +2883,12 @@ With <tt class="docutils literal">runp</tt> the parallel pi calculation becomes
 <pre class="literal-block">
 sum(task.result for task in plac.runp(calc_pi(N) for i in range(ncpus)))/ncpus
 </pre>
+<p>The file <tt class="docutils literal">test_runp</tt> in the <tt class="docutils literal">doc</tt> directory of the plac distribution
+shows another couple of examples of usage, including how to show the
+results of the running computation on a <tt class="docutils literal">TkMonitor</tt>.</p>
 </div>
 <div class="section" id="the-plac-server">
-<h2><a class="toc-backref" href="#id49">The plac server</a></h2>
+<h2><a class="toc-backref" href="#id50">The plac server</a></h2>
 <p>A command-line oriented interface can be easily converted into a
 socket-based interface. Starting from release 0.7 plac features
 a builtin server which is able to accept commands from multiple
@@ -2892,7 +2934,7 @@ Connection closed by foreign host.
 </pre>
 </div>
 <div class="section" id="summary">
-<h2><a class="toc-backref" href="#id50">Summary</a></h2>
+<h2><a class="toc-backref" href="#id51">Summary</a></h2>
 <p>Once <a class="reference external" href="http://pypi.python.org/pypi/plac">plac</a> claimed to be the easiest command-line arguments parser
 in the world. Having read this document you may think that it is not
 so easy after all. But it is a false impression. Actually the
@@ -2918,7 +2960,7 @@ given port number (default 2199)</li>
 </div>
 <hr class="docutils" />
 <div class="section" id="appendix-custom-annotation-objects">
-<h2><a class="toc-backref" href="#id51">Appendix: custom annotation objects</a></h2>
+<h2><a class="toc-backref" href="#id52">Appendix: custom annotation objects</a></h2>
 <p>Internally <a class="reference external" href="http://pypi.python.org/pypi/plac">plac</a> uses an <tt class="docutils literal">Annotation</tt> class to convert the tuples
 in the function signature into annotation objects, i.e. objects with
 six attributes <tt class="docutils literal">help, kind, short, type, choices, metavar</tt>.</p>
diff --git a/plac/doc/plac.pdf b/plac/doc/plac.pdf
index 04d9797..b2652b5 100644
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+++ b/plac/doc/plac.pdf
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 1 0 0 1 0 255 cm
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-BT 1 0 0 1 20 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (Plac batch scripts) Tj T* ET
+BT 1 0 0 1 20 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (Implementing subcommands) Tj T* ET
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+BT 1 0 0 1 20 2 Tm 12 TL /F1 10 Tf 0 0 .501961 rg (plac.Interpreter.call) Tj T* ET
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-BT 1 0 0 1 0 98 Tm 1.174751 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (plac ) Tj 0 0 0 rg (is certainly not intended as a tool for parallel computing, but still you can use it to launch a set of) Tj T* 0 Tw .497984 Tw (commands and to collect the results, similarly to the MapReduce pattern popularized by Google. In order) Tj T* 0 Tw .669431 Tw (to give an example, I will consider the "Hello World" of parallel computing, i.e. the computation of pi with) Tj T* 0 Tw .537633 Tw (independent processes. There is a huge number of algorithms to compute pi; here I will describe a trivial) Tj T* 0 Tw .101567 Tw (one chosen for simplicity, not per efficienty. The trick is to consider the first quadrant of a circle with radius) Tj T* 0 Tw .602488 Tw (1 and to extract a number of points ) Tj /F3 10 Tf (\(x, y\) ) Tj /F1 10 Tf (with ) Tj /F3 10 Tf (x ) Tj /F1 10 Tf (and ) Tj /F3 10 Tf (y ) Tj /F1 10 Tf (random variables in the interval ) Tj /F3 10 Tf ([0,1]) Tj /F1 10 Tf (. The) Tj T* 0 Tw .928876 Tw (probability of extracting a number inside the quadrant \(i.e. with ) Tj /F3 10 Tf (x^2 + y^2 < 1) Tj /F1 10 Tf (\) is proportional to the) Tj T* 0 Tw .433145 Tw (area of the quadrant \(i.e. ) Tj /F3 10 Tf (pi/4) Tj /F1 10 Tf (\). The value of ) Tj /F3 10 Tf (pi ) Tj /F1 10 Tf (therefore can be extracted by multiplying by 4 the ratio) Tj T* 0 Tw (between the number of points in the quadrant versus the total number of points ) Tj /F3 10 Tf (N) Tj /F1 10 Tf (, for ) Tj /F3 10 Tf (N ) Tj /F1 10 Tf (large:) Tj T* ET
+BT 1 0 0 1 0 98 Tm .493555 Tw 12 TL /F1 10 Tf 0 0 0 rg (Starting from release 0.8 ) Tj 0 0 .501961 rg (plac ) Tj 0 0 0 rg (provides builtin support for monitoring the output of concurrent commands,) Tj T* 0 Tw 1.277318 Tw (at least for platforms where multiprocessing is fully supported. You can define your own monitor class,) Tj T* 0 Tw .839979 Tw (simply by inheriting from ) Tj /F3 10 Tf (plac.Monitor ) Tj /F1 10 Tf (and by overriding the methods ) Tj /F3 10 Tf (add_listener\(self, no\)) Tj /F1 10 Tf (,) Tj T* 0 Tw 2.953953 Tw /F3 10 Tf (del_listener\(self, taskno\)) Tj /F1 10 Tf (, ) Tj /F3 10 Tf (notify_listener\(self, taskno, msg\)) Tj /F1 10 Tf (, ) Tj /F3 10 Tf (schedule\(self,) Tj T* 0 Tw .367674 Tw (seconds, func, arg\) ) Tj /F1 10 Tf (and ) Tj /F3 10 Tf (run\(self\)) Tj /F1 10 Tf (. Then, you can a monitor object to any ) Tj /F3 10 Tf (plac.Interpreter) Tj T* 0 Tw 1.149983 Tw /F1 10 Tf (object by simply calling the ) Tj /F3 10 Tf (add_monitor ) Tj /F1 10 Tf (method. For convenience, ) Tj /F3 10 Tf (plac ) Tj /F1 10 Tf (comes with a very simple) Tj T* 0 Tw .82683 Tw /F3 10 Tf (TkMonitor ) Tj /F1 10 Tf (based on Tkinter \(I chose Tkinter because it is easy to use and it is in the standard library,) Tj T* 0 Tw .08332 Tw (but you can use any GUI\): you can just look at how the ) Tj /F3 10 Tf (TkMonitor ) Tj /F1 10 Tf (is implemented in ) Tj /F3 10 Tf (plac_tk.py ) Tj /F1 10 Tf (and) Tj T* 0 Tw (adapt it. Here is an example of usage of the ) Tj /F3 10 Tf (TkMonitor) Tj /F1 10 Tf (:) Tj T* ET
