Having seen references to iPython from my first ever google for 'python', I somehow managed to disregarded it with the sentiment of who works in a console?? or a browser notebook? what is that? ...
I need an IDE with folders / modules / files / projects... what a shame I wasted so much time...
I blame too many years in Visual Studio, Eclipse, Jetbrains IDEs and XCode for making me ignore this long.
Thankfully I have gotten past that, and this book helps you getting there fast... < 150 pages fast.
IPython, and especially the IPython Notebooks are great tools. I can see it being awesome for a whole number of tasks:
- learning python and working through books and tutorials
- running data mining brainstorming sessions
- showing people the latest and greatest stuff you've have come up
- quick cython implementations & performance experiments
- processing multiple cores / servers
- I even saw Harvard now uses it for homework assignments.
That list can just go on and on, but coming back to the book. It was targeted at 2.7, obviously I didn't listen and worked through it in Pythong 3.3., but thankfully there were only a couple very minor changes:
The book uses urllib2 in a couple, that can be replaced with:
r = urllib.request.urlopen('
For the networkx example where was also a slight change:
sg = nx.connected_component_subgraphs(g)
This returned a list of graphs, not a graph, so I just looped the following:
for grp in sg:
Then for the maps exercise I did not have all the dependancies:
I need to Install GEOS...I used MacPorts for that:
sudo port install geos
Then in my .bash_profile I added:
To refresh the profile:
Then for Basemap, downloaded the zip, here.
Followed by(in basemap-1.0.7 dir):
python setup.py install
That's about it, concise intro for a great product.
Now to really put it to the test the next book I am working through:
Building Machine Learning Systems with Python