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<h3><a href="../contents.html">Table Of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">dis – Python Bytecode Disassembler</a><ul>
<li><a class="reference internal" href="#basic-disassembly">Basic Disassembly</a></li>
<li><a class="reference internal" href="#disassembling-functions">Disassembling Functions</a></li>
<li><a class="reference internal" href="#classes">Classes</a></li>
<li><a class="reference internal" href="#using-disassembly-to-debug">Using Disassembly to Debug</a></li>
<li><a class="reference internal" href="#performance-analysis-of-loops">Performance Analysis of Loops</a></li>
<li><a class="reference internal" href="#compiler-optimizations">Compiler Optimizations</a></li>
</ul>
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<div class="section" id="module-dis">
<span id="dis-python-bytecode-disassembler"></span><h1>dis – Python Bytecode Disassembler<a class="headerlink" href="#module-dis" title="Permalink to this headline">¶</a></h1>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field"><th class="field-name">Purpose:</th><td class="field-body">Convert code objects to a human-readable representation of the bytecodes for analysis.</td>
</tr>
<tr class="field"><th class="field-name">Python Version:</th><td class="field-body">1.4 and later</td>
</tr>
</tbody>
</table>
<p>The <a class="reference internal" href="#module-dis" title="dis: Python Bytecode Disassembler"><tt class="xref py py-mod docutils literal"><span class="pre">dis</span></tt></a> module includes functions for working with Python
bytecode by “disassembling” it into a more human-readable form.
Reviewing the bytecodes being executed by the interpreter is a good
way to hand-tune tight loops and perform other kinds of optimizations.
It is also useful for finding race conditions in multi-threaded
applications, since you can estimate the point in your code where
thread control may switch.</p>
<div class="section" id="basic-disassembly">
<h2>Basic Disassembly<a class="headerlink" href="#basic-disassembly" title="Permalink to this headline">¶</a></h2>
<p>The function <tt class="docutils literal"><span class="pre">dis.dis()</span></tt> prints the disassembled representation of a
Python code source (module, class, method, function, or code object).
We can disassemble a module such as:</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre>1
2
3
4</pre></div></td><td class="code"><div class="highlight"><pre><span class="c">#!/usr/bin/env python</span>
<span class="c"># encoding: utf-8</span>
<span class="n">my_dict</span> <span class="o">=</span> <span class="p">{</span> <span class="s">'a'</span><span class="p">:</span><span class="mi">1</span> <span class="p">}</span>
</pre></div>
</td></tr></table></div>
<p>by running <a class="reference internal" href="#module-dis" title="dis: Python Bytecode Disassembler"><tt class="xref py py-mod docutils literal"><span class="pre">dis</span></tt></a> from the command line. The output is organized
into columns with the original source line number, the instruction
“address” within the code object, the opcode name, and any arguments
passed to the opcode.</p>
<div class="highlight-python"><pre>$ python -m dis dis_simple.py
4 0 BUILD_MAP 1
3 LOAD_CONST 0 (1)
6 LOAD_CONST 1 ('a')
9 STORE_MAP
10 STORE_NAME 0 (my_dict)
13 LOAD_CONST 2 (None)
16 RETURN_VALUE</pre>
</div>
<p>In this case, the source translates to 5 different operations to
create and populate the dictionary, then save the results to a local
variable. Since the Python interpreter is stack-based, the first
steps are to put the constants onto the stack in the correct order
with LOAD_CONST, and then use STORE_MAP to pop off the new key and
