On 04/07/2013 05:59 PM, Nathaniel Smith wrote: > On Sun, Apr 7, 2013 at 10:49 PM, Olivier Delalleau <sh...@keba.be> wrote: >> 2013/4/7 <josef.p...@gmail.com> >>> >>> On Sun, Apr 7, 2013 at 5:34 PM, Steve Waterbury <water...@pangalactic.us> >>> wrote: >>>> On 04/07/2013 05:30 PM, Nathaniel Smith wrote: >>>>> On Sun, Apr 7, 2013 at 10:25 PM, Steve Waterbury >>>>> <water...@pangalactic.us> wrote: >>>>>> On 04/07/2013 05:02 PM, Chris Barker - NOAA Federal wrote: >>>>>>> On Sun, Apr 7, 2013 at 8:06 AM, Daπid <davidmen...@gmail.com> wrote: >>>>>>>> On 7 April 2013 16:53, Happyman <bahtiyor_zohi...@mail.ru> wrote: >>>>>>> >>>>>>>> $pip install numpy # to install package "numpy" >>>>>>> >>>>>>> as a warning, last I checked pip did not support binary installs ... >>>>>> >>>>>> Guess you didn't check very recently ;) -- pip does indeed >>>>>> support binary installs. >>>>> >>>>> Binary install in this case means, downloading a pre-built package >>>>> containing .so/.dll files -- very useful if you don't have a working C >>>>> compiler environment on the system you're installing onto. >>>> >>>> Point taken -- just didn't want pip to be sold short. >>>> I'm one of those spoiled Linux people, obviously ... ;) >>> >>> However, pip is really awful on Windows. >>> >>> If you have a virtualenv and you use --upgrade, it wants to upgrade all >>> package dependencies (!), but it doesn't know how (with numpy and scipy). >>> >>> (easy_install was so much nicer.) >>> >>> Josef >> >> >> You can use --no-deps to prevent pip from trying to upgrade dependencies. > > This is only a partial workaround, because this also means that if > there *are* new needed dependencies, they get ignored, resulting in a > possibly broken install. IIRC the full workaround is 'pip install > --no-deps --upgrade foo; pip install foo' > > The other annoying workaround is to instead of using --upgrade, do > something like 'pip install numpy==1.7.1'. This requires knowing (or > looking up) what the latest version is, but once you've done that it > works.
Guess I'm not as easily annoyed -- esp. since looking up what the latest version of numpy is as simple as: waterbug@boson:~$ yolk -V numpy numpy 1.7.1 Steve _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion