What do the > < signs in numpy dtype mean?
<p>What is the difference between <code>dtype='f'</code>, <code>dtype='f4'</code>, <code>dtype='&gt;f4'</code>, <code>dtype'&lt;f4'</code>?
The syntax is not explained in <a href="https://docs.scipy.org/doc/numpy/user/basics.types.html" rel="noreferrer">docs on types</a> (except that 'f' is a shorthand for 'float32'); it is extensively used in the page on <a href="https://docs.scipy.org/doc/numpy/user/basics.rec.html" rel="noreferrer">records</a> but the meaning of <code>&gt;</code>/<code>&lt;</code> is also left unexplained in there.</p>

<p>After some experimentation I found out that</p>

<pre><code>    In [13]: a = np.array([1.0], dtype='f')
    In [15]: print(a.dtype)
    float32
</code></pre>

<p>and</p>

<pre><code>    In [16]: a = np.array([1.0], dtype='&lt;f4')
    In [17]: print(a.dtype)
    float32
</code></pre>

<p>but</p>

<pre><code>    In [18]: a = np.array([1.0], dtype='&gt;f4')
    In [19]: print(a.dtype)
    &gt;f4
</code></pre>

<p>It makes me believe those are not equivalent, which may be the explanation for issues I am facing with an external library.</p>