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+BT 1 0 0 1 0 146 Tm /F3 10 Tf 12 TL (from __future__ import with_statement) Tj T* (import plac) Tj T*  T* (class Hello\(object\):) Tj T* (    mpcommands = ['hello']) Tj T* (    def hello\(self\):) Tj T* (        yield 'hello') Tj T*  T* (if __name__ == '__main__':) Tj T* (    i = plac.Interpreter\(Hello\(\)\)) Tj T* (    i.add_monitor\(plac.TkMonitor\('tkmon'\)\)) Tj T* (    with i:) Tj T* (        i.interact\(\)) Tj T* ET
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-BT 1 0 0 1 0 50 Tm /F1 10 Tf 12 TL .046654 Tw (The algorithm is trivially parallelizable: if you have n CPUs, you can compute pi n times with N/n iterations,) Tj T* 0 Tw 1.122488 Tw (sum the results and divide the total by n. I have a Macbook with two cores, therefore I would expect a) Tj T* 0 Tw 2.347984 Tw (speedup factor of 2 with respect to a sequential computation. Moreover, I would expect a threaded) Tj T* 0 Tw 2.827984 Tw (computation to be even slower than a sequential computation, due to the GIL and the scheduling) Tj T* 0 Tw (overhead.) Tj T* ET
+BT 1 0 0 1 0 26 Tm 1.657633 Tw 12 TL /F1 10 Tf 0 0 0 rg (Try to give the ) Tj /F3 10 Tf (hello ) Tj /F1 10 Tf (command from the interactive interpreter: each time a new text widget will be) Tj T* 0 Tw 1.321235 Tw (added displaying the output of the command. Notice that if ) Tj /F3 10 Tf (Tkinter ) Tj /F1 10 Tf (is not installed correctly on your) Tj T* 0 Tw (system the ) Tj /F3 10 Tf (TkMonitor ) Tj /F1 10 Tf (class will not be available.) Tj T* ET
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-1 0 0 1 62.69291 368.6236 cm
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-BT 1 0 0 1 0 14 Tm .313984 Tw 12 TL /F1 10 Tf 0 0 0 rg (Here is a script implementing the algorithm and working in three different modes \(parallel mode, threaded) Tj T* 0 Tw (mode and sequential mode\) depending on a ) Tj /F3 10 Tf (mode ) Tj /F1 10 Tf (option:) Tj T* ET
+BT 1 0 0 1 0 3 Tm 18 TL /F2 15 Tf 0 0 0 rg (Parallel computing with plac) Tj T* ET
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+BT 1 0 0 1 0 98 Tm 1.174751 Tw 12 TL /F1 10 Tf 0 0 .501961 rg (plac ) Tj 0 0 0 rg (is certainly not intended as a tool for parallel computing, but still you can use it to launch a set of) Tj T* 0 Tw .497984 Tw (commands and to collect the results, similarly to the MapReduce pattern popularized by Google. In order) Tj T* 0 Tw .669431 Tw (to give an example, I will consider the "Hello World" of parallel computing, i.e. the computation of pi with) Tj T* 0 Tw .537633 Tw (independent processes. There is a huge number of algorithms to compute pi; here I will describe a trivial) Tj T* 0 Tw .101567 Tw (one chosen for simplicity, not per efficienty. The trick is to consider the first quadrant of a circle with radius) Tj T* 0 Tw .602488 Tw (1 and to extract a number of points ) Tj /F3 10 Tf (\(x, y\) ) Tj /F1 10 Tf (with ) Tj /F3 10 Tf (x ) Tj /F1 10 Tf (and ) Tj /F3 10 Tf (y ) Tj /F1 10 Tf (random variables in the interval ) Tj /F3 10 Tf ([0,1]) Tj /F1 10 Tf (. The) Tj T* 0 Tw .928876 Tw (probability of extracting a number inside the quadrant \(i.e. with ) Tj /F3 10 Tf (x^2 + y^2 < 1) Tj /F1 10 Tf (\) is proportional to the) Tj T* 0 Tw .433145 Tw (area of the quadrant \(i.e. ) Tj /F3 10 Tf (pi/4) Tj /F1 10 Tf (\). The value of ) Tj /F3 10 Tf (pi ) Tj /F1 10 Tf (therefore can be extracted by multiplying by 4 the ratio) Tj T* 0 Tw (between the number of points in the quadrant versus the total number of points ) Tj /F3 10 Tf (N) Tj /F1 10 Tf (, for ) Tj /F3 10 Tf (N ) Tj /F1 10 Tf (large:) Tj T* ET
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-BT 1 0 0 1 0 242 Tm 12 TL /F3 10 Tf 0 0 0 rg (from __future__ import with_statement) Tj T* (from random import random) Tj T* (import multiprocessing) Tj T* (import plac) Tj T*  T* (class PiCalculator\(object\):) Tj T* (    """Compute pi in parallel with threads or processes""") Tj T* (    ) Tj T* (    @plac.annotations\() Tj T* (        npoints=\('number of integration points', 'positional', None, int\),) Tj T* (        mode=\('sequential|parallel|threaded', 'option', 'm', str, 'SPT'\)\)) Tj T* (    def __init__\(self, npoints, mode='S'\):) Tj T* (        self.npoints = npoints) Tj T* (        if mode == 'P':) Tj T* (            self.mpcommands = ['calc_pi']) Tj T* (        elif mode == 'T':) Tj T* (            self.thcommands = ['calc_pi']) Tj T* (        elif mode == 'S':) Tj T* (            self.commands = ['calc_pi']) Tj T* (        self.n_cpu = multiprocessing.cpu_count\(\)) Tj T* (    ) Tj T* ET
+BT 1 0 0 1 0 74 Tm 12 TL /F3 10 Tf 0 0 0 rg (def calc_pi\(N\):) Tj T* (    inside = 0) Tj T* (    for j in xrange\(N\):) Tj T* (        x, y = random\(\), random\(\)) Tj T* (        if x*x + y*y ) Tj (<) Tj ( 1:) Tj T* (            inside += 1) Tj T* (    return \(4.0 * inside\) / N) Tj T* ET
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+BT 1 0 0 1 0 554 Tm 12 TL /F3 10 Tf 0 0 0 rg (from __future__ import with_statement) Tj T* (from random import random) Tj T* (import multiprocessing) Tj T* (import plac) Tj T*  T* (class PiCalculator\(object\):) Tj T* (    """Compute pi in parallel with threads or processes""") Tj T* (    ) Tj T* (    @plac.annotations\() Tj T* (        npoints=\('number of integration points', 'positional', None, int\),) Tj T* (        mode=\('sequential|parallel|threaded', 'option', 'm', str, 'SPT'\)\)) Tj T* (    def __init__\(self, npoints, mode='S'\):) Tj T* (        self.npoints = npoints) Tj T* (        if mode == 'P':) Tj T* (            self.mpcommands = ['calc_pi']) Tj T* (        elif mode == 'T':) Tj T* (            self.thcommands = ['calc_pi']) Tj T* (        elif mode == 'S':) Tj T* (            self.commands = ['calc_pi']) Tj T* (        self.n_cpu = multiprocessing.cpu_count\(\)) Tj T* (    ) Tj T* (    def submit_tasks\(self\):) Tj T* (        self.i = plac.Interpreter\(self\).