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import hashlib, random, timeit | |
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<div class="section" id="module-random"> | |
<h1>9.6. <tt class="xref docutils literal"><span class="pre">random</span></tt> — Generate pseudo-random numbers<a class="headerlink" href="#module-random" title="Permalink to this headline">¬∂</a></h1> | |
<p>This module implements pseudo-random number generators for various | |
distributions.</p> | |
<div class="admonition-see-also admonition seealso"> | |
<p class="first admonition-title">See also</p> | |
<p class="last">Latest version of the <a class="reference external" href="http://svn.python.org/view/python/branches/release27-maint/Lib/random.py?view=markup">random module Python source code</a></p> | |
</div> | |
<p>For integers, uniform selection from a range. For sequences, uniform selection | |
of a random element, a function to generate a random permutation of a list | |
in-place, and a function for random sampling without replacement.</p> | |
<p>On the real line, there are functions to compute uniform, normal (Gaussian), | |
lognormal, negative exponential, gamma, and beta distributions. For generating | |
distributions of angles, the von Mises distribution is available.</p> | |
<p>Almost all module functions depend on the basic function <a title="random.random" class="reference internal" href="#random.random"><tt class="xref docutils literal"><span class="pre">random()</span></tt></a>, which | |
generates a random float uniformly in the semi-open range [0.0, 1.0). Python | |
uses the Mersenne Twister as the core generator. It produces 53-bit precision | |
floats and has a period of 2**19937-1. The underlying implementation in C is | |
both fast and threadsafe. The Mersenne Twister is one of the most extensively | |
tested random number generators in existence. However, being completely | |
deterministic, it is not suitable for all purposes, and is completely unsuitable | |
for cryptographic purposes.</p> | |
<p>The functions supplied by this module are actually bound methods of a hidden | |
instance of the <tt class="xref docutils literal"><span class="pre">random.Random</span></tt> class. You can instantiate your own | |
instances of <tt class="xref docutils literal"><span class="pre">Random</span></tt> to get generators that don’t share state. This is | |
especially useful for multi-threaded programs, creating a different instance of | |
<tt class="xref docutils literal"><span class="pre">Random</span></tt> for each thread, and using the <a title="random.jumpahead" class="reference internal" href="#random.jumpahead"><tt class="xref docutils literal"><span class="pre">jumpahead()</span></tt></a> method to make | |
it likely that the generated sequences seen by each thread don’t overlap.</p> | |
<p>Class <tt class="xref docutils literal"><span class="pre">Random</span></tt> can also be subclassed if you want to use a different | |
basic generator of your own devising: in that case, override the <a title="random.random" class="reference internal" href="#random.random"><tt class="xref docutils literal"><span class="pre">random()</span></tt></a>, | |
<a title="random.seed" class="reference internal" href="#random.seed"><tt class="xref docutils literal"><span class="pre">seed()</span></tt></a>, <a title="random.getstate" class="reference internal" href="#random.getstate"><tt class="xref docutils literal"><span class="pre">getstate()</span></tt></a>, <a title="random.setstate" class="reference internal" href="#random.setstate"><tt class="xref docutils literal"><span class="pre">setstate()</span></tt></a> and <a title="random.jumpahead" class="reference internal" href="#random.jumpahead"><tt class="xref docutils literal"><span class="pre">jumpahead()</span></tt></a> methods. | |
Optionally, a new generator can supply a <a title="random.getrandbits" class="reference internal" href="#random.getrandbits"><tt class="xref docutils literal"><span class="pre">getrandbits()</span></tt></a> method — this | |
allows <a title="random.randrange" class="reference internal" href="#random.randrange"><tt class="xref docutils literal"><span class="pre">randrange()</span></tt></a> to produce selections over an arbitrarily large range.</p> | |
<p class="versionadded"> | |
<span class="versionmodified">New in version 2.4: </span>the <a title="random.getrandbits" class="reference internal" href="#random.getrandbits"><tt class="xref docutils literal"><span class="pre">getrandbits()</span></tt></a> method.</p> | |
