<div dir="ltr"><br><div class="gmail_extra"><br><div class="gmail_quote">On Fri, May 15, 2015 at 4:07 PM, Chris Barker <span dir="ltr"><<a href="mailto:chris.barker@noaa.gov" target="_blank">chris.barker@noaa.gov</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Hi folks.,<div><br></div><div>I did a little "intro to scipy" session as part of a larger Python class the other day, and was dismayed to find that "pip install numpy" still dosn't work on Windows.</div><div><br></div><div>Thanks mostly to Matthew Brett's work, the whole scipy stack is pip-installable on OS-X, it would be really nice if we had that for Windows.</div><div><br></div><div>And no, saying "you should go get Python(x,y) or Anaconda, or Canopy, or...) is really not a good solution. That is indeed the way to go if someone is primarily focusing on computational programming, but if you have a web developer, or someone new to Python for general use, they really should be able to just grab numpy and play around with it a bit without having to start all over again.</div></div></blockquote><div><br></div><div>Unrelated to the pip/wheel discussion.</div><div><br></div><div>In my experience by far the easiest to get something running to play with is using Winpython. Download and unzip (and maybe add to system path) and most of the data analysis stack is available.</div><div><br></div><div>I haven't even bothered yet to properly install a full "system python" on my Windows machine. I'm just working with 3 winpython. (One even has Julia and IJulia included after following the installation instructions for a short time.)</div><div><br></div><div>Josef</div><div><br></div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><br></div><div><br></div><div>My solution was to point folks to Chris Gohlke's site -- which is a Fabulous resource --</div><div><br></div><div>THANK YOU CHRISTOPH!</div><div><br></div><div>But I still think that we should have the basic scipy stack on PyPi as Windows Wheels...</div><div><br></div><div>IIRC, the last run through on this discussion got stuck on the "what hardware should it support" -- wheels do not allow a selection at install time, so we'd have to decide what instruction set to support, and just stick with that. Which would mean that:</div><div><br></div><div>some folks would get a numpy/scipy that would run a bit slower than it might</div><div>and</div><div>some folks would get one that wouldn't run at all on their machine.</div><div><br></div><div>But I don't see any reason that we can't find a compromise here -- do a build that supports most machines, and be done with it. Even now, people have to go get (one way or another) a MKL-based build to get optimum performance anyway -- so if we pick an instruction set support by, say (an arbitrary, and impossible to determine) 95% of machines out there -- we're good to go.</div><div><br></div><div>I take it there are licensing issues that prevent us from putting Chris' Binaries up on PyPi?</div><div><br></div><div>But are there technical issues I'm forgetting here, or do we just need to come to a consensus as to hardware version to support and do it?</div><span class="HOEnZb"><font color="#888888"><div><br></div><div>-Chris</div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br clear="all"><div><br></div>-- <br><div><br>Christopher Barker, Ph.D.<br>Oceanographer<br><br>Emergency Response Division<br>NOAA/NOS/OR&R <a href="tel:%28206%29%20526-6959" value="+12065266959" target="_blank">(206) 526-6959</a> voice<br>7600 Sand Point Way NE <a href="tel:%28206%29%20526-6329" value="+12065266329" target="_blank">(206) 526-6329</a> fax<br>Seattle, WA 98115 <a href="tel:%28206%29%20526-6317" value="+12065266317" target="_blank">(206) 526-6317</a> main reception<br><br><a href="mailto:Chris.Barker@noaa.gov" target="_blank">Chris.Barker@noaa.gov</a></div>
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