[Numpy-discussion] Sources more confusing in Python

[Steve Waterbury]

On 04/07/2013 05:59 PM, Nathaniel Smith wrote:
> On Sun, Apr 7, 2013 at 10:49 PM, Olivier Delalleau <shish at keba.be> wrote:
>> 2013/4/7 <josef.pktd at gmail.com>
>>>
>>> On Sun, Apr 7, 2013 at 5:34 PM, Steve Waterbury <waterbug at pangalactic.us>
>>> wrote:
>>>> On 04/07/2013 05:30 PM, Nathaniel Smith wrote:
>>>>> On Sun, Apr 7, 2013 at 10:25 PM, Steve Waterbury
>>>>> <waterbug at 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 <davidmenhur at gmail.com> wrote:
>>>>>>>> On 7 April 2013 16:53, Happyman <bahtiyor_zohidov at 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 at boson:~$ yolk -V numpy
numpy 1.7.1

Steve