__enter__\(\)            ) Tj T* (        return [self.i.submit\('calc_pi %d' % \(self.npoints / self.n_cpu\)\)) Tj T* (                for _ in range\(self.n_cpu\)]) Tj T*  T* (    def close\(self\):) Tj T* (        self.i.close\(\)) Tj T*  T* (    @plac.annotations\() Tj T* (        npoints=\('npoints', 'positional', None, int\)\)) Tj T* (    def calc_pi\(self, npoints\):) Tj T* (        counts = 0) Tj T* (        for j in xrange\(npoints\):) Tj T* (            n, r = divmod\(j, 1000000\)) Tj T* (            if r == 0:) Tj T* (                yield '%dM iterations' % n) Tj T* (            x, y = random\(\), random\(\)) Tj T* (            if x*x + y*y ) Tj (<) Tj ( 1:) Tj T* (                counts += 1) Tj T* (        yield \(4.0 * counts\)/npoints) Tj T*  T* (    def run\(self\):) Tj T* (        tasks = self.i.tasks\(\)) Tj T* (        for t in tasks:) Tj T* (            t.run\(\)) Tj T* (        try:) Tj T* ET
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-BT 1 0 0 1 0 62 Tm .381797 Tw 12 TL /F1 10 Tf 0 0 0 rg (Notice the ) Tj /F3 10 Tf (submit_tasks ) Tj /F1 10 Tf (method, which instantiates and initializes a ) Tj /F3 10 Tf (plac.Interpreter ) Tj /F1 10 Tf (object and) Tj T* 0 Tw 3.38152 Tw (submits a number of commands corresponding to the number of available CPUs. The ) Tj /F3 10 Tf (calc_pi) Tj T* 0 Tw 3.796651 Tw /F1 10 Tf (command yield a log message every million of interactions, just to monitor the progress of the) Tj T* 0 Tw 1.751318 Tw (computation. The ) Tj /F3 10 Tf (run ) Tj /F1 10 Tf (method starts all the submitted commands in parallel and sums the results. It) Tj T* 0 Tw 1.17104 Tw (returns the average value of ) Tj /F3 10 Tf (pi ) Tj /F1 10 Tf (after the slowest CPU has finished its job \(if the CPUs are equal and) Tj T* 0 Tw (equally busy they should finish more or less at the same time\).) Tj T* ET
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-BT 1 0 0 1 0 2 Tm /F1 10 Tf 12 TL (Here are the results on my old Macbook with Ubuntu 10.04 and Python 2.6, for 10 million of iterations:) Tj T* ET
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-BT 1 0 0 1 0 26 Tm /F3 10 Tf 12 TL ($ python picalculator.py -mP 10000000 # two processes) Tj T* (3.141904 in 5.744545 seconds) Tj T* ($ python picalculator.py -mT 10000000 # two threads) Tj T* ET
+BT 1 0 0 1 0 182 Tm 12 TL /F3 10 Tf 0 0 0 rg (            total = 0) Tj T* (            for task in tasks:) Tj T* (                total += task.result) Tj T* (        except: # the task was killed) Tj T* (            print tasks) Tj T* (            return) Tj T* (        return total / self.n_cpu) Tj T*  T* (if __name__ == '__main__':) Tj T* (    pc = plac.call\(PiCalculator\)) Tj T* (    pc.submit_tasks\(\)) Tj T* (    try:) Tj T* (        import time; t0 = time.time\(\)) Tj T* (        print '%f in %f seconds ' % \(pc.run\(\), time.time\(\) - t0\)) Tj T* (    finally:) Tj T* (        pc.close\(\)) Tj T* ET
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-BT 1 0 0 1 0 26 Tm /F3 10 Tf 12 TL (3.141272 in 13.875645 seconds) Tj T* ($ python picalculator.py -mS 10000000 # sequential) Tj T* (3.141586 in 11.353841 seconds) Tj T* ET
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-BT 1 0 0 1 0 50 Tm .167765 Tw 12 TL /F1 10 Tf 0 0 0 rg (Since the pattern submit a bunch of tasks, starts them and collect the results is so common, ) Tj 0 0 .501961 rg (plac ) Tj 0 0 0 rg (provides) Tj T* 0 Tw .493828 Tw (an utility function ) Tj /F3 10 Tf (runp\(genseq, mode='p', start=True\) ) Tj /F1 10 Tf (to start a bunch a generators and return) Tj T* 0 Tw .587765 Tw (a list of task objects. By default ) Tj /F3 10 Tf (runp ) Tj /F1 10 Tf (use processes, but you can use threads by passing ) Tj /F3 10 Tf (mode='t') Tj /F1 10 Tf (. If) Tj T* 0 Tw .422765 Tw (you do not wont to start the tasks, you can say so \() Tj /F3 10 Tf (start=False) Tj /F1 10 Tf (\). With ) Tj /F3 10 Tf (runp ) Tj /F1 10 Tf (the parallel pi calculation) Tj T* 0 Tw (becomes a one-liner:) Tj T* ET
+BT 1 0 0 1 0 50 Tm .167765 Tw 12 TL /F1 10 Tf 0 0 0 rg (Since the pattern submit a bunch of tasks, starts them and collect the results is so common, ) Tj 0 0 .501961 rg (plac ) Tj 0 0 0 rg (provides) Tj T* 0 Tw 2.487251 Tw (an utility function ) Tj /F3 10 Tf (runp\(genseq, mode='p', monitors=\(\), start=True\) ) Tj /F1 10 Tf (to start a bunch a) Tj T* 0 Tw .598876 Tw (generators and return a list of task objects. By default ) Tj /F3 10 Tf (runp ) Tj /F1 10 Tf (use processes, but you can use threads by) Tj T* 0 Tw .225542 Tw (passing ) Tj /F3 10 Tf (mode='t') Tj /F1 10 Tf (. If you do not wont to start the tasks, you can say so \() Tj /F3 10 Tf (start=False) Tj /F1 10 Tf (\). With ) Tj /F3 10 Tf (runp ) Tj /F1 10 Tf (the) Tj T* 0 Tw (parallel pi calculation becomes a one-liner:) Tj T* ET
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 %%EOF
diff --git a/plac/doc/plac_adv.txt b/plac/doc/plac_adv.txt
index e4c251b..4477781 100644
--- a/plac/doc/plac_adv.txt
+++ b/plac/doc/plac_adv.txt
@@ -1018,15 +1018,39 @@ task runs and more values are yielded. Accessing the ``.outlist`` is
 nonblocking and can be done freely.
 Finally there is a ``.result``
 property which waits for the task to finish and returns the last yielded 
-value or raises an exception.
-
-Here is some example code to visualize the output of the FakeImporter
-in Tkinter (I chose Tkinter because it is easy to use and it is
-in the standard library, but you can use any GUI):
+value or raises an exception. The code below provides an example of
+how you could implement a GUI over the importer example:
 