<p>As an example of subclassing, the <tt class="xref docutils literal"><span class="pre">random</span></tt> module provides the | |
<a title="random.WichmannHill" class="reference internal" href="#random.WichmannHill"><tt class="xref docutils literal"><span class="pre">WichmannHill</span></tt></a> class that implements an alternative generator in pure | |
Python. The class provides a backward compatible way to reproduce results from | |
earlier versions of Python, which used the Wichmann-Hill algorithm as the core | |
generator. Note that this Wichmann-Hill generator can no longer be recommended: | |
its period is too short by contemporary standards, and the sequence generated is | |
known to fail some stringent randomness tests. See the references below for a | |
recent variant that repairs these flaws.</p> | |
<p class="versionchanged"> | |
<span class="versionmodified">Changed in version 2.3: </span>MersenneTwister replaced Wichmann-Hill as the defaul | |
29 37142 29 10874 0 0 5729 0 0:00:06 0:00:01 0:00:05 16157t generator.</p> | |
<p>The <tt class="xref docutils literal"><span class="pre">random</span></tt> module also provides the <a title="random.SystemRandom" class="reference internal" href="#random.SystemRandom"><tt class="xref docutils literal"><span class="pre">SystemRandom</span></tt></a> class which | |
uses the system function <a title="os.urandom" class="reference external" href="os.html#os.urandom"><tt class="xref docutils literal"><span class="pre">os.urandom()</span></tt></a> to generate random numbers | |
from sources provided by the operating system.</p> | |
<p>Bookkeeping functions:</p> | |
<dl class="function"> | |
<dt id="random.seed"> | |
<tt class="descclassname">random.</tt><tt class="descname">seed</tt><big>(</big><span class="optional">[</span><em>x</em><span class="optional">]</span><big>)</big><a class="headerlink" href="#random.seed" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Initialize the basic random number generator. Optional argument <em>x</em> can be any | |
<a class="reference external" href="../glossary.html#term-hashable"><em class="xref">hashable</em></a> object. If <em>x</em> is omitted or <tt class="xref docutils literal"><span class="pre">None</span></tt>, current system time is used; | |
current system time is also used to initialize the generator when the module is | |
first imported. If randomness sources are provided by the operating system, | |
they are used instead of the system time (see the <a title="os.urandom" class="reference external" href="os.html#os.urandom"><tt class="xref docutils literal"><span class="pre">os.urandom()</span></tt></a> function | |
for details on availability).</p> | |
<p class="versionchanged"> | |
<span class="versionmodified">Changed in version 2.4: </span>formerly, operating system resources were not used.</p> | |
</dd></dl> | |
<dl class="function"> | |
<dt id="random.getstate"> | |
<tt class="descclassname">random.</tt><tt class="descname">getstate</tt><big>(</big><big>)</big><a class="headerlink" href="#random.getstate" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Return an object capturing the current internal state of the generator. This | |
object can be passed to <a title="random.setstate" class="reference internal" href="#random.setstate"><tt class="xref docutils literal"><span class="pre">setstate()</span></tt></a> to restore the state.</p> | |
<p class="versionadded"> | |
<span class="versionmodified">New in version 2.1.</span></p> | |
<p class="versionchanged"> | |
<span class="versionmodified">Changed in version 2.6: </span>State values produced in Python 2.6 cannot be loaded into earlier versions.</p> | |
</dd></dl> | |
<dl class="function"> | |
<dt id="random.setstate"> | |
<tt class="descclassname">random.</tt><tt class="descname">setstate</tt><big>(</big><em>state</em><big>)</big><a class="headerlink" href="#random.setstate" title="Permalink to this definition">¶</a></dt> | |
<dd><p><em>state</em> should have been obtained from a previous call to <a title="random.getstate" class="reference internal" href="#random.getstate"><tt class="xref docutils literal"><span class="pre">getstate()</span></tt></a>, and | |
<a title="random.setstate" class="reference internal" href="#random.setstate"><tt class="xref docutils literal"><span class="pre">setstate()</span></tt></a> restores the internal state of the generator to what it was at | |
