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<section id="numpy-random-randomstate-randint">
<h1>numpy.random.RandomState.randint<a class="headerlink" href="#numpy-random-randomstate-randint" title="Link to this heading">#</a></h1>
<p>method</p>
<dl class="py method">
<dt class="sig sig-object py" id="numpy.random.RandomState.randint">
<span class="sig-prename descclassname"><span class="pre">random.RandomState.</span></span><span class="sig-name descname"><span class="pre">randint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">low</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">int</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#numpy.random.RandomState.randint" title="Link to this definition">#</a></dt>
<dd><p>Return random integers from <em class="xref py py-obj">low</em> (inclusive) to <em class="xref py py-obj">high</em> (exclusive).</p>
<p>Return random integers from the “discrete uniform” distribution of
the specified dtype in the “half-open” interval [<em class="xref py py-obj">low</em>, <em class="xref py py-obj">high</em>). If
<em class="xref py py-obj">high</em> is None (the default), then results are from [0, <em class="xref py py-obj">low</em>).</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>New code should use the <a class="reference internal" href="numpy.random.Generator.integers.html#numpy.random.Generator.integers" title="numpy.random.Generator.integers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">integers</span></code></a>
method of a <a class="reference internal" href="../generator.html#numpy.random.Generator" title="numpy.random.Generator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Generator</span></code></a> instance instead;
please see the <a class="reference internal" href="../index.html#random-quick-start"><span class="std std-ref">Quick start</span></a>.</p>
</div>
<dl class="field-list">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><dl>
<dt><strong>low</strong><span class="classifier">int or array-like of ints</span></dt><dd><p>Lowest (signed) integers to be drawn from the distribution (unless
<code class="docutils literal notranslate"><span class="pre">high=None</span></code>, in which case this parameter is one above the
<em>highest</em> such integer).</p>
</dd>
<dt><strong>high</strong><span class="classifier">int or array-like of ints, optional</span></dt><dd><p>If provided, one above the largest (signed) integer to be drawn
from the distribution (see above for behavior if <code class="docutils literal notranslate"><span class="pre">high=None</span></code>).
If array-like, must contain integer values</p>
</dd>
<dt><strong>size</strong><span class="classifier">int or tuple of ints, optional</span></dt><dd><p>Output shape. If the given shape is, e.g., <code class="docutils literal notranslate"><span class="pre">(m,</span> <span class="pre">n,</span> <span class="pre">k)</span></code>, then
<code class="docutils literal notranslate"><span class="pre">m</span> <span class="pre">*</span> <span class="pre">n</span> <span class="pre">*</span> <span class="pre">k</span></code> samples are drawn. Default is None, in which case a
single value is returned.</p>
</dd>
<dt><strong>dtype</strong><span class="classifier">dtype, optional</span></dt><dd><p>Desired dtype of the result. Byteorder must be native.
The default value is long.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>This function defaults to the C-long dtype, which is 32bit on windows
and otherwise 64bit on 64bit platforms (and 32bit on 32bit ones).
Since NumPy 2.0, NumPy’s default integer is 32bit on 32bit platforms
and 64bit on 64bit platforms. Which corresponds to <em class="xref py py-obj">np.intp</em>.
(<em class="xref py py-obj">dtype=int</em> is not the same as in most NumPy functions.)</p>
</div>
</dd>
</dl>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><dl class="simple">
<dt><strong>out</strong><span class="classifier">int or ndarray of ints</span></dt><dd><p><a class="reference internal" href="../../generated/numpy.size.html#numpy.size" title="numpy.size"><code class="xref py py-obj docutils literal notranslate"><span class="pre">size</span></code></a>-shaped array of random integers from the appropriate
distribution, or a single such random int if <a class="reference internal" href="../../generated/numpy.size.html#numpy.size" title="numpy.size"><code class="xref py py-obj docutils literal notranslate"><span class="pre">size</span></code></a> not provided.</p>
</dd>
</dl>
</dd>
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<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><a class="reference internal" href="numpy.random.RandomState.random_integers.html#numpy.random.RandomState.random_integers" title="numpy.random.RandomState.random_integers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random_integers</span></code></a></dt><dd><p>similar to <a class="reference internal" href="#numpy.random.RandomState.randint" title="numpy.random.RandomState.randint"><code class="xref py py-obj docutils literal notranslate"><span class="pre">randint</span></code></a>, only for the closed interval [<em class="xref py py-obj">low</em>, <em class="xref py py-obj">high</em>], and 1 is the lowest value if <em class="xref py py-obj">high</em> is omitted.</p>
</dd>
<dt><a class="reference internal" href="numpy.random.Generator.integers.html#numpy.random.Generator.integers" title="numpy.random.Generator.integers"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random.Generator.integers</span></code></a></dt><dd><p>which should be used for new code.</p>
</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="e4a7b47f-e078-457b-ab72-bcc025d395f5">
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<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="go">array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0]) # random</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</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="n">size</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="go">array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])</span>
</pre></div>
</div>
<p>Generate a 2 x 4 array of ints between 0 and 4, inclusive:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="go">array([[4, 0, 2, 1], # random</span>
<span class="go"> [3, 2, 2, 0]])</span>
</pre></div>
</div>
<p>Generate a 1 x 3 array with 3 different upper bounds</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">np</span><span class="o">.</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="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">10</span><span class="p">])</span>
<span class="go">array([2, 2, 9]) # random</span>
</pre></div>
</div>
<p>Generate a 1 by 3 array with 3 different lower bounds</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">np</span><span class="o">.</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">5</span><span class="p">,</span> <span class="mi">7</span><span class="p">],</span> <span class="mi">10</span><span class="p">)</span>
<span class="go">array([9, 8, 7]) # random</span>
</pre></div>
</div>
<p>Generate a 2 by 4 array using broadcasting with dtype of uint8</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">np</span><span class="o">.</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">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">7</span><span class="p">],</span> <span class="p">[[</span><span class="mi">10</span><span class="p">],</span> <span class="p">[</span><span class="mi">20</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
<span class="go">array([[ 8, 6, 9, 7], # random</span>
<span class="go"> [ 1, 16, 9, 12]], dtype=uint8)</span>
</pre></div>
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