* **Enter() should lock the resources and optionally return an object.**

* **Exit() should release the resources.**

* **Any exception that happens inside the with block is passed to the exit() method.**

import operator as op

<bool> = op.not_(<obj>) # or, and, not (or/and missing)

<obj> = op.or_/xor/and_(<int/set>, <int/set>) # |, ^, &

<int> = op.lshift/rshift(<int>, <int>) # <<, >>

<obj> = op.add/sub/mul/truediv/floordiv/mod(<obj>, <obj>) # +, -, *, /, //, %

<array> = np.copy/abs/sqrt/log/int64(<array>) # Returns new array of the same shape.

<array> = np.apply_along_axis(<func>, axis, <array>) # Func can return a scalar or array.

(<span class="hljs-number">1</span>, <span class="hljs-number">2</span>, <span class="hljs-number">3</span>)

<div><h3 id="contextmanager">Context Manager</h3><ul>

<li><strong>Enter() should lock the resources and optionally return an object.</strong></li>

<li><strong>Exit() should release the resources.</strong></li>

<li><strong>Any exception that happens inside the with block is passed to the exit() method.</strong></li>

<div><h2 id="operator"><a href="#operator" name="operator">#</a>Operator</h2><p><strong>Module of functions that provide the functionality of operators. Functions are ordered by operator precedence, starting with least binding.</strong></p><pre><code class="python language-python hljs"><span class="hljs-keyword">import</span> operator <span class="hljs-keyword">as</span> op

&lt;bool&gt; = op.not_(&lt;obj&gt;) <span class="hljs-comment"># or, and, not (or/and missing)</span>

&lt;obj&gt; = op.or_/xor/and_(&lt;int/set&gt;, &lt;int/set&gt;) <span class="hljs-comment"># |, ^, &amp;</span>

&lt;int&gt; = op.lshift/rshift(&lt;int&gt;, &lt;int&gt;) <span class="hljs-comment"># &lt;&lt;, &gt;&gt;</span>

&lt;obj&gt; = op.add/sub/mul/truediv/floordiv/mod(&lt;obj&gt;, &lt;obj&gt;) <span class="hljs-comment"># +, -, *, /, //, %</span>

&lt;view&gt; = &lt;array&gt;.transpose() <span class="hljs-comment"># Or: &lt;array&gt;.T</span>

<pre><code class="python language-python hljs">&lt;array&gt; = np.copy/abs/sqrt/log/int64(&lt;array&gt;) <span class="hljs-comment"># Returns new array of the same shape.</span>

&lt;array&gt; = np.apply_along_axis(&lt;func&gt;, axis, &lt;array&gt;) <span class="hljs-comment"># Func can return a scalar or array.</span>

<pre><code class="python language-python hljs">&lt;array&gt; = np.concatenate(&lt;list_of_arrays&gt;, axis=<span class="hljs-number">0</span>) <span class="hljs-comment"># Links arrays along first axis (rows).</span>