[zo1]

I did that earlier today:

pip install jupyter

pip install numpy

pip install scipy

pip install scikit-learn

pip install matplotlib

The only problem I had was with OpenCV, which requires manual make installation if you want the contrib package. The other problem was when trying to install scikit-learn, it requires manual pip installation of scipy.

[timClicks]

I would always be worried with installing numpy/scipy via pip that I wouldn't be linking to BLAS/LAPACK correctly.

[rhodysurf]

What do you mean? I have always installed via pip with zero errors on all three platforms.

[moyix]

The worry is not that it will throw an error, it's that it will silently link against lower-performance math libraries and make your code inexplicably slow.

[yeukhon]

The reason you can't is because of the C libraries levaaged must be installed prior to install numpy and scipy.

For example, you can't get through PyYaml unless python-dev is installed on Ubuntu. I am not sure if wheel would fix it but I don't think so.

[takeda]

Wheel is a binary distribution, so files would already be compiled and therefore python-dev would not be needed anymore.

[yeukhon]

Is wheel not default? Or play it elementary :-) how would I avoid this issue in the future?

[takeda]

I did not write anything worthy to send to PIP so don't know exactly but looks like it is up to the developers[1]

Anyway I just noticed that PyPI only supports binary packages for Windows and Mac OS X. Although, you could still generate wheels of packages that you use by using something like this:

    pip wheel -r requirements.txt

You can then install them with pip install <file> or (unfortunately I forgot the option, perhaps it was -i) you can use an option to point to a directory containing wheels and pip install to install the main package. It should use all dependencies in that directory as well.

[1] http://pythonwheels.com/

[techdragon]

the issue with Wheels on Linux, and this is very much a Linux problem, is that the 'pre built' nature of libraries in wheels doesnt play nice with the raw chaos of Linux's package management + distro + kernel ecosystem. I raised the question of FreeBSD and Solaris based wheels at a PyCon when I was in a face to face discussion with someone more knowledgeable, and the answer was 'in theory that should work like Windows & OSX, no one has done the hard work yet.'

So yeah Linux is not the most friendly environment for Python Wheels.