value to be added to the dictionary. The resulting object is bound to
the name “my_dict” with STORE_NAME.</p>
</div>
<div class="section" id="disassembling-functions">
<h2>Disassembling Functions<a class="headerlink" href="#disassembling-functions" title="Permalink to this headline">¶</a></h2>
<p>Unfortunately, disassembling the entire module does not recurse into
functions automatically. For example, if we start with this module:</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10</pre></div></td><td class="code"><div class="highlight"><pre><span class="c">#!/usr/bin/env python</span>
<span class="c"># encoding: utf-8</span>
<span class="k">def</span> <span class="nf">f</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">):</span>
<span class="n">nargs</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span>
<span class="k">print</span> <span class="n">nargs</span><span class="p">,</span> <span class="n">args</span>
<span class="k">if</span> <span class="n">__name__</span> <span class="o">==</span> <span class="s">'__main__'</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">dis</span>
<span class="n">dis</span><span class="o">.</span><span class="n">dis</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
</pre></div>
</td></tr></table></div>
<p>the results show loading the code object onto the stack and then
turning it into a function (LOAD_CONST, MAKE_FUNCTION), but <em>not</em> the
body of the function.</p>
<div class="highlight-python"><pre>$ python -m dis dis_function.py
4 0 LOAD_CONST 0 (<code object f at 0x100464f30, file "dis_function.py", line 4>)
3 MAKE_FUNCTION 0
6 STORE_NAME 0 (f)
8 9 LOAD_NAME 1 (__name__)
12 LOAD_CONST 1 ('__main__')
15 COMPARE_OP 2 (==)
18 POP_JUMP_IF_FALSE 49
9 21 LOAD_CONST 2 (-1)
24 LOAD_CONST 3 (None)
27 IMPORT_NAME 2 (dis)
30 STORE_NAME 2 (dis)
10 33 LOAD_NAME 2 (dis)
36 LOAD_ATTR 2 (dis)
39 LOAD_NAME 0 (f)
42 CALL_FUNCTION 1
45 POP_TOP
46 JUMP_FORWARD 0 (to 49)
>> 49 LOAD_CONST 3 (None)
52 RETURN_VALUE</pre>
</div>
<p>To see inside the function, we need to pass it to <tt class="docutils literal"><span class="pre">dis.dis()</span></tt>.</p>
<div class="highlight-python"><pre>$ python dis_function.py
5 0 LOAD_GLOBAL 0 (len)
3 LOAD_FAST 0 (args)
6 CALL_FUNCTION 1
9 STORE_FAST 1 (nargs)
6 12 LOAD_FAST 1 (nargs)
15 PRINT_ITEM
16 LOAD_FAST 0 (args)
19 PRINT_ITEM
20 PRINT_NEWLINE
21 LOAD_CONST 0 (None)
24 RETURN_VALUE</pre>
</div>
</div>
<div class="section" id="classes">
<h2>Classes<a class="headerlink" href="#classes" title="Permalink to this headline">¶</a></h2>
<p>You can also pass classes to <tt class="docutils literal"><span class="pre">dis</span></tt>, in which case all of the methods
are disassembled in turn.</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17</pre></div></td><td class="code"><div class="highlight"><pre><span class="c">#!/usr/bin/env python</span>
<span class="c"># encoding: utf-8</span>
<span class="kn">import</span> <span class="nn">dis</span>
<span class="k">class</span> <span class="nc">MyObject</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">"""Example for dis."""</span>
<span class="n">CLASS_ATTRIBUTE</span> <span class="o">=</span> <span class="s">'some value'</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">name</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s">'MyObject(</span><span class="si">%s</span><span class="s">)'</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span>
<span class="n">dis</span><span class="o">.</span><span class="n">dis</span><span class="p">(</span><span class="n">MyObject</span><span class="p">)</span>
</pre></div>
</td></tr></table></div>
<div class="highlight-python"><pre>$ python dis_class.py
Disassembly of __init__:
12 0 LOAD_FAST 1 (name)
3 LOAD_FAST 0 (self)
6 STORE_ATTR 0 (name)
9 LOAD_CONST 0 (None)
12 RETURN_VALUE
Disassembly of __str__:
15 0 LOAD_CONST 1 ('MyObject(%s)')
3 LOAD_FAST 0 (self)
6 LOAD_ATTR 0 (name)
9 BINARY_MODULO
10 RETURN_VALUE</pre>
</div>
</div>
<div class="section" id="using-disassembly-to-debug">
<h2>Using Disassembly to Debug<a class="headerlink" href="#using-disassembly-to-debug" title="Permalink to this headline">¶</a></h2>
<p>Sometimes when debugging an exception it can be useful to see which
bytecode caused a problem. There are a couple of ways to disassemble
the code around an error.</p>
<p>The first is by using <tt class="docutils literal"><span class="pre">dis.dis()</span></tt> in the interactive interpreter to
report about the last exception. If no argument is passed to <tt class="docutils literal"><span class="pre">dis</span></tt>,
then it looks for an exception and shows the disassembly of the top of
the stack that caused it.</p>
<div class="highlight-python"><pre>$ python
Python 2.6.2 (r262:71600, Apr 16 2009, 09:17:39)
[GCC 4.0.1 (Apple Computer, Inc. build 5250)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import dis
>>> j = 4
>>> i = i + 4
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'i' is not defined
>>> dis.distb()
1 --> 0 LOAD_NAME 0 (i)
3 LOAD_CONST 0 (4)
6 BINARY_ADD
7 STORE_NAME 0 (i)
10 LOAD_CONST 1 (None)
13 RETURN_VALUE
>>></pre>
</div>
<p>Notice the <tt class="docutils literal"><span class="pre">--></span></tt> indicating the opcode that caused the error. There
is no <tt class="docutils literal"><span class="pre">i</span></tt> variable defined, so the value associated with the name
can’t be loaded onto the stack.</p>
<p>Within your code you can also print the information about an active
traceback by passing it to <tt class="docutils literal"><span class="pre">dis.distb()</span></tt> directly. In this example,
there is a DivideByZero exception, but since the formula has two
divisions it isn’t clear which part is zero.</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16</pre></div></td><td class="code"><div class="highlight"><pre><span class="c">#!/usr/bin/env python</span>
<span class="c"># encoding: utf-8</span>
<span class="n">i</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">j</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">k</span> <span class="o">=</span> <span class="mi">3</span>
<span class="c"># ... many lines removed ...</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">k</span> <span class="o">*</span> <span class="p">(</span><span class="n">i</span> <span class="o">/</span> <span class="n">j</span><span class="p">)</span> <span class="o">+</span> <span class="p">(</span><span class="n">i</span> <span class="o">/</span> <span class="n">k</span><span class="p">)</span>
<span class="k">except</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">dis</span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="n">exc_type</span><span class="p">,</span> <span class="n">exc_value</span><span class="p">,</span> <span class="n">exc_tb</span> <span class="o">=</span> <span class="n">sys</span><span class="o">.</span><span class="n">exc_info</span><span class="p">()</span>
<span class="n">dis</span><span class="o">.</span><span class="n">distb</span><span class="p">(</span><span class="n">exc_tb</span><span class="p">)</span>
</pre></div>
</td></tr></table></div>
<p>The bad value is easy to spot when it is loaded onto the stack in the
disassembled version. The bad operation is highlighted with the
<tt class="docutils literal"><span class="pre">--></span></tt>, and we just need to look up a few lines higher to find where
<tt class="docutils literal"><span class="pre">i</span></tt>‘s <tt class="docutils literal"><span class="pre">0</span></tt> value was pushed onto the stack.</p>
