Hacker News Reader

Install scipy on Windows and include the Intel linear matrix libraries.

The numpy+mkl wheel is available on Gohlke's site.

Try pip installing scipy or Numpy and you'll see the value of conda.

As if that still was a problem, now that we have wheels, and especially manylinux wheels.

See Myth #6 here: http://jakevdp.github.io/blog/2016/08/25/conda-myths-and-mis...

Valid points. Still most of them are not issues in my daily work.

And by the way Peter, thank you for the amazing work you do.

Although I mostly use the system's numpy package (usually shipped with the distribution), I just tried installing it via pip and had no problem (obviously just one data point).

Just ran `pipenv install scipy numpy`. Installs like any other package..

This is also a useful read:

http://jakevdp.github.io/blog/2016/08/25/conda-myths-and-mis...

I really like conda. It is easy to have multiple enviroments and minimizes the footprint by symbolically linking in what is needed.

Rasterio, fiona and anything else GDAL based always causes me headaches.