title: Python multiprocess/multithreading to speed up file copying
body: <p>I have a program which copies large numbers of files from one location to another - I'm talking 100,000+ files (I'm copying 314g in image sequences at this moment). They're both on huge, VERY fast network storage RAID'd in the extreme. I'm using shutil to copy the files over sequentially and it is taking some time, so I'm trying to find the best way to opimize this. I've noticed some software I use effectively multi-threads reading files off of the network with huge gains in load times so I'd like to try doing this in python.</p>
  <p>I have no experience with programming multithreading/multiprocessesing - does this seem like the right area to proceed? If so what's the best way to do this? I've looked around a few other SO posts regarding threading file copying in python and they all seemed to say that you get no speed gain, but I do not think this will be the case considering my hardware. I'm nowhere near my IO cap at the moment and resources are sitting around 1% (I have 40 cores and 64g of RAM locally).</p>
  <p><strong>EDIT</strong></p>
  <p>Been getting some up-votes on this question (now a few years old) so I thought I'd point out one more thing to speed up file copies. In addition to the fact that you can easily 8x-10x copy speeds using some of the answers below (seriously!) I have also since found that <code>shutil.copy2</code> is excruciatingly slow for no good reason. Yes, even in python 3+. It is beyond the scope of this question so I won't dive into it here (it's also highly OS and hardware/network dependent), beyond just mentioning that by tweaking the copy buffer size in the <code>copy2</code> function you can increase copy speeds by yet another factor of 10! (however note that you will start running into bandwidth limits and the gains are not linear when multi-threading AND tweaking buffer sizes. At some point it <em>does</em> flat line).</p>