<div class="highlight-python"><pre>$ python dis_traceback.py
4 0 LOAD_CONST 0 (1)
3 STORE_NAME 0 (i)
5 6 LOAD_CONST 1 (0)
9 STORE_NAME 1 (j)
6 12 LOAD_CONST 2 (3)
15 STORE_NAME 2 (k)
10 18 SETUP_EXCEPT 26 (to 47)
11 21 LOAD_NAME 2 (k)
24 LOAD_NAME 0 (i)
27 LOAD_NAME 1 (j)
--> 30 BINARY_DIVIDE
31 BINARY_MULTIPLY
32 LOAD_NAME 0 (i)
35 LOAD_NAME 2 (k)
38 BINARY_DIVIDE
39 BINARY_ADD
40 STORE_NAME 3 (result)
43 POP_BLOCK
44 JUMP_FORWARD 65 (to 112)
12 >> 47 POP_TOP
48 POP_TOP
49 POP_TOP
13 50 LOAD_CONST 3 (-1)
53 LOAD_CONST 4 (None)
56 IMPORT_NAME 4 (dis)
59 STORE_NAME 4 (dis)
14 62 LOAD_CONST 3 (-1)
65 LOAD_CONST 4 (None)
68 IMPORT_NAME 5 (sys)
71 STORE_NAME 5 (sys)
15 74 LOAD_NAME 5 (sys)
77 LOAD_ATTR 6 (exc_info)
80 CALL_FUNCTION 0
83 UNPACK_SEQUENCE 3
86 STORE_NAME 7 (exc_type)
89 STORE_NAME 8 (exc_value)
92 STORE_NAME 9 (exc_tb)
16 95 LOAD_NAME 4 (dis)
98 LOAD_ATTR 10 (distb)
101 LOAD_NAME 9 (exc_tb)
104 CALL_FUNCTION 1
107 POP_TOP
108 JUMP_FORWARD 1 (to 112)
111 END_FINALLY
>> 112 LOAD_CONST 4 (None)
115 RETURN_VALUE</pre>
</div>
</div>
<div class="section" id="performance-analysis-of-loops">
<h2>Performance Analysis of Loops<a class="headerlink" href="#performance-analysis-of-loops" title="Permalink to this headline">¶</a></h2>
<p>Aside from debugging errors, <a class="reference internal" href="#module-dis" title="dis: Python Bytecode Disassembler"><tt class="xref py py-mod docutils literal"><span class="pre">dis</span></tt></a> can also help you identify
performance issues in your code. Examining the disassembled code is
especially useful with tight loops where the number of exposed Python
instructions is low but they translate to an inefficient set of
bytecodes. We can see how the disassembly is helpful by examining a
few different implementations of a class, <tt class="docutils literal"><span class="pre">Dictionary</span></tt>, that reads a
list of words and groups them by their first letter.</p>
<p>First, the test driver application:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">dis</span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">import</span> <span class="nn">timeit</span>
<span class="n">module_name</span> <span class="o">=</span> <span class="n">sys</span><span class="o">.</span><span class="n">argv</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="n">module</span> <span class="o">=</span> <span class="nb">__import__</span><span class="p">(</span><span class="n">module_name</span><span class="p">)</span>
<span class="n">Dictionary</span> <span class="o">=</span> <span class="n">module</span><span class="o">.</span><span class="n">Dictionary</span>
<span class="n">dis</span><span class="o">.</span><span class="n">dis</span><span class="p">(</span><span class="n">Dictionary</span><span class="o">.</span><span class="n">load_data</span><span class="p">)</span>
<span class="k">print</span>
<span class="n">t</span> <span class="o">=</span> <span class="n">timeit</span><span class="o">.</span><span class="n">Timer</span><span class="p">(</span>
<span class="s">'d = Dictionary(words)'</span><span class="p">,</span>
<span class="sd">"""from %(module_name)s import Dictionary</span>
<span class="sd">words = [l.strip() for l in open('/usr/share/dict/words', 'rt')]</span>
<span class="sd"> """</span> <span class="o">%</span> <span class="nb">locals</span><span class="p">()</span>
<span class="p">)</span>
<span class="n">iterations</span> <span class="o">=</span> <span class="mi">10</span>
<span class="k">print</span> <span class="s">'TIME: </span><span class="si">%0.4f</span><span class="s">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">timeit</span><span class="p">(</span><span class="n">iterations</span><span class="p">)</span><span class="o">/</span><span class="n">iterations</span><span class="p">)</span>
