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Author here. Although the software contained in the base is indeed relatively easy to install, you'd be surprised how often people struggle installing Python an
by jeroenjanssens 12y ago
Author here. Although the software contained in the base is indeed relatively easy to install, you'd be surprised how often people struggle installing Python and its packages on Mac OS X or Microsoft Windows!
The initial reason I created DST was that I'm currently writing a book called Data Science at the Command Line. Installing the command-line tools discussed in this book is unfortunately not straightforward. I wanted to offer potential readers a Vagrant box (with a shell provisioner) that installs these command-line tools. Similar to what Matthew Russell has done for his book Mining the Social Web [1]. This blog post [2] provides some more explanation and compares four different solutions.
The software packages that you mention sure are exciting! If there is an author or teacher that wants to teach these to her readers or students, then we should create a bundle (i.e., Ansible playbook) for them!
[1] https://github.com/ptwobrussell/Mining-the-Social-Web-2nd-Edition https://github.com/ptwobrussell/Mining-the-Social-Web-2nd-Ed...
[2] http://jeroenjanssens.com/2013/12/07/lean-mean-data-science-machine.html http://jeroenjanssens.com/2013/12/07/lean-mean-data-science-...
- paulgb 12y agoIt's a pain to install BLAS and the numpy family on a box you don't have root on so I definitely see value in the VM approach. Does being in a VM degrade the performance to the point where this is mainly a teaching tool or is it comparable to a native install?