Context manager, Operator, NumPy

README.md

@@ -1199,7 +1199,7 @@ class Counter:
 ```
 
 ### Context Manager
-* **With statements only work with objects that have enter() and exit() special methods.**
+* **With statements only work on objects that have enter() and exit() special methods.**
 * **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.**
@@ -2160,7 +2160,7 @@ Operator
 ```python
 import operator as op
 <bool> = op.not_(<obj>)                                         # or, and, not (or/and missing)
-<bool> = op.eq/ne/lt/le/gt/ge/contains/is_(<obj>, <obj>)        # ==, !=, <, <=, >, >=, in, is
+<bool> = op.eq/ne/lt/le/gt/ge/is_/contains(<obj>, <obj>)        # ==, !=, <, <=, >, >=, is, in
 <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>)      # +, -, *, /, //, %
@@ -2666,7 +2666,7 @@ import numpy as np
 
 ```python
 <array> = np.copy/abs/sqrt/log/int64(<array>)           # Returns new array of the same shape.
-<array> = <array>.sum/max/mean/argmax/all(axis)         # Passed dimension gets aggregated.
+<array> = <array>.sum/max/mean/argmax/all(axis)         # Aggregates specified dimension.
 <array> = np.apply_along_axis(<func>, axis, <array>)    # Func can return a scalar or array.
 ```
 

index.html

@@ -1017,7 +1017,7 @@ Z = dataclasses.make_dataclass(<span class="hljs-string">'Z'</span>, [<span clas
 (<span class="hljs-number">1</span>, <span class="hljs-number">2</span>, <span class="hljs-number">3</span>)
 </code></pre>
 <div><h3 id="contextmanager">Context Manager</h3><ul>
-<li><strong>With statements only work with objects that have enter() and exit() special methods.</strong></li>
+<li><strong>With statements only work on objects that have enter() and exit() special methods.</strong></li>
 <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>
@@ -1781,7 +1781,7 @@ CompletedProcess(args=[<span class="hljs-string">'bc'</span>, <span class="hljs-
 </ul>
 <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;bool&gt; = op.eq/ne/lt/le/gt/ge/contains/is_(&lt;obj&gt;, &lt;obj&gt;)        <span class="hljs-comment"># ==, !=, &lt;, &lt;=, &gt;, &gt;=, in, is</span>
+&lt;bool&gt; = op.eq/ne/lt/le/gt/ge/is_/contains(&lt;obj&gt;, &lt;obj&gt;)        <span class="hljs-comment"># ==, !=, &lt;, &lt;=, &gt;, &gt;=, is, in</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>
@@ -2190,7 +2190,7 @@ $ snakeviz test.prof                                            <span class="hlj
 &lt;view&gt;  = &lt;array&gt;.transpose()                           <span class="hljs-comment"># Or: &lt;array&gt;.T</span>
 </code></pre>
 <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; = &lt;array&gt;.sum/max/mean/argmax/all(axis)         <span class="hljs-comment"># Passed dimension gets aggregated.</span>
+&lt;array&gt; = &lt;array&gt;.sum/max/mean/argmax/all(axis)         <span class="hljs-comment"># Aggregates specified dimension.</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>
 </code></pre>
 <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>