</pre></div>
</div>
<p>We can use <tt class="docutils literal"><span class="pre">dis_test_loop.py</span></tt> to run each incarnation of the
<tt class="docutils literal"><span class="pre">Dictionary</span></tt> class.</p>
<p>A straightforward implementation of <tt class="docutils literal"><span class="pre">Dictionary</span></tt> might look
something like:</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15</pre></div></td><td class="code"><div class="highlight"><pre><span class="c">#!/usr/bin/env python</span>
<span class="c"># encoding: utf-8</span>
<span class="k">class</span> <span class="nc">Dictionary</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">words</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">by_letter</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">load_data</span><span class="p">(</span><span class="n">words</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">load_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">words</span><span class="p">):</span>
<span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">words</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">by_letter</span><span class="p">[</span><span class="n">word</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">word</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">KeyError</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">by_letter</span><span class="p">[</span><span class="n">word</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[</span><span class="n">word</span><span class="p">]</span>
</pre></div>
</td></tr></table></div>
<p>The output shows this version taking 0.1074 seconds to load the 234936
words in my copy of <tt class="docutils literal"><span class="pre">/usr/share/dict/words</span></tt> on OS X. That’s not too
bad, but as you can see from the disassembly below, the loop is doing
more work than it needs to. As it enters the loop in opcode 13, it
sets up an exception context (<tt class="docutils literal"><span class="pre">SETUP_EXCEPT</span></tt>). Then it takes 6
opcodes to find <tt class="docutils literal"><span class="pre">self.by_letter[word[0]]</span></tt> before appending <tt class="docutils literal"><span class="pre">word</span></tt>
to the list. If there is an exception because <tt class="docutils literal"><span class="pre">word[0]</span></tt> isn’t in
the dictionary yet, the exception handler does all of the same work to
determine <tt class="docutils literal"><span class="pre">word[0]</span></tt> (3 opcodes) and sets <tt class="docutils literal"><span class="pre">self.by_letter[word[0]]</span></tt>
to a new list containing the word.</p>
<div class="highlight-python"><pre>$ python dis_test_loop.py dis_slow_loop
11 0 SETUP_LOOP 84 (to 87)
3 LOAD_FAST 1 (words)
6 GET_ITER
>> 7 FOR_ITER 76 (to 86)
10 STORE_FAST 2 (word)
12 13 SETUP_EXCEPT 28 (to 44)
13 16 LOAD_FAST 0 (self)
19 LOAD_ATTR 0 (by_letter)
22 LOAD_FAST 2 (word)
25 LOAD_CONST 1 (0)
28 BINARY_SUBSCR
29 BINARY_SUBSCR
30 LOAD_ATTR 1 (append)
33 LOAD_FAST 2 (word)
36 CALL_FUNCTION 1
39 POP_TOP
40 POP_BLOCK
41 JUMP_ABSOLUTE 7
14 >> 44 DUP_TOP
45 LOAD_GLOBAL 2 (KeyError)
48 COMPARE_OP 10 (exception match)
51 JUMP_IF_FALSE 27 (to 81)
54 POP_TOP
55 POP_TOP
56 POP_TOP
57 POP_TOP
15 58 LOAD_FAST 2 (word)
61 BUILD_LIST 1
64 LOAD_FAST 0 (self)
67 LOAD_ATTR 0 (by_letter)
70 LOAD_FAST 2 (word)
73 LOAD_CONST 1 (0)
76 BINARY_SUBSCR
77 STORE_SUBSCR
78 JUMP_ABSOLUTE 7
>> 81 POP_TOP
82 END_FINALLY
83 JUMP_ABSOLUTE 7
>> 86 POP_BLOCK
>> 87 LOAD_CONST 0 (None)
90 RETURN_VALUE
TIME: 0.1074</pre>
</div>
<p>One technique to eliminate the exception setup is to pre-populate
<tt class="docutils literal"><span class="pre">self.by_letter</span></tt> with one list for each letter of the alphabet.
