[scikit-learn] Declaring numpy and scipy dependencies?

Andreas Mueller t3kcit at gmail.com
Wed Aug 31 17:15:01 EDT 2016

On 07/28/2016 03:16 PM, Matthew Brett wrote:
> On Thu, Jul 28, 2016 at 8:10 PM, Andreas Mueller <t3kcit at gmail.com> wrote:
>> On 07/28/2016 03:04 PM, Matthew Brett wrote:
>>> On Thu, Jul 28, 2016 at 7:55 PM, Sebastian Raschka
>>> <mail at sebastianraschka.com> wrote:
>>>> I think that should work fine for the `pip install scikit-learn`,
>>>> however, I think the problem was with upgrading, right?
>>>> E.g., if you run
>>>> pip install scikit-learn --upgrade
>>>> it would try to upgrade numpy and scipy as well, which may not be
>>>> desired. I think the only workaround would be to run
>>>> pip install scikit-learn --upgrade --no-deps
>>>> unless they changed the behavior recently. I mean, it’s not really a
>>>> problem, but many users may not know about the --no-deps flag.
>>> Also - the install will work fine for platforms with wheels, but is
>>> still bad for platforms without - like the Raspberry Pi.
>> Hm... so these would be ARM wheels? Or Raspberry Pi specific ones?
> No, they'd have to be Raspberry Pi specific ones because no-one has
> worked out a general ARM-wide specification, as we have for Intel
> Linux = manylinux1.
Following up on this thread, I'm trying to write better installation 

What's the best-practice for cases when there are no wheels?
I imagine there's also no conda channel for Raspberry Pi.

So is it the package manager?


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