 .. include:: importer_ui.py
    :literal:
 
+Monitor support
+--------------------------------
+
+Starting from release 0.8 plac_ provides builtin support for monitoring the
+output of concurrent commands, at least for platforms where multiprocessing
+is fully supported. You can define your own monitor
+class, simply by inheriting from ``plac.Monitor`` and by
+overriding the methods ``add_listener(self, no)``, 
+``del_listener(self, taskno)``, ``notify_listener(self, taskno, msg)``,
+``schedule(self, seconds, func, arg)`` and ``run(self)``. 
+Then, you can a monitor object to any ``plac.Interpreter`` object
+by simply calling the ``add_monitor`` method.
+For convenience,
+``plac`` comes with a very simple ``TkMonitor`` based on Tkinter
+(I chose Tkinter because it is easy to use and it is
+in the standard library, but you can use any GUI): you can just
+look at how the ``TkMonitor`` is implemented in ``plac_tk.py``
+and adapt it. Here is an example of usage of the ``TkMonitor``:
+
+.. include:: tkmon.py
+   :literal:
+
+Try to give the ``hello`` command from the interactive interpreter:
+each time a new text widget will be added displaying the output
+of the command. Notice that if ``Tkinter`` is not installed correctly
+on your system the ``TkMonitor`` class will not be available.
+
 Parallel computing with plac
 ---------------------------------------------
 
@@ -1092,7 +1116,7 @@ mode is some 20% slower than the sequential mode.
 
 Since the pattern submit a bunch of tasks, starts them and collect the
 results is so common, plac_ provides an utility function 
-``runp(genseq, mode='p', start=True)`` to start
+``runp(genseq, mode='p', monitors=(), start=True)`` to start
 a bunch a generators and return a list of task objects. By default
 ``runp`` use processes, but you can use threads by passing ``mode='t'``.
 If you do not wont to start the tasks, you can say so (``start=False``).
@@ -1100,6 +1124,10 @@ With ``runp`` the parallel pi calculation becomes a one-liner::
 
     sum(task.result for task in plac.runp(calc_pi(N) for i in range(ncpus)))/ncpus
 
+The file ``test_runp`` in the ``doc`` directory of the plac distribution
+shows another couple of examples of usage, including how to show the
+results of the running computation on a ``TkMonitor``.
+
 The plac server
 -------------------------------------------------------
 
diff --git a/plac/doc/test_runp.py b/plac/doc/test_runp.py
new file mode 100644
index 0000000..619fc1f
--- /dev/null
+++ b/plac/doc/test_runp.py
@@ -0,0 +1,24 @@
+"""
+This test should work on Linux if you have both Tkinter installed.
+"""
+
+from __future__ import with_statement
+import plac, plac_tk, time
+
+def gen(n):
+    for i in range(n):
+        yield str(i)
+        time.sleep(.1)
+
+def test():
+    tasks = plac.runp([gen(3), gen(5), gen(10)])
+    for t in tasks:
+        t.result
+    t.man.stop()
+
+def test_tkmonitor():
+    mon = plac_tk.TkMonitor('tkmon')
+    tasks = plac.runp([gen(3), gen(5), gen(10)], monitors=[mon])
+    for t in tasks:
+        t.result
+    t.man.stop()
diff --git a/plac/doc/test_server.py b/plac/doc/test_server.py
index a9904ee..81214ee 100644
--- a/plac/doc/test_server.py
+++ b/plac/doc/test_server.py
@@ -14,22 +14,26 @@ wrong command
 showall
 ''']
 
-def client_send(commands, port):
+def telnet(commands, port):
     time.sleep(.5) # wait a bit for the server to start
     po = subprocess.Popen(['telnet', 'localhost', str(port)],
                           stdin=subprocess.PIPE)
-    for cmd in commands.splitlines():
-        po.stdin.write(cmd + '\n')
-        time.sleep(.1) # wait a bit for the server to answer
+    try:
+        for cmd in commands.splitlines():
+            po.stdin.write(cmd + '\n')
+            time.sleep(.1) # wait a bit for the server to answer
+    finally:
+        po.stdin.close()
 
 def test():
     port = random.choice(range(2000, 20000))
     clients = []
     for cmds in COMMANDS:
-        cl = multiprocessing.Process(target=client_send, args=(cmds, port))
+        cl = multiprocessing.Process(target=telnet, args=(cmds, port))
         clients.append(cl)
         cl.start()
-    i.stop_server(wait=1)
-    i.start_server(port, timeout=.1)
+
+    i.start_server(port, timeout=.5)
     for cl in clients:
         cl.join()
+    i.stop_server()
diff --git a/plac/plac.py b/plac/plac.py
index ed6d3a9..c762cca 100644
--- a/plac/plac.py
+++ b/plac/plac.py
@@ -27,9 +27,13 @@
 See doc/plac.pdf, doc/plac_adv.pdf for the documentation.
 """
 