the time <a title="random.setstate" class="reference internal" href="#random.setstate"><tt class="xref docutils literal"><span class="pre">setstate()</span></tt></a> was called.</p> | |
<p class="versionadded"> | |
<span class="versionmodified">New in version 2.1.</span></p> | |
</dd></dl> | |
<dl class="function"> | |
<dt id="random.jumpahead"> | |
<tt class="descclassname">random.</tt><tt class="descname">jumpahead</tt><big>(</big><em>n</em><big>)</big><a class="headerlink" href="#random.jumpahead" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Change the internal state to one different from and likely far away from the | |
current state. <em>n</em> is a non-negative integer which is used to scramble the | |
current state vector. This is most useful in multi-threaded programs, in | |
conjunction with multiple instances of the <tt class="xref docutils literal"><span class="pre">Random</span></tt> class: | |
<a title="random.setstate" class="reference internal" href="#random.setstate"><tt class="xref docutils literal"><span class="pre">setstate()</span></tt></a> or <a title="random.seed" class="reference internal" href="#random.seed"><tt class="xref docutils literal"><span class="pre">seed()</span></tt></a> can be used to force all instances into the | |
same internal state, and then <a title="random.jumpahead" class="reference internal" href="#random.jumpahead"><tt class="xref docutils literal"><span class="pre">jumpahead()</span></tt></a> can be used to force the | |
instances’ states far apart.</p> | |
<p class="versionadded"> | |
<span class="versionmodified">New in version 2.1.</span></p> | |
<p class="versionchanged"> | |
<span class="versionmodified">Changed in version 2.3: </span>Instead of jumping to a specific state, <em>n</em> steps ahead, <tt class="docutils literal"><span class="pre">jumpahead(n)</span></tt> | |
jumps to another state likely to be separated by many steps.</p> | |
</dd></dl> | |
<dl class="function"> | |
<dt id="random.getrandbits"> | |
<tt class="descclassname">random.</tt><tt class="descname">getrandbits</tt><big>(</big><em>k</em><big>)</big><a class="headerlink" href="#random.getrandbits" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Returns a python <a title="long" class="reference external" href="functions.html#long"><tt class="xref docutils literal"><span class="pre">long</span></tt></a> int with <em>k</em> random bits. This method is supplied | |
with the MersenneTwister generator and some other generators may also provide it | |
as an optional part of the API. When available, <a title="random.getrandbits" class="reference internal" href="#random.getrandbits"><tt class="xref docutils literal"><span class="pre">getrandbits()</span></tt></a> enables | |
<a title="random.randrange" class="reference internal" href="#random.randrange"><tt class="xref docutils literal"><span class="pre">randrange()</span></tt></a> to handle arbitrarily large ranges.</p> | |
<p class="versionadded"> | |
<span class="versionmodified">New in version 2.4.</span></p> | |
</dd></dl> | |
<p>Functions for integers:</p> | |
<dl class="function"> | |
<dt id="random.randrange"> | |
<tt class="descclassname">random.</tt><tt class="descname">randrange</tt><big>(</big><span class="optional">[</span><em>start</em><span class="optional">]</span>, <em>stop</em><span class="optional">[</span>, <em>step</em><span class="optional">]</span><big>)</big><a class="headerlink" href="#random.randrange" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Return a randomly selected element from <tt class="docutils literal"><span class="pre">range(start,</span> <span class="pre">stop,</span> <span class="pre">step)</span></tt>. This is | |
equivalent to <tt class="docutils literal"><span class="pre">choice(range(start,</span> <span class="pre">stop,</span> <span class="pre">step))</span></tt>, but doesn’t actually build a | |
range object.</p> | |
<p class="versionadded"> | |
<span class="versionmodified">New in version 1.5.2.</span></p> | |
</dd></dl> | |
<dl class="function"> | |
<dt id="random.randint"> | |
<tt class="descclassname">random.</tt><tt class="descname">randint</tt><big>(</big><em>a</em>, <em>b</em><big>)</big><a class="headerlink" href="#random.randint" title="Permalink to this definition">¶</a></dt> | |
<dd>Return a random integer <em>N</em> such that <tt class="docutils literal"><span class="pre">a</span> <span class="pre"><=</span> <span class="pre">N</span> <span class="pre"><=</span> <span class="pre">b</span></tt>.</dd></dl> | |
<p>Functions for sequences:</p> | |
<dl class="function"> | |
<dt id="random.choice"> | |
