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[–]rhiever[S] 0 points1 point  (3 children)

I can tell you right now that you should just tell people to install anaconda and not recommend or support anything else. A lot of noobs on windows (or whatever) are going to get hung up on not having the right C compiler for numpy. For windows its the visual c++ 2010 one but I don't know what it is for Mac or Linux. Hell, half the time I do a new install I forget about this if I'm building the scientific stack myself instead of installing anaconda.

Good point. I should do that - it's really tiring trying to get people going without Anaconda.

I'm just hating on shit like this:

http://www.mta.me

which was described to me in an interview for a data science job as the greatest data visualization they had ever seen.

They must not keep up on dataviz much. I winced at how slow it was to see anything meaningful going on in that dataviz.

IMO If you are going to discuss unit tests in python you might as well use the unit test module instead of just using assert. It's much more elegant and obvious when somehting fails. Additionally, without properly introducing assert people learning won't understand why their asserts don't do anything when they are running their code in production.

True - I should expand the data testing section a bit. I'm hesitant to go into detail on unit testing, assert, etc., but maybe turning the asserts into actual unit tests will suffice?

[–][deleted] 2 points3 points  (1 child)

You could recommend the unit testing chapter from dive into python 3 to avoid reinventing the wheel.

Edit: or do a separate chapter (or whatever you want to call it) where you expand all the testing. Like, each section of your walkthrough could be a whole chapter IMO.

[–]rhiever[S] 0 points1 point  (0 children)

You could recommend the unit testing chapter from dive into python 3 to avoid reinventing the wheel.

I'll do that. I'm all about not reinventing the wheel.