-__version__ = '0.7.6'
+__version__ = '0.8.0'
 
 from plac_core import *
 
 if sys.version >= '2.5':
-    from plac_ext import Interpreter, import_main, ReadlineInput, stdout, runp
+    from plac_ext import Interpreter, import_main, ReadlineInput, stdout, runp, Monitor
+    try:
+        from plac_tk import TkMonitor
+    except ImportError:
+        pass
diff --git a/plac/plac_ext.py b/plac/plac_ext.py
index 6678477..4429aec 100644
--- a/plac/plac_ext.py
+++ b/plac/plac_ext.py
@@ -220,7 +220,10 @@ class BaseTask(object):
         self.str, self.etype, self.exc, self.tb = '', None, None, None
         self.status = 'SUBMITTED'
         self.outlist = []
-        
+
+    def notify(self, msg):
+        "Notifies the underlying monitor. To be implemented"
+
     def _wrap(self, genobj, stringify_tb=False):
         """
         Wrap the genobj into a generator managing the exceptions,
@@ -234,6 +237,7 @@ class BaseTask(object):
                     raise GeneratorExit
                 if value is not None: # add output
                     self.outlist.append(value)
+                    self.notify(str(value))
                 yield
         except (GeneratorExit, TerminatedProcess, KeyboardInterrupt): 
             # soft termination
@@ -352,13 +356,19 @@ class MPTask(BaseTask):
         except: # the process died hard
             return []
 
-    def __init__(self, no, arglist, genobj, mp_manager):
+    def notify(self, msg):
+        self.man.send('notify_listener %d %r' % (self.no, msg))
+
+    def __init__(self, no, arglist, genobj, manager):
+        """
+        The monitor has a .send method and a .man multiprocessing.Manager
+        """
         self.no = no
         self.arglist = arglist
         self._genobj = self._wrap(genobj, stringify_tb=True)
-        self.mp_manager = mp_manager
-        self._outlist = self.mp_manager.list()
-        self.ns = self.mp_manager.Namespace()
+        self.man = manager
+        self._outlist = manager.mp.list()
+        self.ns = manager.mp.Namespace()
         self.status = 'SUBMITTED'
         self.etype, self.exc, self.tb = None, None, None
         self.str = repr(self)
@@ -381,6 +391,7 @@ class MPTask(BaseTask):
 
 class HelpSummary(object):
     "Build the help summary consistently with the cmd module"
+
     @classmethod
     def make(cls, obj, specialcommands):
         c = cmd.Cmd(stdout=cls())
@@ -394,10 +405,13 @@ class HelpSummary(object):
         c.print_topics('threaded commands',
                        sorted(obj.thcommands), 15, 80)
         return c.stdout
+
     def __init__(self):
         self._ls = []
+
     def write(self, s):
         self._ls.append(s)
+
     def __str__(self):
         return ''.join(self._ls)
 
@@ -415,7 +429,7 @@ class TaskManager(object):
         if obj.mpcommands or obj.thcommands:
             self.specialcommands.update(['.kill', '.list', '.output'])
         self.helpsummary = HelpSummary.make(obj, self.specialcommands)
-        self.mp_manager = multiprocessing.Manager() if obj.mpcommands else None
+        self.man = Manager() if obj.mpcommands else None
         signal.signal(signal.SIGTERM, terminatedProcess)
 
     def close(self):
@@ -427,8 +441,8 @@ class TaskManager(object):
                     task.wait()
             except: # task killed, nothing to wait
                 pass
-        if self.mp_manager:
-            self.mp_manager.shutdown()
+        if self.man:
+            self.man.stop()
 
     def _get_latest(self, taskno=-1, status=None):
         "Get the latest submitted task from the registry"
@@ -519,17 +533,22 @@ class Process(subprocess.Popen):
     "Start the interpreter specified by the params in a subprocess"
 
     def __init__(self, params):
-        code = '''import plac
+        signal.signal(signal.SIGPIPE, signal.SIG_DFL) 
+        # to avoid broken pipe messages
+        code = '''import plac, sys
+sys.argv[0] = '<%s>'
 plac.Interpreter(plac.import_main(*%s)).interact(prompt='i>\\n')
-''' % params
+''' % (params[0], params)
         subprocess.Popen.__init__(
             self, [sys.executable, '-u', '-c', code],
             stdin=subprocess.PIPE, stdout=subprocess.PIPE)
+        self.man = multiprocessing.Manager()
 
     def close(self):
         "Close stdin and stdout"
         self.stdin.close()
         self.stdout.close()
+        self.man.shutdown()
 
     def recv(self): # char-by-char cannot work
         "Return the output of the subprocess, line-by-line until the prompt"
@@ -546,6 +565,111 @@ plac.Interpreter(plac.import_main(*%s)).interact(prompt='i>\\n')
         self.stdin.write(line + os.linesep)
         return self.recv()
 