<tt class="descclassname">random.</tt><tt class="descname">choice</tt><big>(</big><em>seq</em><big>)</big><a class="headerlink" href="#random.choice" title="Permalink to this definition">¶</a></dt> | |
<dd>Return a random element from the non-empty sequence <em>seq</em>. If <em>seq</em> is empty, | |
raises <a title="exceptions.IndexError" class="reference external" href="exceptions.html#exceptions.IndexError"><tt class="xref docutils literal"><span class="pre">IndexError</span></tt></a>.</dd></dl> | |
<dl class="function"> | |
<dt id="random.shuffle"> | |
<tt class="descclassname">random.</tt><tt class="descname">shuffle</tt><big>(</big><em>x</em><span class="optional">[</span>, <em>random</em><span class="optional">]</span><big>)</big><a class="headerlink" href="#random.shuffle" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Shuffle the sequence <em>x</em> in place. The optional argument <em>random</em> is a | |
0-argument function returning a random float in [0.0, 1.0); by default, this is | |
the function <a title="random.random" class="reference internal" href="#random.random"><tt class="xref docutils literal"><span class="pre">random()</span></tt></a>.</p> | |
<p>Note that for even rather small <tt class="docutils literal"><span class="pre">len(x)</span></tt>, the total number of permutations of | |
<em>x</em> is larger than the period of most random number generators; this implies | |
that most permutations of a long sequence can never be generated.</p> | |
</dd></dl> | |
<dl class="function"> | |
<dt id="random.sample"> | |
<tt class="descclassname">random.</tt><tt class="descname">sample</tt><big>(</big><em>population</em>, <em>k</em><big>)</big><a class="headerlink" href="#random.sample" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Return a <em>k</em> length list of unique elements chosen from the population sequence. | |
Used for random sampling without replacement.</p> | |
<p class="versionadded"> | |
<span class="versionmodified">New in version 2.3.</span></p> | |
<p>Returns a new list containing elements from the population while leaving the | |
original population unchanged. The resulting list is in selection order so that | |
all sub-slices will also be valid random samples. This allows raffle winners | |
(the sample) to be partitioned into grand prize and second place winners (the | |
subslices).</p> | |
<p>Members of the population need not be <a class="reference external" href="../glossary.html#term-hashable"><em class="xref">hashable</em></a> or unique. If the population | |
contains repeats, then each occurrence is a possible selection in the sample.</p> | |
<p>To choose a sample from a range of integers, use an <a title="xrange" class="reference external" href="functions.html#xrange"><tt class="xref docutils literal"><span class="pre">xrange()</span></tt></a> object as an | |
argument. This is especially fast and space efficient for sampling from a large | |
population: <tt class="docutils literal"><span class="pre">sample(xrange(10000000),</span> <span class="pre">60)</span></tt>.</p> | |
</dd></dl> | |
<p>The following functions generate specific real-valued distributions. Function | |
parameters are named after the corresponding variables in the distribution’s | |
equation, as used in common mathematical practice; most of these equations can | |
be found in any statistics text.</p> | |
<dl class="function"> | |
<dt id="random.random"> | |
<tt class="descclassname">random.</tt><tt class="descname">random</tt><big>(</big><big>)</big><a class="headerlink" href="#random.random" title="Permalink to this definition">¶</a></dt> | |
<dd>Return the next random floating point number in the range [0.0, 1.0).</dd></dl> | |
<dl class="function"> | |
<dt id="random.uniform"> | |
<tt class="descclassname">random.</tt><tt class="descname">uniform</tt><big>(</big><em>a</em>, <em>b</em><big>)</big><a class="headerlink" href="#random.uniform" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Return a random floating point number <em>N</em> such that <tt class="docutils literal"><span class="pre">a</span> <span class="pre"><=</span> <span class="pre">N</span> <span class="pre"><=</span> <span class="pre">b</span></tt> for | |
<tt class="docutils literal"><span class="pre">a</span> <span class="pre"><=</span> <span class="pre">b</span></tt> and <tt class="docutils literal"><span class="pre">b</span> <span class="pre"><=</span> <span class="pre">N</span> <span class="pre"><=</span> <span class="pre">a</span></tt> for <tt class="docutils literal"><span class="pre">b</span> <span class="pre"><</span> <span class="pre">a</span></tt>.</p> | |