That means we should always find the list we want for the new word,
and can just do the lookup and save the value.</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15</pre></div></td><td class="code"><div class="highlight"><pre><span class="c">#!/usr/bin/env python</span>
<span class="c"># encoding: utf-8</span>
<span class="kn">import</span> <span class="nn">string</span>
<span class="k">class</span> <span class="nc">Dictionary</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">words</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">by_letter</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span> <span class="p">(</span><span class="n">letter</span><span class="p">,</span> <span class="p">[])</span>
<span class="k">for</span> <span class="n">letter</span> <span class="ow">in</span> <span class="n">string</span><span class="o">.</span><span class="n">letters</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">load_data</span><span class="p">(</span><span class="n">words</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">load_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">words</span><span class="p">):</span>
<span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">words</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">by_letter</span><span class="p">[</span><span class="n">word</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">word</span><span class="p">)</span>
</pre></div>
</td></tr></table></div>
<p>The change cuts the number of opcodes in half, but only shaves the
time down to 0.0984 seconds. Obviously the exception handling had
some overhead, but not a huge amount.</p>
<div class="highlight-python"><pre>$ python dis_test_loop.py dis_faster_loop
14 0 SETUP_LOOP 38 (to 41)
3 LOAD_FAST 1 (words)
6 GET_ITER
>> 7 FOR_ITER 30 (to 40)
10 STORE_FAST 2 (word)
15 13 LOAD_FAST 0 (self)
16 LOAD_ATTR 0 (by_letter)
19 LOAD_FAST 2 (word)
22 LOAD_CONST 1 (0)
25 BINARY_SUBSCR
26 BINARY_SUBSCR
27 LOAD_ATTR 1 (append)
30 LOAD_FAST 2 (word)
33 CALL_FUNCTION 1
36 POP_TOP
37 JUMP_ABSOLUTE 7
>> 40 POP_BLOCK
>> 41 LOAD_CONST 0 (None)
44 RETURN_VALUE
TIME: 0.0984</pre>
</div>
<p>We can further improve the performance by moving the lookup for
<tt class="docutils literal"><span class="pre">self.by_letter</span></tt> outside of the loop (the value doesn’t change,
after all).</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15</pre></div></td><td class="code"><div class="highlight"><pre><span class="c">#!/usr/bin/env python</span>
<span class="c"># encoding: utf-8</span>
<span class="kn">import</span> <span class="nn">collections</span>
<span class="k">class</span> <span class="nc">Dictionary</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">words</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">by_letter</span> <span class="o">=</span> <span class="n">collections</span><span class="o">.</span><span class="n">defaultdict</span><span class="p">(</span><span class="nb">list</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">load_data</span><span class="p">(</span><span class="n">words</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">load_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">words</span><span class="p">):</span>
<span class="n">by_letter</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">by_letter</span>
<span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">words</span><span class="p">:</span>
<span class="n">by_letter</span><span class="p">[</span><span class="n">word</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">word</span><span class="p">)</span>
</pre></div>
</td></tr></table></div>
<p>Opcodes 0-6 now find the value of <tt class="docutils literal"><span class="pre">self.by_letter</span></tt> and save it as a
local variable <tt class="docutils literal"><span class="pre">by_letter</span></tt>. Using a local variable only takes a
single opcode, instead of 2 (statement 22 uses <tt class="docutils literal"><span class="pre">LOAD_FAST</span></tt> to place
the dictionary onto the stack). After this change, the run time is
