Speed comparison of R and Python implementations
<p>I have implemented a specific algorithm in <code>R</code>. There exists a <code>Python</code> library which offers an alternative implementation.</p>

<p>I would now like to formally compare the speed of the two implementations to assess which is "more efficient" in different kinds of situations.</p>

<p>What would be the best way to do this? <a href="http://www.r-bloggers.com/r-vs-python-speed-comparison-for-bootstrapping/" rel="nofollow">Here</a>, it is suggested to use the <code>system.time()</code> (in <code>R</code>) and <code>time.time()</code> (in <code>Python</code>) functions to compare the actual executions of the functions. Is this generally recommended? Do these time measures actually measure the same thing?</p>

<p>Would it be an alternative to measure the time of the whole script execution to include "overhead" stuff like variable definitions etc?</p>

<p>PS: I am a regular user of <code>R</code>, but have close to zero experience in <code>Python</code></p>