<p>The end-point value <tt class="docutils literal"><span class="pre">b</span></tt> may or may not be included in the range | |
depending on floating-point rounding in the equation <tt class="docutils literal"><span class="pre">a</span> <span class="pre">+</span> <span class="pre">(b-a)</span> <span class="pre">*</span> <span class="pre">random()</span></tt>.</p> | |
</dd></dl> | |
<dl class="function"> | |
<dt id="random.triangular"> | |
<tt class="descclassname">random.</tt><tt class="descname">triangular</tt><big>(</big><em>low</em>, <em>high</em>, <em>mode</em><big>)</big><a class="headerlink" href="#random.triangular" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Return a random floating point number <em>N</em> such that <tt class="docutils literal"><span class="pre">low</span> <span class="pre"><=</span> <span class="pre">N</span> <span class="pre"><=</span> <span class="pre">high</span></tt> and | |
with the specified <em>mode</em> between those bounds. The <em>low</em> and <em>high</em> bounds | |
default to zero and one. The <em>mode</em> argument defaults to the midpoint | |
between the bounds, giving a symmetric distribution.</p> | |
<p class="versionadded"> | |
<span class="versionmodified">New in version 2.6.</span></p> | |
</dd></dl> | |
<dl class="function"> | |
<dt id="random.betavariate"> | |
<tt class="descclassname">random.</tt><tt class="descname">betavariate</tt><big>(</big><em>alpha</em>, <em>beta</em><big>)</big><a class="headerlink" href="#random.betavariate" title="Permalink to this definition">¶</a></dt> | |
<dd>Beta distribution. Conditions on the parameters are <tt class="docutils literal"><span class="pre">alpha</span> <span class="pre">></span> <span class="pre">0</span></tt> and | |
<tt class="docutils literal"><span class="pre">beta</span> <span class="pre">></span> <span class="pre">0</span></tt>. Returned values range between 0 and 1.</dd></dl> | |
<dl class="function"> | |
<dt id="random.expovariate"> | |
<tt class="descclassname">random.</tt><tt class="descname">expovariate</tt><big>(</big><em>lambd</em><big>)</big><a class="headerlink" href="#random.expovariate" title="Permalink to this definition">¶</a></dt> | |
<dd>Exponential distribution. <em>lambd</em> is 1.0 divided by the desired | |
mean. It should be nonzero. (The parameter would be called | |
“lambda”, but that is a reserved word in Python.) Returned values | |
range from 0 to positive infinity if <em>lambd</em> is positive, and from | |
negative infinity to 0 if <em>lambd</em> is negative.</dd></dl> | |
<dl class="function"> | |
<dt id="random.gammavariate"> | |
<tt class="descclassname">random.</tt><tt class="descname">gammavariate</tt><big>(</big><em>alpha</em>, <em>beta</em><big>)</big><a class="headerlink" href="#random.gammavariate" title="Permalink to this definition">¶</a></dt> | |
<dd>Gamma distribution. (<em>Not</em> the gamma function!) Conditions on the | |
parameters are <tt class="docutils literal"><span class="pre">alpha</span> <span class="pre">></span> <span class="pre">0</span></tt> and <tt class="docutils literal"><span class="pre">beta</span> <span class="pre">></span> <span class="pre">0</span></tt>.</dd></dl> | |
<dl class="function"> | |
<dt id="random.gauss"> | |
<tt class="descclassname">random.</tt><tt class="descname">gauss</tt><big>(</big><em>mu</em>, <em>sigma</em><big>)</big><a class="headerlink" href="#random.gauss" title="Permalink to this definition">¶</a></dt> | |
<dd>Gaussian distribution. <em>mu</em> is the mean, and <em>sigma</em> is the standard | |
deviation. This is slightly faster than the <a title="random.normalvariate" class="reference internal" href="#random.normalvariate"><tt class="xref docutils literal"><span class="pre">normalvariate()</span></tt></a> function | |
defined below.</dd></dl> | |
<dl class="function"> | |
<dt id="random.lognormvariate"> | |
<tt class="descclassname">random.</tt><tt class="descname">lognormvariate</tt><big>(</big><em>mu</em>, <em>sigma</em><big>)</big><a class="headerlink" href="#random.lognormvariate" title="Permalink to this definition">¶</a></dt> | |
<dd>Log normal distribution. If you take the natural logarithm of this | |
distribution, you’ll get a normal distribution with mean <em>mu</em> and standard | |
deviation <em>sigma</em>. <em>mu</em> can have any value, and <em>sigma</em> must be greater than | |
zero.</dd></dl> | |
<dl class="function"> | |