down to 0.0842 seconds.</p>
<div class="highlight-python"><pre>$ python dis_test_loop.py dis_fastest_loop
13 0 LOAD_FAST 0 (self)
3 LOAD_ATTR 0 (by_letter)
6 STORE_FAST 2 (by_letter)
14 9 SETUP_LOOP 35 (to 47)
12 LOAD_FAST 1 (words)
15 GET_ITER
>> 16 FOR_ITER 27 (to 46)
19 STORE_FAST 3 (word)
15 22 LOAD_FAST 2 (by_letter)
25 LOAD_FAST 3 (word)
28 LOAD_CONST 1 (0)
31 BINARY_SUBSCR
32 BINARY_SUBSCR
33 LOAD_ATTR 1 (append)
36 LOAD_FAST 3 (word)
39 CALL_FUNCTION 1
42 POP_TOP
43 JUMP_ABSOLUTE 16
>> 46 POP_BLOCK
>> 47 LOAD_CONST 0 (None)
50 RETURN_VALUE
TIME: 0.0842</pre>
</div>
<p>A further optimization, suggested by Brandon Rhodes, is to eliminate
the Python version of the <tt class="docutils literal"><span class="pre">for</span></tt> loop entirely. If we use
<a class="reference internal" href="../itertools/index.html#itertools-groupby"><em>itertools.groupby()</em></a> to arrange the input,
the iteration is moved to C. We can do this safely because we know
the inputs are already sorted. If you didn’t know they were sorted
you would need to sort them first.</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18</pre></div></td><td class="code"><div class="highlight"><pre><span class="c">#!/usr/bin/env python</span>
<span class="c"># encoding: utf-8</span>
<span class="kn">import</span> <span class="nn">operator</span>
<span class="kn">import</span> <span class="nn">itertools</span>
<span class="k">class</span> <span class="nc">Dictionary</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">words</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">by_letter</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">load_data</span><span class="p">(</span><span class="n">words</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">load_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">words</span><span class="p">):</span>
<span class="c"># Arrange by letter</span>
<span class="n">grouped</span> <span class="o">=</span> <span class="n">itertools</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="n">words</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="n">operator</span><span class="o">.</span><span class="n">itemgetter</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span>
<span class="c"># Save arranged sets of words</span>
<span class="bp">self</span><span class="o">.</span><span class="n">by_letter</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">((</span><span class="n">group</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">],</span> <span class="n">group</span><span class="p">)</span> <span class="k">for</span> <span class="n">group</span> <span class="ow">in</span> <span class="n">grouped</span><span class="p">)</span>
</pre></div>
</td></tr></table></div>
<p>The <a class="reference internal" href="../itertools/index.html#module-itertools" title="itertools: Iterator functions for efficient looping"><tt class="xref py py-mod docutils literal"><span class="pre">itertools</span></tt></a> version takes only 0.0543 seconds to run, just
over half of the original time.</p>
<div class="highlight-python"><pre>$ python dis_test_loop.py dis_eliminate_loop
15 0 LOAD_GLOBAL 0 (itertools)
3 LOAD_ATTR 1 (groupby)
6 LOAD_FAST 1 (words)
9 LOAD_CONST 1 ('key')
12 LOAD_GLOBAL 2 (operator)
15 LOAD_ATTR 3 (itemgetter)
18 LOAD_CONST 2 (0)
21 CALL_FUNCTION 1
24 CALL_FUNCTION 257
27 STORE_FAST 2 (grouped)
17 30 LOAD_GLOBAL 4 (dict)
33 LOAD_CONST 3 (<code object <genexpr> at 0x7e7b8, file "/Users/dhellmann/Documents/PyMOTW/dis/PyMOTW/dis/dis_eliminate_loop.py", line 17>)
36 MAKE_FUNCTION 0
39 LOAD_FAST 2 (grouped)
42 GET_ITER
43 CALL_FUNCTION 1
46 CALL_FUNCTION 1
49 LOAD_FAST 0 (self)
52 STORE_ATTR 5 (by_letter)
55 LOAD_CONST 0 (None)
58 RETURN_VALUE
TIME: 0.0543</pre>
</div>
</div>
<div class="section" id="compiler-optimizations">
<h2>Compiler Optimizations<a class="headerlink" href="#compiler-optimizations" title="Permalink to this headline">¶</a></h2>
<p>Disassembling compiled source also exposes some of the optimizations
made by the compiler. For example, literal expressions are folded