+class Monitor(object):
+    """
+    Base monitor class with methods add_listener/del_listener/notify_listener
+    and start/stop/schedule/slave.
+    """
+    commands = 'add_listener', 'del_listener', 'notify_listener'
+    def __init__(self, name):
+        self.name = name
+    def add_listener(self, taskno):
+        pass
+    def del_listener(self, taskno):
+        pass    
+    def notify_listener(self, taskno, msg):
+        pass
+    def start(self):
+        pass
+    def stop(self):
+        pass
+    def schedule(self, seconds, display, arg):
+        pass
+
+import Queue
+
+class SlaveProcess(object):
+    """
+    Spawn a slave process reading from an input queue and displaying
+    on a monitor object. Methods are start/send/stop.
+    """
+    def __init__(self, mon):
+        self.mon= mon
+        self.queue = multiprocessing.Queue()
+        self.proc = multiprocessing.Process(None, self._run)
+
+    def start(self):
+        self.proc.start()
+
+    def send(self, line):
+        self.queue.put(line)
+
+    def stop(self):
+        self.queue.close()
+        self.proc.terminate()
+
+    def _sendline(self, i):
+        "Send a line to the underlying monitor"
+        try:
+            line = self.queue.get_nowait()
+        except Queue.Empty:
+            pass
+        else:
+            i.send(line)
+        self.mon.schedule(.1, self._sendline, i)
+
+    def _run(self):
+        with Interpreter(self.mon) as i:
+            # .schedule() must be invoked inside the with block
+            self.mon.schedule(.1, self._sendline, i)
+            self.mon.run()
+
+class StartStopObject(object):
+    started = False
+    def start(self): pass
+    def stop(self): pass
+
+class Manager(StartStopObject):
+    """
+    The plac Manager contains a multiprocessing.Manager and a set
+    of slave monitor processes to which we can send commands. There
+    is a manager for each interpreter with mpcommands.
+    """
+    def add(self, monitor):
+        'Add or replace a monitor in the registry'
+        slave = SlaveProcess(monitor)
+        name = slave.name = monitor.name
+        self.registry[name] = slave
+
+    def delete(self, name):
+        'Remove a named monitor from the registry'
+        del self.registry[name]
+
+    def __init__(self):
+        self.registry = {}
+        self.started = False
+        self.mp = None
+
+    # can be called more than once
+    def start(self):
+        if self.mp is None:
+            self.mp = multiprocessing.Manager()
+        for slave in self.registry.itervalues():
+            slave.start()
+        self.started = True
+
+    def stop(self):
+        for slave in self.registry.itervalues():
+            slave.stop()
+        if self.mp:
+            self.mp.shutdown()
+            self.mp = None
+        self.started = False
+
+    def send(self, line):
+        for slave in self.registry.itervalues():
+            slave.send(line)
+
 ########################## plac server ##############################
 
 import asyncore, asynchat, socket
@@ -621,29 +745,6 @@ class Interpreter(object):
     A context manager with a .send method and a few utility methods:
     execute, test and doctest.
     """
-
-    @classmethod
-    def call(cls, factory, arglist=sys.argv[1:], 
-             commentchar='#', split=shlex.split, 
-             stdin=sys.stdin, prompt='i> ', verbose=False):
-        """
-        Call a container factory with the arglist and instantiate an
-        interpreter object. If there are remaining arguments, send them to the
-        interpreter, else start an interactive session.
-        """
-        obj = partial_call(factory, arglist)
-        i = cls(obj, commentchar, split)
-        if i.obj._args_:
-            with i:
-                task = i.send(i.obj._args_) # synchronous
-                if task.exc:
-                    raise task.etype, task.exc, task.tb
-                print(task)
-        elif i.obj._interact_:
-            i.interact(stdin, prompt, verbose)
-        else:
-            i.parser.print_usage()
-
     def __init__(self, obj, commentchar='#', split=shlex.split):
         self.obj = obj
         try:
@@ -654,17 +755,18 @@ class Interpreter(object):
         self.split = split
         self._set_commands(obj)
         self.tm = TaskManager(obj)
+        self.man = self.tm.man
         self.parser = plac_core.parser_from(obj, prog='', add_help=False)
         if self.commands:
             self.commands.update(self.tm.specialcommands)
-            self.parser.addsubcommands(self.tm.specialcommands, self.tm,
-                                  title='special commands')
+            self.parser.addsubcommands(
+                self.tm.specialcommands, self.tm, title='special commands')
         if obj.mpcommands:
-            self.parser.addsubcommands(obj.mpcommands, obj,
-                                  title='commands run in external processes')
+            self.parser.addsubcommands(
+                obj.mpcommands, obj, title='commands run in external processes')
         if obj.thcommands:
-            self.parser.addsubcommands(obj.thcommands, obj,
-                                  title='threaded commands')
+            self.parser.addsubcommands(
+                obj.thcommands, obj, title='threaded commands')
         self.parser.error = lambda msg: sys.exit(msg) # patch the parser
         self._interpreter = None
 
@@ -705,9 +807,14 @@ class Interpreter(object):
             arglist = line
         if not arglist:
             return nulltask
+        m = self.tm.man # manager
+        if m and not m.started:
+            m.start()
         task = self._interpreter.send(arglist) # nonblocking
         if not plac_core._match_cmd(arglist[0], self.tm.specialcommands):
             self.tm.registry[task.no] = task
+            if m:
+                m.send('add_listener %d' % task.no)
         return task
 
     def send(self, line):
@@ -745,7 +852,7 @@ class Interpreter(object):
                 if not plac_core.iterable(result): # atomic result
                     task = SynTask(no, arglist, gen_val(result))
                 elif cmd in self.obj.mpcommands:
-                    task = MPTask(no, arglist, result, self.tm.mp_manager)
+                    task = MPTask(no, arglist, result, self.tm.man)
                 elif cmd in self.obj.thcommands:
                     task = ThreadedTask(no, arglist, result)
                 else: # blocking task
@@ -867,25 +974,55 @@ class Interpreter(object):
         finally:
             asyncore.close_all()
 
-    def stop_server(self, wait=0.0):
+    def stop_server(self, after=0.0):
         "Stops the asyncore server, possibly after a given number of seconds"
-        threading.Timer(wait, asyncore.socket_map.clear).start()
+        threading.Timer(after, asyncore.socket_map.clear).start()
+
+    def add_monitor(self, mon):
+        self.man.add(mon)
+
+    def del_monitor(self, name):
+        self.man.delete(name)
+
+    @classmethod
+    def call(cls, factory, arglist=sys.argv[1:], 
+             commentchar='#', split=shlex.split, 
+             stdin=sys.stdin, prompt='i> ', verbose=False):
+        """
+        Call a container factory with the arglist and instantiate an
+        interpreter object. If there are remaining arguments, send them to the
+        interpreter, else start an interactive session.
+        """
+        obj = partial_call(factory, arglist)
+        i = cls(obj, commentchar, split)
+        if i.obj._args_:
+            with i:
+                task = i.send(i.obj._args_) # synchronous
+                if task.exc:
+                    raise task.etype, task.exc, task.tb
+                print(task)
+        elif i.obj._interact_:
+            i.interact(stdin, prompt, verbose)
+        else:
+            i.parser.print_usage()
 
 #################################### runp #####################################
 
 class _TaskLauncher(object):
     "Helper for runp"
+
     def __init__(self, genseq, mode):
         if mode == 'p':
             self.mpcommands = ['rungen']
         else:
             self.thcommands = ['rungen']
         self.genlist = list(genseq)
+
     def rungen(self, i):
         for out in self.genlist[int(i) - 1]:
             yield out
 
-def runp(genseq, mode='p', start=True):
+def runp(genseq, mode='p', monitors=(), start=True):
     """Run a sequence of generators in parallel. Mode can be 'p' (use processes)
     or 't' (use threads). Return a list of running task objects. If start is
     False, the tasks are only submitted and not automatically started.
@@ -893,6 +1030,8 @@ def runp(genseq, mode='p', start=True):
     assert mode in 'pt', mode
     launcher = _TaskLauncher(genseq, mode)
     inter = Interpreter(launcher).__enter__()
+    for mon in monitors: # must be added before submit
+        inter.add_monitor(mon)
     for i in range(len(launcher.genlist)):
         inter.submit('rungen %d' % (i + 1))
     if start:
diff --git a/plac/setup.py b/plac/setup.py
index aafe43d..006786a 100644
--- a/plac/setup.py
+++ b/plac/setup.py
@@ -32,7 +32,7 @@ if __name__ == '__main__':
           author_email='michele.simionato@gmail.com',
           url='http://pypi.python.org/pypi/plac',
           license="BSD License",
-          py_modules = ['plac_core', 'plac_ext', 'plac'],
+          py_modules = ['plac_core', 'plac_ext', 'plac_tk', 'plac'],
           scripts = ['plac_runner.py'],
           install_requires=require('argparse', 'multiprocessing'),
           use_2to3=True,
@@ -44,6 +44,7 @@ if __name__ == '__main__':
                        'Natural Language :: English',
                        'Operating System :: OS Independent',
                        'Programming Language :: Python',
+                       'Programming Language :: Python :: 3',
                        'Topic :: Software Development :: Libraries',
                        'Topic :: Utilities'],
           zip_safe=False)
author	Michele Simionato <michele.simionato@gmail.com>	2011-02-16 10:50:26 +0100
committer	Michele Simionato <michele.simionato@gmail.com>	2011-02-16 10:50:26 +0100
commit	ff2c6f7791094f6f4e04393e9e038847a493fbce (patch)
tree	9cc4c16a722ff2ca908c2723d6f51339e373425d
parent	fdd6d7c4d569c7efaf13d4c256369867c2dd8a5a (diff)
parent	02d7e73ea41c57e0f1abe47cfda0cedad4a7c720 (diff)
download	micheles-ff2c6f7791094f6f4e04393e9e038847a493fbce.tar.gz