<p dir="auto">One of the <a href="https://numpy.org/devdocs/dev/releasing.html?highlight=how%20release#build-and-archive-documentation" rel="nofollow">last steps in the release</a> is to upload documentation to numpy.org/doc via the <a href="https://github.com/numpy/doc">https://github.com/numpy/doc</a> repo. This is new to 1.18.</p>
<p dir="auto">It would be nice if someone else would work through the steps to make sure the directions are clear,  but I can do it if desired.</p>
<p dir="auto">Floating point result will appear if using numpy array of type uint64. This leads to numerically incorrect result when number is sufficiently large.<br>
Tested on Python 3.5.2, numpy 1.13.3, on Windows 10 Build 17046.1000 (Insider Preivew)</p>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="import numpy as np
a = np.array([2], np.uint64)
print(31328281838316189 % a[0]) # which gives 0.0, not 1 as expected
print(31328281838316189 // a[0]) # which gives 1.56641409192e+16, not 15664140919158094 as expected"><pre class="notranslate"><span class="pl-k">import</span> <span class="pl-s1">numpy</span> <span class="pl-k">as</span> <span class="pl-s1">np</span>
<span class="pl-s1">a</span> <span class="pl-c1">=</span> <span class="pl-s1">np</span>.<span class="pl-en">array</span>([<span class="pl-c1">2</span>], <span class="pl-s1">np</span>.<span class="pl-s1">uint64</span>)
<span class="pl-en">print</span>(<span class="pl-c1">31328281838316189</span> <span class="pl-c1">%</span> <span class="pl-s1">a</span>[<span class="pl-c1">0</span>]) <span class="pl-c"># which gives 0.0, not 1 as expected</span>
<span class="pl-en">print</span>(<span class="pl-c1">31328281838316189</span> <span class="pl-c1">//</span> <span class="pl-s1">a</span>[<span class="pl-c1">0</span>]) <span class="pl-c"># which gives 1.56641409192e+16, not 15664140919158094 as expected</span></pre></div>
<p dir="auto">This problem will not occur if I replace uint64 with int64.</p>