title: Memory usage difference between Windows and Ubuntu for a Numpy array
body: <p>As the title says, I'm seeing a big difference between the memory usage of a numpy array between Windows and Ubuntu.</p>
  
  <p>Here's a simple code to replicate this issue:</p>
  
  <pre class="lang-py prettyprint-override"><code>import numpy as np
  import joblib
  
  a = [1]*1000
  b = [a for i in range(1000)]
  np_arr = np.array(b)
  
  joblib.dump(np_arr, 'arr.h5')
  </code></pre>
  
  <p>If I run this code in a Windows 10 machine, <code>arr.h5</code>'s size is <strong>3907KB</strong>.</p>
  
  <p>But it I run this on Ubuntu 18.04, it's <strong>7812KB</strong></p>
  
  <p>The main issue is that I'm dealing with large datasets and my code runs fine on a Windows machine with 16GB, but I'm having Memory Errors on Ubuntu with 32GB</p>