during compilation, when possible.</p>
<div class="highlight-python"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre> 1
2
3
4
5
6
7
8
9
10
11
12</pre></div></td><td class="code"><div class="highlight"><pre><span class="c">#!/usr/bin/env python</span>
<span class="c"># encoding: utf-8</span>
<span class="c"># Folded</span>
<span class="n">i</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">+</span> <span class="mi">2</span>
<span class="n">f</span> <span class="o">=</span> <span class="mf">3.4</span> <span class="o">*</span> <span class="mf">5.6</span>
<span class="n">s</span> <span class="o">=</span> <span class="s">'Hello,'</span> <span class="o">+</span> <span class="s">' World!'</span>
<span class="c"># Not folded</span>
<span class="n">I</span> <span class="o">=</span> <span class="n">i</span> <span class="o">*</span> <span class="mi">3</span> <span class="o">*</span> <span class="mi">4</span>
<span class="n">F</span> <span class="o">=</span> <span class="n">f</span> <span class="o">/</span> <span class="mi">2</span> <span class="o">/</span> <span class="mi">3</span>
<span class="n">S</span> <span class="o">=</span> <span class="n">s</span> <span class="o">+</span> <span class="s">'</span><span class="se">\n</span><span class="s">'</span> <span class="o">+</span> <span class="s">'Fantastic!'</span>
</pre></div>
</td></tr></table></div>
<p>The expressions on lines 5-7 can be computed at compilation time and
collapsed into single LOAD_CONST instructions because nothing in the
expression can change the way the operation is performed. That isn’t
true about lines 10-12. Because a variable is involved in those
expressions, and the variable might refer to an object that overloads
the operator involved, the evaluation has to be delayed to runtime.</p>
<div class="highlight-python"><pre>$ python -m dis dis_constant_folding.py
5 0 LOAD_CONST 11 (3)
3 STORE_NAME 0 (i)
6 6 LOAD_CONST 12 (19.04)
9 STORE_NAME 1 (f)
7 12 LOAD_CONST 13 ('Hello, World!')
15 STORE_NAME 2 (s)
10 18 LOAD_NAME 0 (i)
21 LOAD_CONST 6 (3)
24 BINARY_MULTIPLY
25 LOAD_CONST 7 (4)
28 BINARY_MULTIPLY
29 STORE_NAME 3 (I)
11 32 LOAD_NAME 1 (f)
35 LOAD_CONST 1 (2)
38 BINARY_DIVIDE
39 LOAD_CONST 6 (3)
42 BINARY_DIVIDE
43 STORE_NAME 4 (F)
12 46 LOAD_NAME 2 (s)
49 LOAD_CONST 8 ('\n')
52 BINARY_ADD
53 LOAD_CONST 9 ('Fantastic!')
56 BINARY_ADD
57 STORE_NAME 5 (S)
60 LOAD_CONST 10 (None)
63 RETURN_VALUE</pre>
</div>
<div class="admonition-see-also admonition seealso">
<p class="first admonition-title">See also</p>
<dl class="last docutils">
<dt><a class="reference external" href="http://docs.python.org/library/dis.html">dis</a></dt>
<dd>The standard library documentation for this module, including
the list of <a class="reference external" href="http://docs.python.org/library/dis.html#python-bytecode-instructions">bytecode instructions</a>.</dd>
<dt><em>Python Essential Reference</em>, 4th Edition, David M. Beazley</dt>
<dd><a class="reference external" href="http://www.informit.com/store/product.aspx?isbn=0672329786">http://www.informit.com/store/product.aspx?isbn=0672329786</a></dd>
<dt><a class="reference external" href="http://thomas.apestaart.org/log/?p=927">thomas.apestaart.org “Python Disassembly”</a></dt>
<dd>A short discussion of the difference between storing values in
a dictionary between Python 2.5 and 2.6.</dd>
<dt><a class="reference external" href="http://stackoverflow.com/questions/869229/why-is-looping-over-range-in-python-faster-than-using-a-while-loop">Why is looping over range() in Python faster than using a while loop?</a></dt>
<dd>A discussion on StackOverflow.com comparing 2 looping examples
via their disassembled bytecodes.</dd>
<dt><a class="reference external" href="http://code.activestate.com/recipes/277940/">Decorator for binding constants at compile time</a></dt>
<dd>Python Cookbook recipe by Raymond Hettinger and Skip Montanaro
with a function decorator that re-writes the bytecodes for a
function to insert global constants to avoid runtime name
lookups.</dd>
</dl>
</div>
</div>
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