<dt id="random.normalvariate"> | |
<tt class="descclassname">random.</tt><tt class="descname">normalvariate</tt><big>(</big><em>mu</em>, <em>sigma</em><big>)</big><a class="headerlink" href="#random.normalvariate" title="Permalink to this definition">¶</a></dt> | |
<dd>Normal distribution. <em>mu</em> is the mean, and <em>sigma</em> is the standard deviation.</dd></dl> | |
<dl class="function"> | |
<dt id="random.vonmisesvariate"> | |
<tt class="descclassname">random.</tt><tt class="descname">vonmisesvariate</tt><big>(</big><em>mu</em>, <em>kappa</em><big>)</big><a class="headerlink" href="#random.vonmisesvariate" title="Permalink to this definition">¶</a></dt> | |
<dd><em>mu</em> is the mean angle, expressed in radians between 0 and 2*<em>pi</em>, and <em>kappa</em> | |
is the concentration parameter, which must be greater than or equal to zero. If | |
<em>kappa</em> is equal to zero, this distribution reduces to a uniform random angle | |
over the range 0 to 2*<em>pi</em>.</dd></dl> | |
<dl class="function"> | |
<dt id="random.paretovariate"> | |
<tt class="descclassname">random.</tt><tt class="descname">paretovariate</tt><big>(</big><em>alpha</em><big>)</big><a class="headerlink" href="#random.paretovariate" title="Permalink to this definition">¶</a></dt> | |
<dd>Pareto distribution. <em>alpha</em> is the shape parameter.</dd></dl> | |
<dl class="function"> | |
<dt id="random.weibullvariate"> | |
<tt class="descclassname">random.</tt><tt class="descname">weibullvariate</tt><big>(</big><em>alpha</em>, <em>beta</em><big>)</big><a class="headerlink" href="#random.weibullvariate" title="Permalink to this definition">¶</a></dt> | |
<dd>Weibull distribution. <em>alpha</em> is the scale parameter and <em>beta</em> is the shape | |
parameter.</dd></dl> | |
<p>Alternative Generators:</p> | |
<dl class="class"> | |
<dt id="random.WichmannHill"> | |
<em class="property">class </em><tt class="descclassname">random.</tt><tt class="descname">WichmannHill</tt><big>(</big><span class="optional">[</span><em>seed</em><span class="optional">]</span><big>)</big><a class="headerlink" href="#random.WichmannHill" title="Permalink to this definition">¶</a></dt> | |
<dd>Class that implements the Wichmann-Hill algorithm as the core generator. Has all | |
of the same methods as <tt class="xref docutils literal"><span class="pre">Random</span></tt> plus the <a title="random.whseed" class="reference internal" href="#random.whseed"><tt class="xref docutils literal"><span class="pre">whseed()</span></tt></a> method described | |
below. Because this class is implemented in pure Python, it is not threadsafe | |
and may require locks between calls. The period of the generator is | |
6,953,607,871,644 which is small enough to require care that two independent | |
random sequences do not overlap.</dd></dl> | |
<dl class="function"> | |
<dt id="random.whseed"> | |
<tt class="descclassname">random.</tt><tt class="descname">whseed</tt><big>(</big><span class="optional">[</span><em>x</em><span class="optional">]</span><big>)</big><a class="headerlink" href="#random.whseed" title="Permalink to this definition">¶</a></dt> | |
<dd>This is obsolete, supplied for bit-level compatibility with versions of Python | |
prior to 2.1. See <a title="random.seed" class="reference internal" href="#random.seed"><tt class="xref docutils literal"><span class="pre">seed()</span></tt></a> for details. <a title="random.whseed" class="reference internal" href="#random.whseed"><tt class="xref docutils literal"><span class="pre">whseed()</span></tt></a> does not guarantee | |
that distinct integer arguments yield distinct internal states, and can yield no | |
more than about 2**24 distinct internal states in all.</dd></dl> | |
<dl class="class"> | |
<dt id="random.SystemRandom"> | |
<em class="property">class </em><tt class="descclassname">random.</tt><tt class="descname">SystemRandom</tt><big>(</big><span class="optional">[</span><em>seed</em><span class="optional">]</span><big>)</big><a class="headerlink" href="#random.SystemRandom" title="Permalink to this definition">¶</a></dt> | |
<dd><p>Class that uses the <a title="os.urandom" class="reference external" href="os.html#os.urandom"><tt class="xref docutils literal"><span class="pre">os.urandom()</span></tt></a> function for generating random numbers | |
from sources provided by the operating system. Not available on all systems. | |
Does not rely on software state and sequences are not reproducible. Accordingly, | |
