[wting]

I have a few comments about some of the slides, feel free to correct any misunderstandings.

Dictionary vs Object:

Lookups in both data structures is O(1), the difference being the hashing cost (and an additional memory lookup for heap) vs a single memory lookup on the stack (1 line of assembly).

Squares list:

> ... so every iteration through the list we have the potential need to size the list and copy all the data.

This is no different than stl::vector which has an amortized cost of O(1) for a push_back().

It's not going to be as fast as C, but I'd also argue for a generator version instead:

    def squares(n):
        return (i*i for i in xrange(n))

One of the main reasons people choose Python is for expressiveness and not manually managing memory, although pre-allocation does seem like a good idea.

[kragen]

You mean std::vector, from the STL. And yes, the amortized cost is O(1) per element and thus O(N) in total, but the constant factor and lower-order terms (the O(1) time to do the allocation and garbage-collect it later) do matter.