the <a title="random.seed" class="reference internal" href="#random.seed"><tt class="xref docutils literal"><span class="pre">seed()</span></tt></a> and <a title="random.jumpahead" class="reference internal" href="#random.jumpahead"><tt class="xref docutils literal"><span class="pre">jumpahead()</span></tt></a> methods have no effect and are ignored. | |
The <a title="random.getstate" class="reference internal" href="#random.getstate"><tt class="xref docutils literal"><span class="pre">getstate()</span></tt></a> and <a title="random.setstate" class="reference internal" href="#random.setstate"><tt class="xref docutils literal"><span class="pre">setstate()</span></tt></a> methods raise | |
<a title="exceptions.NotImplementedError" class="reference external" href="exceptions.html#exceptions.NotImplementedError"><tt class="xref docutils literal"><span class="pre">NotImplementedError</span></tt></a> if called.</p> | |
<p class="versionadded"> | |
<span class="versionmodified">New in version 2.4.</span></p> | |
</dd></dl> | |
<p>Examples of basic usage:</p> | |
<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="n">random</span><span class="o">.</span><span class="n">random</span><span class="p">()</span> <span class="c"># Random float x, 0.0 <= x < 1.0</span> | |
<span class="go">0.37444887175646646</span> | |
<span class="gp">>>> </span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> <span class="c"># Random float x, 1.0 <= x < 10.0</span> | |
<span class="go">1.1800146073117523</span> | |
<span class="gp">>>> </span><span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span> <span class="c"># Integer from 1 to 10, endpoints included</span> | |
<span class="go">7</span> | |
<span class="gp">>>> </span><span class="n">random</span><span class="o">.</span><span class="n">randrange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">101</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> <span class="c"># Even integer from 0 to 100</span> | |
<span class="go">26</span> | |
<span class="gp">>>> </span><span class="n">random</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="s">'abcdefghij'</span><span class="p">)</span> <span class="c"># Choose a random element</span> | |
<span class="go">'c'</span> | |
<span class="gp">>>> </span><span class="n">items</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">,</span> <span class="mi">7</span><span class="p">]</span> | |
<span class="gp">>>> </span><span class="n">random</span><span class="o">.</span><span class="n">shuffle</span><span class="p">(</span><span class="n">items</span><span class="p">)</span> | |
<span class="gp">>>> </span><span class="n">items</span> | |
<span class="go">[7, 3, 2, 5, 6, 4, 1]</span> | |
<span class="gp">>>> </span><span class="n">random</span><span class="o">.</span><span class="n">sample</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="mi">3</span><span class="p">)</span> <span class="c"># Choose 3 elements</span> | |
<span class="go">[4, 1, 5]</span> | |
</pre></div> | |
</div> | |
<div class="admonition-see-also admonition seealso"> | |
<p class="first admonition-title">See also</p> | |
<p>M. Matsumoto and T. Nishimura, “Mersenne Twister: A 623-dimensionally | |
equidistributed uniform pseudorandom number generator”, ACM Transactions on | |
Modeling and Computer Simulation Vol. 8, No. 1, January pp.3-30 1998.</p> | |
<p>Wichmann, B. A. & Hill, I. D., “Algorithm AS 183: An efficient and portable | |
pseudo-random number generator”, Applied Statistics 31 (1982) 188-190.</p> | |
<p class="last"><a class="reference external" href="http://code.activestate.com/recipes/576707/">Complementary-Multiply-with-Carry recipe</a> for a compatible alternative | |
random number generator with a long period and comparatively simple update | |
operations.</p> | |
</div> | |
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""" | |
N = 1000 | |
print 'Etag for python.org document (%d bytes):' % len(document), timeit.timeit(lambda: hash_it(document), number=N) | |
new_document = generate_it(len(document)) | |
print 'Etag for random document (%d bytes)' % len(new_document), timeit.timeit(lambda: hash_it(new_document), number=N) | |
N = 1000 | |
from django.utils.text import compress_string | |
print 'Gzip for python.org document (%d bytes):' % len(document), timeit.timeit(lambda: compress_string(document), number=N) | |
print 'Gzip for random document (%d bytes)' % len(new_document), timeit.timeit(lambda: compress_string(new_document), number=N) | |
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